Agenda packet — Colma City Council, January 25, 2023 (part 3 of 3)

Source: U.S. Census Bureau, 2020 Census State Redistricting Data (Public Law 94-171) Summary File, 2020 Census of Population and Housing, Table P002.

Note: The plot shows the racial distribution at the census block level for Town of Colma and vicinity. Dots in each census block are randomly placed and should not be construed as actual placement of people.

To understand how each city contributes to the total segregation of the Bay Area, one can look at the difference in the racial composition of a jurisdiction compared to the racial composition of the region as a whole. The racial demographics in Colma for the years 2000, 2010, and 2020 can be found in Table 4 below. The table also provides the racial composition of the nine-county Bay Area. As of 2020, Colma has a lower share of white residents than the Bay Area as a whole, a higher share of Latinx residents, a lower share of Black residents, and a higher share of Asian/Pacific Islander residents.

17 Table 4: Population by Racial Group, Colma and the Region Colma Bay Area
Race 2000 2010 2020 2020
Asian/Pacific Islander 23.5% 33.8% 29.5% 28.2%
Black/African American 0.9% 2.6% 3.3% 5.6%
Latinx 43.9% 39.5% 41.2% 24.4%
Other or Multiple Races 3.9% 4.1% 5.6% 5.9%
White 27.7% 20.1% 20.4% 35.8%
Universe: Population.

Source: IPUMS National Historical Geographic Information System (NHGIS). U.S. Census Bureau, 2020 Census State Redistricting Data (Public Law 94-171) Summary File, 2020 Census of Population and Housing, Table P002. Data from 2010 is from U.S. Census Bureau, Census 2010, Table P4. Data for 2000 is standardized to 2010 census tract geographies and is from U.S. Census Bureau, Census 2000, Table P004.

Figure 6 below compares the racial demographics in Colma to those of all 109 Bay Area jurisdictions. 11 In this chart, each dot represents a Bay Area jurisdiction. For each racial group, the spread of dots represents the range of that group’s representation among Bay Area jurisdictions. Additionally, the black line within each racial group notes the percentage of the population of Town of Colma represented by that group and how that percentage ranks among all 109 jurisdictions. Local staff can use this chart to compare the representation of different racial groups in their jurisdiction to those groups’ representation in other jurisdictions in the region, which can indicate the extent of segregation between this jurisdiction and the region.

11 While comparisons of segregation measures are made only using the 104 jurisdictions with more than one census tract, this comparison of jurisdiction level demographic data can be made using all 109 jurisdictions.

18 Figure 6: Racial Demographics of Colma Compared to All Bay Area Jurisdictions (2020) Universe: Bay Area Jurisdictions.

Source U.S. Census Bureau, 2020 Census State Redistricting Data (Public Law 94-171) Summary File, 2020 Census of Population and Housing, Table P002.

The map in Figure 7 below also illustrates regional racial segregation between Colma and other jurisdictions. This map demonstrates how the percentage of people of color in Colma and surrounding jurisdictions compares to the Bay Area as a whole:
• Jurisdictions shaded orange have a share of people of color that is less than the Bay Area as a whole, and the degree of difference is greater than five percentage points. • Jurisdictions shaded white have a share of people of color comparable to the regional percentage of people of color (within five percentage points). • Jurisdictions shaded grey have a share of people of color that is more than five percentage points greater than the regional percentage of people of color.

19 Figure 7: Comparing the Share of People of Color in Colma and Vicinity to the Bay Area (2020)
Universe: Population.

Source: U.S. Census Bureau, 2020 Census State Redistricting Data (Public Law 94-171) Summary File, 2020 Census of Population and Housing, Table P002.

Note: People of color refer to persons not identifying as non-Hispanic white. The nine-county Bay Area is the reference region for this map.

Segregation between jurisdictions in the region can also be analyzed by calculating regional values for the segregation indices discussed previously. Table 5 presents dissimilarity index, isolation index, and Theil’s H index values for racial segregation for the entire nine-county Bay Area in 2010 and 2020. In the previous section of this report focused on neighborhood level racial segregation, these indices were calculated by comparing the racial demographics of the census tracts within a jurisdiction to the demographics of the jurisdiction as a whole. In Table 5, these measures are calculated by comparing the racial demographics of local jurisdictions to the region’s racial makeup. For example, looking at the 2020 data, Table 5 shows the white isolation index value for the region is 0.429, meaning that on average white Bay Area residents live in a jurisdiction that is 42.9% white in 2020. An example of regional dissimilarity index values in Table 5 is the Black/white dissimilarity index value of 0.459, which means that across the region 45.9% of Black (or white) residents would need to move to a different jurisdiction to evenly distribute Black and white residents across Bay Area jurisdictions. The dissimilarity index values in Table 5 reflect recommendations made in HCD’s AFFH guidance for calculating dissimilarity at the region level.12 The regional value for the Theil’s H index measures how

12 For more information on HCD’s recommendations regarding data considerations for analyzing integration and segregation patterns, see page 31 of the AFFH Guidance Memo.

20 diverse each Bay Area jurisdiction is compared to the racial diversity of the whole region. A Theil’s H Index value of 0 would mean all jurisdictions within the Bay Area have the same racial demographics as the entire region, while a value of 1 would mean each racial group lives exclusively in their own separate jurisdiction. The regional Theil’s H index value for racial segregation decreased slightly between 2010 and 2020, meaning that racial groups in the Bay Area are now slightly less separated by the borders between jurisdictions.

Table 5: Regional Racial Segregation Measures
Index Group 2010 2020
Isolation Index Regional Level
Asian/Pacific Islander 0.317 0.378
Black/African American 0.144 0.118
Latinx 0.283 0.291
White 0.496 0.429
People of Color 0.629 0.682
Dissimilarity Index Regional Level
Asian/Pacific Islander vs. White 0.384 0.369
Black/African American vs. White 0.475 0.459
Latinx vs. White 0.301 0.297
People of Color vs. White 0.296 0.293
Theil's H Multi-racial All Racial Groups 0.103 0.097
Universe: Population.

21 3 INCOME SEGREGATION I N TOWN OF COLMA
Definition of Terms - Income Groups
When analyzing segregation by income, this report uses income group designations consistent with the Regional Housing Needs Allocation and the Housing Element:

Very low-income: individuals earning less than 50% of Area Median Income (AMI)
Low-income: individuals earning 50%-80% of AMI
Moderate-income: individuals earning 80%-120% of AMI
Above moderate-income: individuals earning 120% or more of AMI Additionally, this report uses the term “lower-income” to refer to all people who earn less than 80% of AMI, which includes both low-income and very low-income individuals.

The income groups described above are based on U.S. Department of Housing and Urban Development (HUD) calculations for AMI. HUD calculates the AMI for different metropolitan areas, and the nine county Bay Area includes the following metropolitan areas: Napa Metro Area (Napa County), Oakland-Fremont Metro Area (Alameda and Contra Costa Counties), San Francisco Metro Area (Marin, San Francisco, and San Mateo Counties), San Jose-Sunnyvale-Santa Clara Metro Area (Santa Clara County), Santa Rosa Metro Area (Sonoma County), and Vallejo- Fairfield Metro Area (Solano County).

The income categories used in this report are based on the AMI for the HUD metro area where this jurisdiction is located.

3.1 Neighborhood Level Income Segregation ( within Colma) Income segregation can be measured using similar indices as racial segregation. Income dot maps, similar to the racial dot maps shown in Figures 1 and 5, are useful for visualizing segregation between multiple income groups at the same time. The income dot map of Colma in Figure 8 below offers a visual representation of the spatial distribution of income groups within the jurisdiction. As with the racial dot maps, when the dots show lack of a pattern or clustering, income segregation measures tend to be lower, and conversely, when clusters are apparent, the segregation measures may be higher as well.

22 Figure 8: Income Dot Map of Colma (2015)
Universe: Population.

Source: U.S. Department of Housing and Urban Development, American Community Survey 5-Year 2011-2015 Low- and Moderate- Income Summary Data.

Note: The plot shows the income group distribution at the census block group level for Town of Colma and vicinity. Dots in each block group are randomly placed and should not be construed as actual placement of individuals.

The isolation index values for all income groups in Colma for the years 2010 and 2015 can be found in Table 6 below.13 Very Low-income residents are the most isolated income group in Colma. Colma’s isolation index of 0.416 for these residents means that the average Very Low-income resident in Colma lives in a neighborhood that is 41.6% Very Low-income. Among all income groups, the Very Low-income population’s isolation index has changed the most over time, becoming more segregated from other income groups between 2010 and 2015.

Similar to the tables presented earlier for neighborhood racial segregation, the “Bay Area Average” column in Table 6 provides the average isolation index value across Bay Area jurisdictions for different income groups in 2015. The data in this column can be used as a comparison to provide context for the levels of segregation experienced by income groups in this jurisdiction. For example, Table 6 indicates the average isolation index value for very low-income residents across Bay Area jurisdictions is 0.269,

13 This report presents data for income segregation for the years 2010 and 2015, which is different than the time periods used for racial segregation. This deviation stems from the data source recommended for income segregation calculations in HCD’s AFFH Guidelines. This data source most recently updated with data from the 2011-2015 American Community Survey 5-year estimates. For more information on HCD’s recommendations for calculating income segregation, see page 32 of HCD’s AFFH Guidelines.

23 meaning that in the average Bay Area jurisdiction a very low-income resident lives in a neighborhood that is 26.9% very low-income.

Table 6: Income Group Isolation Index Values for Segregation within Colma Colma Bay Area
Average
Income Group 2010 2015 2015
Very Low-Income (<50% AMI) 0.265 0.416 0.269
Low-Income (50%-80% AMI) 0.240 0.302 0.145
Moderate-Income (80%-120% AMI) 0.299 0.150 0.183
Above Moderate-Income (>120% AMI) 0.228 0.160 0.507
Universe: Population.

Source: Data for 2015 is from U.S. Department of Housing and Urban Development, American Community Survey 5-Year 2011- 2015 Low- and Moderate-Income Summary Data. Data for 2010 is from U.S. Department of Housing and Urban Development, American Community Survey 5-Year 2006-2010 Low- and Moderate-Income Summary Data.

Figure 9 below shows how income group isolation index values in Colma compare to values in other Bay Area jurisdictions. In this chart, each dot represents a Bay Area jurisdiction. For each income group, the spread of dots represents the range of isolation index values among Bay Area jurisdictions.

Additionally, the black line within each income group notes the isolation index value for that group in Colma, and each dashed red line represents the Bay Area average for the isolation index for that group.

Local staff can use this chart to contextualize how segregation levels for income groups in their jurisdiction compare to the rest of the region.

24 Figure 9: Income Group Isolation Index Values for Colma Compared to Other Bay Area Jurisdictions (2015)
Universe: Bay Area Jurisdictions.

Source: U.S. Department of Housing and Urban Development, American Community Survey 5-Year 2011-2015 Low- and Moderate- Income Summary Data.

Table 7 below provides the dissimilarity index values indicating the level of segregation in Colma between residents who are lower-income (earning less than 80% of AMI) and those who are not lower- income (earning above 80% of AMI). This data aligns with the requirements described in HCD’s AFFH Guidance Memo for identifying dissimilarity for lower-income households. 14 Segregation in Colma
between lower-income residents and residents who are not lower-income decreased between 2010 and 2015. Additionally, Table
7 shows dissimilarity index values for the level of segregation in Albany between residents who are very low-income (earning less than 50% of AMI) and those who are above moderate-income (earning above 120% of AMI). This supplementary data point provides additional nuance to an analysis of income segregation, as this index value indicates the extent to which a jurisdiction’s lowest and highest income residents live in separate neighborhoods.

Similar to other tables in this report, the “Bay Area Average” column shows the average dissimilarity index values for these income group pairings across Bay Area jurisdictions in 2015. For example, Table 7 indicates that the average dissimilarity index between lower-income residents and other residents in a Bay Area jurisdiction is 0.198, so on average 19.8% of lower-income residents in a Bay Area jurisdiction would need to move to a different neighborhood within the jurisdiction to create perfect income group integration in that jurisdiction.

14 For more information, see page 32 of HCD’s AFFH Guidance Memo.

25 In 2015, the income segregation in Colma between lower-income residents and other residents was lower than the average value for Bay Area jurisdictions (See Table 7). This means that the lower- income residents are less segregated from other residents within Colma compared to other Jurisdictions in the region.

Table 7: Income Group Dissimilarity Index Values for Segregation within Colma Colma Bay Area
Average
Income Group 2010 2015 2015
Below 80% AMI vs. Above 80% AMI 0.108 0.001 0.198
Below 50% AMI vs. Above 120% AMI 0.000 0.097 0.253
Universe: Population.

Figure 10 below shows how dissimilarity index values for income segregation in Colma compare to values in other Bay Area jurisdictions. In this chart, each dot represents a Bay Area jurisdiction. For each income group pairing, the spread of dots represents the range of dissimilarity index values among Bay Area jurisdictions. Additionally, the black line within each income group pairing notes the dissimilarity index value in Colma, and each dashed red line represents the Bay Area average for the dissimilarity index for that pairing. Local staff can use this chart to contextualize how segregation levels between lower-income residents and wealthier residents in their jurisdiction compared to the rest of the region.

26 Figure 10: Income Group Dissimilarity Index Values for Colma Compared to Other Bay Area Jurisdictions (2015)
Universe: Bay Area Jurisdictions.

Source: U.S. Department of Housing and Urban Development, American Community Survey 5-Year 2011-2015 Low- and Moderate- Income Summary Data.

The Theil’s H Index values for neighborhood income group segregation in Colma for the years 2010 and 2015 can be found in Table 8 below. The “Bay Area Average” column in this table provides the average Theil’s H Index value across Bay Area jurisdictions for different income groups in 2015. By 2015, the Theil’s H Index value for income segregation in Colma was about the same amount as it had been in 2010. In 2015, the Theil’s H Index value for income group segregation in Colma was lower than the average value for Bay Area jurisdictions, indicating there is less neighborhood level income segregation in Colma than in the average Bay Area city.

Table 8 : Theil’s H Index Values for Income Segregation within Colma Colma Bay Area
Average
Index 2010 2015 2015
Theil's H Multi-income 0.012 0.012 0.043
Universe: Population.

27 Figure 11 below shows how Theil’s H index values for income group segregation in Colma compare to values in other Bay Area jurisdictions in 2015. In this chart, each dot represents a Bay Area jurisdiction.

Additionally, the black line notes the Theil’s H index value for income group segregation in Colma, and the dashed red line represents the average Theil’s H index value across Bay Area jurisdictions. Local staff can use this chart to compare how neighborhood income group segregation levels in their jurisdiction compare to other jurisdictions in the region.

Figure 11: Income Group Theil’s H Index Values for Colma Compared to Other Bay Area Jurisdictions (2015)
Universe: Bay Area Jurisdictions.

Source: U.S. Department of Housing and Urban Development, American Community Survey 5-Year 2011-2015 Low- and Moderate- Income Summary Data.

3.2 Regional Income Segregation ( between Colma and other jurisdictions)
At the regional level, segregation is measured between jurisdictions instead of between neighborhoods.

Income dot maps are not only useful for examining neighborhood income segregation within a jurisdiction, but these maps can also be used to explore income demographic differences between jurisdictions in the region. Figure 12 below presents an income dot map showing the spatial distribution of income groups in Colma as well as in nearby Bay Area jurisdictions.

28 Figure 12: Income Dot Map of Colma and Surrounding Areas (2015) Universe: Population.

Source: U.S. Department of Housing and Urban Development, American Community Survey 5-Year 2011-2015 Low- and Moderate- Income Summary Data.

When looking at income segregation between jurisdictions in the Bay Area, one can examine how Colma differs from the region. The income demographics in Colma for the years 2010 and 2015 can be found in Table 9 below. The table also provides the income composition of the nine-county Bay Area in 2015. As of that year, Colma had a higher share of very low-income residents than the Bay Area as a whole, a higher share of low-income residents, a lower share of moderate-income residents, and a lower share of above moderate-income residents.

Table 9: Population by Income Group, Colma and the Region Colma Bay Area
Income Group 2010 2015 2015
Very Low-Income (<50% AMI) 20.85% 37.26% 28.7%
Low-Income (50%-80% AMI) 28.23% 20.38% 14.3%
Moderate-Income (80%-120% AMI) 26.94% 13.38% 17.6%
Above Moderate-Income (>120% AMI) 23.98% 28.98% 39.4%

29 Universe: Population.

Source: Data for 2015 is from Housing U.S. Department of and Urban Development, American Community Survey 5-Year 2011- 2015 Low- and Moderate-Income Summary Data. Data for 2010 is from U.S. Department of Housing and Urban Development, American Community Survey 5-Year 2006-2010 Low- and Moderate-Income Summary Data.

Figure 13 below compares the income demographics in Colma to other Bay Area jurisdictions. 15 Like the chart in Figure 3, each dot represents a Bay Area jurisdiction. For each income group, the spread of dots represents the range of that group’s representation among Bay Area jurisdictions. The smallest range is among jurisdictions’ moderate-income populations, while Bay Area jurisdictions vary the most in the share of their population that is above moderate-income. Additionally, the black lines within each income group note the percentage of Colma population represented by that group and how that percentage ranks among other jurisdictions. Local staff can use this chart to compare the representation of different income groups in their jurisdiction to those groups’ representation in other jurisdictions in the region, which can indicate the extent of segregation between this jurisdiction and the region.

Figure 13: Income Demographics of Colma Compared to Other Bay Area Jurisdictions (2015)
Universe: Bay Area Jurisdictions.

Source: U.S. Department of Housing and Urban Development, American Community Survey 5-Year 2011-2015 Low- and Moderate- Income Summary Data.

15 While comparisons of segregation measures are made only using the 104 jurisdictions with more than one census tract, this comparison of jurisdiction level demographic data can be made using all 109 jurisdictions.

30 Income segregation between jurisdictions in the region can also be analyzed by calculating regional values for the segregation indices discussed previously. Similar to the regional racial segregation measures shown in Table 5, Table 10 presents dissimilarity index, isolation index, and Theil’s H index values for income segregation for the entire nine-county Bay Area in 2010 and 2015. In the previous section of this report focused on neighborhood level income segregation, segregation indices were calculated by comparing the income demographics of the census tracts within a jurisdiction to the demographics of the jurisdiction as a whole. In Table 10, these measures are calculated by comparing the income demographics of local jurisdictions to the region’s income group makeup. For example, looking at 2015 data, Table 10 shows the regional isolation index value for very low-income residents is

0.315 for 2015, meaning that on average very low-income Bay Area residents live in a jurisdiction that is 31.5% very low-income. The regional dissimilarity index for lower-income residents and other residents is 0.194 in 2015, which means that across the region 19.4% of lower-income residents would need to move to a different jurisdiction to create perfect income group integration in the Bay Area as a whole. The regional value for the Theil’s H index measures how diverse each Bay Area jurisdiction is compared to the income group diversity of the whole region. A Theil’s H Index value of 0 would mean all jurisdictions within the Bay Area have the same income demographics as the entire region, while a value of 1 would mean each income group lives exclusively in their own separate jurisdiction. The regional Theil’s H index value for income segregation decreased slightly between 2010 an d 2015, meaning that income groups in the Bay Area are now slightly less separated by the borders between jurisdictions.

Table 10: Regional Income Segregation Measures
Index Group 2010 2015
Isolation Index Regional Level
Very Low-Income (<50% AMI) 0.277 0.315
Low-Income (50%-80% AMI) 0.157 0.154
Moderate-Income (80%-120% AMI) 0.185 0.180
Above Moderate-Income (>120% AMI) 0.467 0.435
Dissimilarity Index Regional Level
Below 80% AMI vs. Above 80% AMI 0.186 0.194
Below 50% AMI vs. Above 120% AMI 0.238 0.248
Theil's H Multi-income All Income Groups 0.034 0.032
Universe: Population.

31 4 APPENDIX 1: SUMMARY OF FINDINGS

4.1 Segregation in Town of Colma
• The isolation index measures the segregation of a single group, and the dissimilarity index measures segregation between two different groups. The Theil’s H-Index can be used to measure segregation between all racial or income groups across the city at once. • As of 2020, Latinx residents are the most segregated compared to other racial groups in Colma, as measured by the isolation index. Latinx residents live in neighborhoods where they are less likely to come into contact with other racial groups.
• Among all racial groups, the white population’s isolation index value has changed the most over time, becoming less segregated from other racial groups between 2000 and 2020. • According to the dissimilarity index, within Colma the highest level of racial segregation is between Asian and white residents.16
• According to the Theil’s H-Index, neighborhood racial segregation in Colma increased between 2010 and 2020. Neighborhood income segregation stayed about the same between 2010 and 2015.
• Very Low-income residents are the most segregated compared to other income groups in Colma. Very Low-income residents live in neighborhoods where they are less likely to encounter residents of other income groups.
• Among all income groups, the Very Low-income population’s segregation measure has changed the most over time, becoming more segregated from other income groups between 2010 and 2015.
• According to the dissimilarity index, segregation between lower-income residents and residents who are not lower-income has decreased between 2010 and 2015. In 2015, the income segregation in Colma between lower-income residents and other residents was lower than the average value for Bay Area jurisdictions.

4.2 Segregation Between Town of Colma and Other jurisdictions in the Bay Area Region
• Colma has a lower share of white residents than other jurisdictions in the Bay Area as a whole, a higher share of Latinx residents, a lower share of Black residents, and a higher share of Asian/Pacific Islander residents.

16 The analysis conducted for this report suggests that dissimilarity index values are unreliable for a population group if that group represents approximately less than 5% of the jurisdiction’s total population. ABAG/MTC recommends that when cities have population groups that are less than 5% of the jurisdiction’s population (see Table 15 in Appendix 2), jurisdiction staff could focus on the isolation index or Thiel’s H-Index to gain a more accurate understanding of neighborhood-level racial segregation in their jurisdiction.

32 • Regarding income groups, Colma has a higher share of very low-income residents than other jurisdictions in the Bay Area as a whole, a higher share of low-income residents, a lower share of moderate-income residents, and a lower share of above moderate-income residents.

33 5 APPENDIX 2: SEGREGAT ION DATA
Appendix 2 combines tabular data presented throughout this report into a more condensed format. This data compilation is intended to enable local jurisdiction staff and their consultants to easily reference this data and re-use the data in the Housing Element or other relevant documents/analyses.

Table 11 in this appendix combines data from Table 1, Table 2, and Table 3 in the body of the report.

Table 12 in this appendix combines data from Table 6, Table 7, and Table 8 in the body of the report.

Table 13 represents a duplication of Table 5 in the body of the report; Table 14 represents a duplication of Table 10 in the body of the report; Table 15 in this appendix represents a duplication of Table 4 in the body of the report, while Table 16 represents a duplication of Table 9 in the body of the report.

Table 11: Neighborhood Racial Segregation Levels in Colma Colma Bay Area
Average
Index Race 2000 2010 2020 2020
Isolation
Asian/Pacific Islander 0.227 0.347 0.302 0.245
Black/African American 0.024 0.024 0.036 0.053
Latinx 0.349 0.345 0.412 0.251
White 0.403 0.257 0.207 0.491
Dissimilarity
Asian/Pacific Islander vs. White 0.172 0.074 0.079 0.185 Black/African American vs. White 0.170* 0.059* 0.055* 0.244 Latinx vs. White 0.092 0.065 0.040 0.207
People of Color vs. White 0.120 0.067 0.045 0.168
Theil's H Multi-racial All 0.018 0.005 0.009 0.042
Universe: Population.

Source: IPUMS National Historical Geographic Information System (NHGIS). U.S. Census Bureau, 2020 Census State Redistricting Data (Public Law 94-171) Summary File, 2020 Census of Population and Housing, Table P002. Data from 2010 is from U.S. Census Bureau, 2010 Census of Population and Housing, Table P4. Data for 2000 is standardized to 2010 census tract geographies and is from U.S. Census Bureau, Census 2000, Table P004.

Note: If a number is marked with an asterisk (*), it indicates that the index is based on a racial group making up less than 5 percent of the jurisdiction population, leading to unreliable numbers.

34 Table 12: Neighborhood Income Segregation Levels in Colma Colma Bay Area
Average
Index Income Group 2010 2015 2015
Isolation
Very Low-Income (<50% AMI) 0.265 0.416 0.269
Low-Income (50%-80% AMI) 0.240 0.302 0.145
Moderate-Income (80%-120% AMI) 0.299 0.150 0.183
Above Moderate-Income (>120% AMI) 0.228 0.160 0.507
Dissimilarity
Below 80% AMI vs. Above 80% AMI 0.108 0.001 0.198
Below 50% AMI vs. Above 120% AMI 0.000 0.097 0.253
Theil's H Multi-racial All 0.012 0.012 0.043
Universe: Population.

Source: Income data for 2015 is from U.S. Department of Housing and Urban Development, American Community Survey 5-Year 2011-2015 Low- and Moderate-Income Summary Data. Data for 2010 is from U.S. Department of Housing and Urban Development, American Community Survey 5-Year 2006-2010 Low- and Moderate-Income Summary Data.

35 Table 13: Regional Racial Segregation Measures
Index Group 2010 2020
Isolation Index Regional Level
Asian/Pacific Islander 0.317 0.378
Black/African American 0.144 0.118
Latinx 0.283 0.291
White 0.496 0.429
People of Color 0.629 0.682
Dissimilarity Index Regional Level
Asian/Pacific Islander vs. White 0.384 0.369
Black/African American vs. White 0.475 0.459
Latinx vs. White 0.301 0.297
People of Color vs. White 0.296 0.293
Theil's H Multi-racial All Racial Groups 0.103 0.097
Universe: Population.

Table 14: Regional Income Segregation Measures
Index Group 2010 2015
Isolation Index Regional Level
Very Low-Income (<50% AMI) 0.277 0.315
Low-Income (50%-80% AMI) 0.157 0.154
Moderate-Income (80%-120% AMI) 0.185 0.180
Above Moderate-Income (>120% AMI) 0.467 0.435
Dissimilarity Index Regional Level
Below 80% AMI vs. Above 80% AMI 0.186 0.194
Below 50% AMI vs. Above 120% AMI 0.238 0.248
Theil's H Multi-income All Income Groups 0.034 0.032
Universe: Population.

36 Table 15: Population by Racial Group, Colma and the Region Colma Bay Area
Race 2000 2010 2020 2020
Asian/Pacific Islander 23.51% 33.76% 29.53% 35.8%
Black/African American 0.92% 2.57% 3.32% 5.6%
Latinx 43.91% 39.51% 41.21% 28.2%
Other or Multiple Races 3.95% 4.07% 5.57% 24.4%
White 27.71% 20.09% 20.37% 5.9%
Universe: Population.

Source: IPUMS National Historical Geographic Information System (NHGIS). U.S. Census Bureau, 2020 Census State Redistricting Data (Public Law 94-171) Summary File, 2020 Census of Population and Housing, Table P002. Data from 2010 is from U.S. Census Bureau, 2010 Census of Population and Housing, Table P4. Data for 2000 is standardized to 2010 census tract geographies and is from U.S. Census Bureau, Census 2000, Table P004.

Table 16: Population by Income Group, Colma and the Region Colma Bay Area
Income Group 2010 2015 2015
Very Low-Income (<50% AMI) 20.85% 37.26% 28.7%
Low-Income (50%-80% AMI) 28.23% 20.38% 14.3%
Moderate-Income (80%-120% AMI) 26.94% 13.38% 17.6%
Above Moderate-Income (>120% AMI) 23.98% 28.98% 39.4%
Universe: Population.

37 6 REFERENCES
Ananat, Elizabeth Oltmans. 2011. “The wrong side(s) of the tracks: The causal effects of racial segregation on urban poverty and inequality,” American Economic Journal: Applied Economics 3: 34-

66. Bayer, Patrick, Robert McMillan, and Kim S. Rueben. 2004. “What Drives Racial Segregation? New Evidence using Census Microdata,” Journal of Urban Economics 56(3): 514-535.

Burch, Traci. 2014. “The Old Jim Crow: Racial Residential Segregation and Imprisonment,” Law and Policy 36(3): 223-255.

Chetty, Raj and Nathanial Hendren. 2018. “The Impacts of Neighborhoods on Intergenerational Mobility I: Childhood Exposure Effects,” The Quarterly Journal of Economics 133(3):1107-1162 Cutler, David M., and Edward L. Glaeser. 1997. “Are ghettos good or bad?,” The Quarterly Journal of Economics 112(3): 827-72.

Lens, Michael and Paavo Monkkonen. 2016. “Do Strict Land Use Regulations Make Metropolitan Areas More Segregated by Income?,” Journal of the American Planning Association 82(1): 6–21.

Pendall, Rolf. 2000. “Local Land-Use Regulation and the Chain of Exclusion,” Journal of the American Planning Association 66(2): 125-142.

Rothstein, Richard. 2017. The Color of Law: A Forgotten History of how our Government Segregated America. New York: Liveright Publishing.

Sampson, Robert J. 2012. Great American city: Chicago and the enduring neighborhood effect.

Chicago: University of Chicago Press.

Sharkey, Patrick. 2013. Stuck in place: Urban neighborhoods and the end of progress toward racial equality. Chicago: University of Chicago Press.

Trounstine, Jessica. 2015. “Segregation and Inequality in Public Goods,” American Journal of Political Science 60(3): 709-725.

Trounstine, Jessica. 2018. Segregation by Design: Local Politics and Inequality in American Cities. New York: Cambridge University Press.

ROOT POLICY RESEARCH SECTION V, PAGE 1
SECTION V.

Disparate Access to Educational
Opportunities
This section examines the extent to which members of protected classes and those in poverty experience disparities in access to opportunity as measured by access to education. This section draws from data provided by the San Mateo Office of Education, the California Department of Education, and U.S. Census American Community Surveys (ACS). This section discusses the following topics:
 Changes in school enrollment during COVID-19 by race and ethnicity, and by groups with extenuating circumstances;1
 Achievement gaps by race and ethnicity and for groups with extenuating circumstances as measured by test scores, California State University or University of California admissions standards, and college-going rates;  Barriers to success measured by chronic absenteeism, dropout rates, and suspension rates.

After describing this section’s primary findings, we describe the county’s school districts before launching into data measuring achievement gaps and barriers to success.

Primary Findings
Student racial and ethnic diversity is modestly increasing. Student bodies in San Mateo County have become increasingly racially and ethnically diverse.  Hispanic students make up the largest ethnic group in the county’s schools, representing 38% of students in the 2020-2021 academic school year. This a slight increase from the 2010-2011 school year, where Hispanic students made up 37% of the population.
 There has been a large increase in Asian students, with 17% identifying as such in 2020-2021, an increase of 5 percentage points from 2010-2011.  Students identifying as White (26%) have decreased by 3 percentage points since 2010- 2011.

1 The term “extenuating circumstances” is used in this section to capture students whose socioeconomic situations and/or disability may make standard educational environments challenging.

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Free and reduced lunch-qualifying students and English language learners are concentrated in a handful of schools. Overall, 29% of public school students in San Mateo County qualify for reduced or free lunch.  The rate of reduced lunch qualification was highest in Ravenswood City Elementary School District, where 83% of students qualify for reduced lunch. Also in Ravenswood City Elementary, 30% of students are experiencing homelessness. This is a large outlier in the county, where overall just 2% are experiencing homelessness.  Countywide, 20% of public school students are English learners. Again, this rate is highest at Ravenswood City Elementary, where 53% of students are English learners.

La Honda-Pescadero Unified School District, Jefferson Union High School, and Redwood City Elementary also have high rates of English learners, representing more than a third of students.

Enrollment is dropping. Public school enrollment reduced substantially in some areas during the pandemic. Total enrollment decreased by 3% between 2019-2020 and 2020-2021 in San Mateo County, which was the largest decrease of the decade.  Portola Valley and La Honda-Pescadero school districts had the largest enrollment decreases during COVID-19, with a 11% and 10% decline in enrollments, respectively.  Decreased enrollment was especially common among Pacific Islander students.

Between 2019-2021, enrollment among Pacific Islander students decreased by 6% (from 1,581 students in 2019-20 to 1,484 students in 2020-21), substantially higher than the 3% countywide average.
 Enrollment among migrant students decreased drastically by 16% over the same period (from 332 students to 279 students).

Learning proficiency is improving yet disparities exist. Across all racial and ethnic groups, the rate at which students met or exceeded English and mathematics testing standards has increased since the 2014-2015 school year. Students with extenuating circumstances (i.e., disability, facing homelessness, learning English) tend to score lower on English and mathematics tests than the overall student body.  Proficiency gaps are especially pronounced among English learning students in Portola Valley Elementary, Woodside Elementary, Menlo Park City Elementary, and Brisbane Elementary, where students with extenuating circumstances met or exceeded mathematics test standards at a rate at least 50 percentage points below the overall test rate in each district.
 Students with disabilities in San Carlos Elementary and Las Lomitas Elementary school districts scored far below the overall student body: In these districts, students with disabilities met or exceeded mathematics test standards at 54 percentage points below the overall test rate.

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Many students meet admissions standards for CSU or UC schools.  Among the high school districts in San Mateo County, Sequoia Union had the highest rate of graduates who met such admission standards, at 69%. On the other end of the spectrum, Cabrillo Unified and South San Francisco Unified had the lowest rates at 41%.
 Jefferson Union High School District had the most drastic increase in the share of graduates meeting CSU or UC standards: just 21% of students met these standards in 2016-2017 compared to 48% of students in 2019-2020. La Honda-Pescadero Unified School District experienced a 10 percentage point increase in this success rate over the same period.

Most school districts in the county have a college-going rate at 70% or higher—yet there are wide gaps by race and ethnicity.
 In every district, White students have a higher college-going rate than Hispanic students, but the largest gaps are in South San Francisco United, where 91% of White students go to college compared to just 68% of Hispanic students—a 23 percentage point gap.

Students with extenuating circumstances are highly concentrated in a few schools and move schools often due to housing instability.  Students with extenuating circumstances may need additional resources—e.g., onsite health care, free meals, tutoring—to be successful in school. When these students are concentrated into a few schools, the schools bear an unequal responsibility for providing needed resources. K-12 school funding in California has long been inadequate, and, although policymakers have recently allocated additional resources to schools with high proportions of low income children under a “concentration grant” system, funding gaps remain.
 The highest concentration of high needs students is found in Ravenswood City Elementary, where 30% of all students are experiencing homelessness and 83% qualify for free and reduced lunch.
 Currently, students whose families have been evicted do not have protections allowing them to remain in their current school district. This can result in frequent changes in schools for low income children, raising their vulnerability to falling behind in school.

Absenteeism, dropout rates, and discipline rates are highest for students of color, students with disabilities, and students with other extenuating circumstances. While 10% of students were chronically absent during the 2018-2019 school year, chronic absenteeism rates were higher in districts with a large number of students experiencing economic and housing precarity.  For instance, Ravenswood Elementary, which has a 30% rate of homelessness among students, had one of the higher rates of chronic absenteeism at 16%.

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 Pacific Islander students (26%), Black/African American students (18%), and Hispanic students (15%) had notably higher rates of chronic absenteeism than the overall student population (10%).
 In most districts, chronic absenteeism is higher among students with disabilities. In fact, only Bayshore Elementary’s students with disabilities had a lower rate of chronic absenteeism than the overall student body.

Dropout rates vary across the county:
 Dropout rates were highest in Sequoia Union High School District (10%) and South San Francisco Unified (9%).
 In all school districts in the county, dropout rates are higher for boys than for girls.  Pacific Islander, Black/African American, and Hispanic students in the county often had higher dropout rates than those in other racial and ethnic groups  Students with disabilities, students experiencing homelessness, foster youth, and students learning English had higher dropout rates than the overall population.

Discipline rates also vary by area and race and ethnicity.  In many school districts across San Mateo County, Hispanic students are disciplined at disproportionately higher rates compared to their peers.  In most districts, Black/African American and Pacific Islander students are also overrepresented in terms of suspension rates, but these rates are slight compared to those of Hispanic students.
 Asian and Filipino students were underrepresented in terms of suspension rates.

White students were also underrepresented in discipline rates in most districts except for La Honda-Pescadero.

The demographics of faculty and staff are fairly similar to that of students.  There is a slightly larger share of White and Black/African American staff than students, meaning that Black/African American and White student groups are more likely to interact with same-race staff and faculty than other racial groups.  Asian students are less likely to interact with a same-race staff of faculty member: 17% of the student body is Asian compared to just 8% of staff and faculty.

Background
This section describes the school districts in San Mateo County, including their geographic boundaries and a brief history of the school districts’ formation. This section also includes details on how districts’ enrollments and student demographic have changed over time.

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San Mateo County School Districts. There are three unified school districts in San Mateo County which include both elementary and high schools. These are Cabrillo Unified School District, La Honda-Pescadero Unified School District, and South San Francisco Unified School District.

In addition to the unified school districts, there are three high school districts, which include: Jefferson Union High School District, San Mateo Union High School District, and Sequoia Union High School District. The elementary schools covering these high schools’ district boundaries areas are described below:
 In the Jefferson Union High School District geographic boundary, elementary school districts are the Bayshore Elementary School District, Brisbane School District, Jefferson Elementary School District, and Pacifica School District.  Within the San Mateo Union High School District geographic boundary, elementary school districts include San Mateo-Foster City School District, Hillsborough City School District, Burlingame School District, San Bruno Park School District, and Millbrae School District.
 Within the Sequoia Union High School District geographic boundary, the elementary schools include Belmont-Redwood Shores School District, San Carlos School District, Redwood City School District, Ravenswood City School District, Menlo Park City School District, Woodside Elementary School District, Las Lomitas Elementary School District, and Portola Valley School District.

Geographic boundaries of school districts. Figure V-1 illustrates the geographic boundaries of the unified school districts as well as the three high school districts. Municipal boundaries are overlayed on the map.

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Figure V-1.

Unified School Districts and High School Districts in San Mateo County

Source: San Mateo County Office of Education.

As illustrated in the map, Cabrillo Unified School District covers Half Moon Bay and some unincorporated areas of San Mateo County. South San Francisco Unified covers South San

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Francisco and a small portion of Daly City. La Honda-Pescadero Unified School District covers unincorporated areas of San Mateo County.

The other high school districts, Jefferson Union, San Mateo Union, and Sequoia Union, cover the remaining jurisdictions. Jefferson Union covers Brisbane, Colma, Daly City, and Pacifica. San Mateo Union covers Burlingame, Hillsborough, Millbrae, San Bruno, San Mateo City, and Foster City. Sequoia Union covers Atherton, Belmont, Redwood City, East Palo Alto, Menlo Park, San Carlos, Portola Valley, and Woodside.

The county’s elementary school districts cover the same areas as the three high school districts. Their geographic boundaries are illustrated in the map below.

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Figure V-2.

Elementary School Districts in San Mateo County

Source: San Mateo County Office of Education.

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Because the elementary school districts are much smaller, many jurisdictions have several elementary schools. The table blow shows each jurisdiction and their associated elementary school.

Figure V-3.

School Districts in San Mateo County’s Jurisdictions

Source: San Mateo County Office of Education.

A brief history of district formation. San Mateo County’s numerous school districts were formed over a century ago, when the county was more rural and scattered:
communities needed elementary schools close to home, and only a few students were attending high school. As young people began going to high school, individual districts often found they had too few students and resources to support their own high schools, so Jurisdiction
Atherton Sequoia Union Menlo Park City ; Las Lomitas Elementary; Redwood City
Belmont Sequoia Union Belmont-Redwood Shores
Brisbane Jefferson Union Brisbane; Bayshore Elementary
Burlingame San Mateo Union Burlingame
Colma Jefferson Union Jefferson Elementary
Daly City Jefferson Union; South San Francisco Unified Jefferson; Bayshore Elementary East Palo Alto Sequoia Union Ravenswood City
Foster City San Mateo Union San Mateo-Foster City
Half Moon Bay Cabrillo Unified (none, included in Cabrillo Unified) Hillsborough San Mateo Union Hillsborough City
Menlo Park Sequoia Union Menlo Park City; Las Lomitas Elementary; Ravenswood City
Millbrae San Mateo Union Millbrae
Pacifica Jefferson Union Pacifica
Portola Valley Sequoia Union Portola Valley
Redwood City Sequoia Union Redwood City
San Bruno San Mateo Union San Bruno Park
San Carlos Sequoia Union San Carlos; Redwood City
San Mateo San Mateo Union San Mateo-Foster City
South San Francisco South San Francisco Unified (none, included in South San Francisco Unified) Woodside Sequoia Union Woodside Elementary; Portola Valley; Las Lomitas; Redwood City
Unified or High School District Elementary School District(s) ROOT POLICY RESEARCH SECTION V, PAGE 10
separate high school districts, covering the territories of two or more elementary districts, were established to meet the communities’ needs.2
Once California’s population grew and San Mateo County became more urbanized, “a jigsaw puzzle of overlapping districts evolved haphazardly.” Since 1920, the state has been pushing elementary districts to unify with the high school districts that serve their communities, citing improved educational quality and equity of opportunity. However, there has been limited success and local voters in San Mateo County have consistently resisted unification.3
Early efforts at unification were more successful in the rural communities along the coast— for example, voters approved the new Cabrillo Unified district for the area around Half Moon Bay and the La Honda-Pescadero Unified district in a 1964 election. Unification was not supported by many suburban communities edging the Bay. The county’s school district committee proposed to split each of the three high school districts and feeder schools into two or three smaller unified districts, but the State Board of Education rejected variations of those plans three times. The Board argued that the county committee’s proposals would create districts with widely varying property tax bases and could contribute to racial segregation. The State Board instead devised a plan that would create a single unified district within each of the existing high school district boundaries. Voters turned down the state plans in all three districts in June 1966, and rejected a similar proposal again in 1972.

In 1973, the Mid-Peninsula Task Force for Integrated Education petitioned the county committees to unify the elementary districts of Menlo Park, Las Lomitas, Portola Valley, Ravenswood and a portion of Sequoia Union High School District across county lines with Palo Alto Unified. Their goal was racial integration, but the county committee did not support the effort.4
Efforts against unification have persisted, leaving the county with several elementary school districts which feed into a high school, rather than a unified district. As a result, some elementary school districts have faced waning budgets and administrative hurtles.

For instance, Brisbane and Bayshore elementary school districts, at the northern end of the county, serve a little more than 1,000 students and long have struggled with tight budgets.

To rectify their budgetary concerns, the districts now share both a superintendent and a chief business officer. They also participate in a special education collaborative with the Jefferson elementary and high school districts.

According to the county’s superintendent of schools Anne Campbell, other districts may find themselves pooling their resources in the future: local identification may be strong,

2 Watson, Aleta. “How Did We End Up With 54 School Districts in San Mateo and Santa Clara Counties?” Silicon Valley Community Foundation, 2012. https://www.siliconvalleycf.org/sites/default/files/report-edu.pdf 3 Ibid.
4 Ibid.

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she says, but financial reality is hard to ignore: “As we move forward in time, I think it’s going to be interesting to see what school districts are going to do, especially as budgets get more bleak.”5
Enrollment changes. Total public school enrollment in the county has decreased slightly, by just 1%, from the 2010-2011 academic year to 2020-2021. Figure V-4 illustrates enrollment changes by district.

Bayshore Elementary, Ravenswood City, and Portola Valley school districts experienced the largest enrollment decreases (by at least 30%) between 2010-11 and 2020-21. School districts with the largest increases in enrollments were Burlingame (22%) and Belmont- Redwood Shores (30%).

5 Ibid.

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Figure V-4.

Enrollment changes by district, 2010-11 to 2020-2021

Source: California Department of Education and Root Policy Research

However, it is important to note that many of these enrollment decreases were driven by the pandemic. In fact, total enrollment in these public schools decreased by 3% between School District
Unified School Districts
Cabrillo Unified 3,352 2,934 -12%
La Honda-Pescadero 341 275 -19%
South San Francisco 9,312 8,182 -12%
High & Elementary School Districts
Jefferson Union High School 4,960 4,705 -5%
Bayshore Elementary 543 361 -34%
Brisbane Elementary 545 474 -13%
Jefferson Elementary 6,998 6,653 -5%
Pacifica 3,164 3,006 -5%
San Mateo Union High School 8,406 9,760 16%
Burlingame Elementary 2,771 3,387 22%
Hillsborough City Elementary 1,512 1,268 -16%
Millbrae Elementary 2,222 2,238 1%
San Bruno Park Elementary 2,599 2,275 -12%
San Mateo-Foster City 10,904 10,969 1%
Sequoia Union High School 8,765 10,327 18%
Belmont-Redwood Shores 3,206 4,152 30%
Las Lomitas Elementary 1,336 1,116 -16%
Menlo Park City Elementary 2,629 2,781 6%
Portola Valley Elementary 711 491 -31%
Ravenswood City Elementary 4,285 2,993 -30%
Redwood City Elementary 9,119 8,086 -11%
San Carlos Elementary 3,212 3,265 2%
Woodside Elementary 453 369 -19%
Total Enrollment 91,345 90,067 -1%
2010-2011
Enrollment
2020-2021
Enrollment Percent Change
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2019-2020 and 2020-2021 in San Mateo County: the largest decrease of the decade. As shown in Figure V-5, enrollments actually increased steadily from 2010-2011 to 2017-2018, then began decreasing afterwards.

Figure V-5.

Public School Enrollment Changes, 2010-2011 to 2020-2021

Note: These data exclude enrollments in SBE Everest Public High School District, which in 2015 combined with the Sequoia Union High School District.

Source: California Department of Education and Root Policy Research

Portola Valley and La Honda-Pescadero school districts had the largest enrollment decreases during COVID-19, with a 11% and 10% decline in enrollments, respectively. The only school district with increasing enrollments between the 2019-2020 to 2020-2021 school years was Sequoia Union High School District, with a modest 1% increase in enrollments.

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Figure V-6.

Enrollment changes by district during COVID-19, 2019-20 to 2020-21

Source: California Department of Education and Root Policy Resear ch.

Declining enrollments in public schools have been common across the state and country during the COVID-19 pandemic, and enrollment declines in San Mateo County are on par School District
Unified School Districts
Cabrillo Unified 3,136 2,934 -6%
La Honda-Pescadero 306 275 -10%
South San Francisco 8,438 8,182 -3%
High & Elementary School Districts
Jefferson Union High School 4,811 4,705 -2%
Bayshore Elementary 381 361 -5%
Brisbane Elementary 476 474 0%
Jefferson Elementary 6,687 6,653 -1%
Pacifica 3,110 3,006 -3%
San Mateo Union High School 9,885 9,760 -1%
Burlingame Elementary 3,534 3,387 -4%
Hillsborough City Elementary 1,290 1,268 -2%
Millbrae Elementary 2,349 2,238 -5%
San Bruno Park Elementary 2,454 2,275 -7%
San Mateo-Foster City 11,576 10,969 -5%
Sequoia Union High School 10,238 10,327 1%
Belmont-Redwood Shores 4,314 4,152 -4%
Las Lomitas Elementary 1,208 1,116 -8%
Menlo Park City Elementary 2,922 2,781 -5%
Portola Valley Elementary 551 491 -11%
Ravenswood City Elementary 3,269 2,993 -8%
Redwood City Elementary 8,530 8,086 -5%
San Carlos Elementary 3,405 3,265 -4%
Woodside Elementary 376 369 -2%
Total Enrollment 93,246 90,067 -3%
2019-2020
Enrollment
2020-2021
Enrollment Percent Change
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with those across the state. According to a study conducted by the Public Policy Institute of California, public K–12 enrollment declined by 3% in California from the 2019-2020 school year to the 2020-2021 school year. 6
As funding is tied directly to the number of enrolled pupils, schools in San Mateo County could suffer fiscal consequences with continued declines. By law, districts are “held harmless” for declines for one year—that is, school budgets for 2020–2021 were unaffected, but continued enrollment declines could mean cuts in future years.7 Reductions in enrollments, and consequently funding, could also worsen economic inequality in the long-term by reducing students’ resources and access to opportunities.

Demographics: race & ethnicity. Over the last decade, San Mateo County’s school districts have diversified in terms of students’ race and ethnicity. Hispanic students make up the largest ethnic group in the county’s schools: 38% of students identified as Hispanic in the 2020-2021 academic school year. This is just a one percentage point increase from 2010-2011. Many other students are White (26%), though this has decreased by 3 percentage points since 2010-2011, The largest increase was in Asian students, with 17% identifying as such in 2020-2021, an increase of 5 percentage points from 2010-2011.

Other students identify as Filipino (8%), or bi- or multi-racial (8%). A small and decreasing percentage of students identify as Black/African American (1%) and Pacific Islander (2%).

6 Lafortune, Julien & Prunty, Emmanuel. “Digging into Enrollment Drops at California Public Schools.” Public Policy Institute of California. May 14, 2021. https://www.ppic.org/blog/digging-into-enrollment-drops-at-california-public- schools/
7 Ibid.

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Figure V-7.

Changes in Race and
Ethnicity, 2010-2011 to 2020-
2021
Note: These data exclude enrollments in SBE
Everest Public High School District, which
in 2015 combined with the Sequoia Union
High School District.

Source: California Department of Education and
Root Policy Research
:

Figure V-8 shows the racial and ethnic distribution of students enrolled in public schools by jurisdiction in 2020-2021.
 Portola Valley Elementary School District (66%) and Woodside Elementary School District (64%) had the highest share of White students, making them among the least racially and ethnically diverse districts in the county.  Ravenswood City Elementary School District and Redwood City Elementary School District had the highest share of Hispanic students, at 84% and 70%, respectively.  Ravenswood City also had the highest proportion of Pacific Islander students (7%) and Black/African American students (5%) compared to other districts.  Millbrae Elementary (46%), Hillsborough Elementary (32%), and Belmont-Redwood Shores Elementary (32%) had the highest share of Asian students.  Jefferson Elementary School District and Jefferson Union High School District had the highest portion of Filipino students, at 25% and 29% respectively.

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Figure V-8.

Student body by Race and Ethnicity, 2020-2021

Note: In almost all school districts, less than 1% of students were Native American , so they are not included in this table.

Source: California Department of Education and Root Policy Research Enrollment changes due to COVID-19 varied by race and ethnicity. For instance, between 2019-2021, enrollment among Pacific Islander students decreased by 6% (from 1,581 students in 2019-20 to 1,484 students in 2020-21). This is substantially higher than the 3% countywide average. Enrollments among Filipino and Hispanic students decreased by 4% while enrollment among Black/African American students decreased by 2%. On the other School District
Unified School Districts
Cabrillo Unified 1% 0% 1% 52% 0% 40% 5%
La Honda-Pescadero 0% 0% 1% 63% 0% 35% 1%
South San Francisco 14% 1% 23% 48% 2% 6% 6%
High & Elementary School Districts
Jefferson Union High School 15% 1% 29% 31% 1% 14% 7%
Bayshore Elementary 19% 3% 21% 41% 4% 3% 8%
Brisbane Elementary 20% 1% 12% 28% 0% 24% 11%
Jefferson Elementary 19% 2% 25% 36% 1% 11% 5%
Pacifica 8% 1% 9% 26% 0% 39% 16%
San Mateo Union High School 23% 1% 5% 32% 2% 28% 10%
Burlingame Elementary 27% 0% 3% 16% 0% 41% 9%
Hillsborough Elementary 32% 0% 2% 5% 0% 48% 12%
Millbrae Elementary 46% 1% 6% 20% 2% 16% 8%
San Bruno Park Elementary 16% 1% 10% 41% 5% 15% 1%
San Mateo-Foster City 26% 1% 3% 37% 2% 21% 9%
Sequoia Union High School 9% 2% 1% 45% 2% 35% 5%
Belmont-Redwood Shores 32% 1% 3% 12% 1% 34% 14%
Las Lomitas Elementary 18% 1% 1% 13% 0% 53% 14%
Menlo Park City Elementary 13% 1% 1% 17% 1% 55% 11%
Portola Valley Elementary 6% 0% 0% 14% 0% 66% 13%
Ravenswood City Elementary 0% 5% 0% 84% 7% 1% 2%
Redwood City Elementary 4% 1% 1% 70% 1% 19% 4%
San Carlos Elementary 18% 1% 1% 14% 0% 49% 13%
Woodside Elementary 4% 2% 0% 16% 1% 64% 11%
Total 17% 1% 8% 38% 2% 26% 8%
White Asian
Two or
more racesHispanicFilipinoBlack
Pacific
Islander
ROOT POLICY RESEARCH SECTION V, PAGE 18
end of the spectrum, there was a 3% increase in enrollment among White students (from 22,308 students to 23,055 students) between 2019-20 and 2020-21. Similarly, there was a 1% increase in enrollment among Asian students and a 4% increase among students of two or more races.

Figure V-9.

Enrollment Changes by Race and Ethnicity, San Mateo County, 2019-20 to 2020-21

Source: California Department of Education and Root Policy Research While many of their families may have simply moved out of San Mateo County during the pandemic, it is possible that Black/African American, Filipino, Hispanic, and Pacific Islander students are otherwise slipping through the cracks of the education system during this period.

Demographics: students with extenuating circumstances. Several students in the county’s public schools are facing additional hurtles to educational ease.

Many are English learners, qualify for reduced lunch, are foster children, are experiencing homelessness, have a disability, or are migrants. Students in these groups often have hindrances to excelling in school because of detrimental circumstances beyond their control. These include financial and social hardships as well as problems within students' families.

Qualification for free and reduced lunch is often used as a proxy for extenuating circumstances. Qualifications are determined based on household size and income. For instance, in the 2020-2021 academic year, students from a household of three making less

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than $40,182 annually qualified for reduced price meals, and those making less than $28,236 in a household of three qualified for free meals.8 Free and reduced lunch disparities. Overall, 29% of public school students in San Mateo County qualify for reduced or free lunch. This rate was substantially lower in districts like Hillsborough Elementary, San Carlos Elementary, Portola Valley Elementary, Las Lomitas Elementary, Belmont-Redwood Shores, and Menlo Park City Elementary, where each had less than 10% of students qualify for free or reduced lunch.

The rate of reduced lunch qualification was far higher in Ravenswood City Elementary School District, where 83% of students qualify for reduced lunch.

Disparities in homelessness. In Ravenswood City Elementary, 30% of students are experiencing homelessness. This is an outlier in the county, where overall just 2% are experiencing homelessness. The school district has received media attention due to its astronomically high rate of students experiencing homelessness. Some have noted that rates of homelessness have increased due to escalating costs of living in an area surrounded by affluence.9 Others have highlighted that ”Having a roof over your head, having a safe place to sleep and study, is fundamental to absolutely everything," and have noted that students who experience homelessness have higher dropout rates and are more likely to experience homelessness as adults.10
School moves related to evictions. Currently, students whose families have been evicted do not have protections allowing them to remain in their current school district.

This means that precarious housing also means precarious schooling for many of the county’s students. Frequent moves by students are closely related to lower educational proficiency.

In the City of San Francisco, a 2010 ordinance protects some students from being evicted during the school year; however, it only relates to owner/relative move-in evictions.11 Children in families who are evicted for other reasons may need to move schools or districts when their housing is lost.

English language learners. Countywide, 20% of public school students are English learners. Again, this rate is highest at Ravenswood City Elementary, where 53% of students are English learners. La Honda-Pescadero Unified School District, Jefferson Union High

8 “Income Eligibility Scales for School Year 2020-2021.” California Department of Education. 9 Bartley, Kaitlyn. “Homelessness: The shadow that hangs over students in this Bay Area school district.” The Mercury News. December 2018.
10 Jones, Carolyn. “California schools see big jump in homeless students.” Palo Alto Online. October 2020. 11 https://sfrb.org/new-amendment-prohibiting-owner-move-evictions-minor-children-during-school-year ROOT POLICY RESEARCH SECTION V, PAGE 20
School, and Redwood City Elementary also have high rates of English learners, representing more than a third of students.

Less than one percent of students in San Mateo County public school districts are foster youth or migrants. Cabrillo Unified School District had the highest rate of migrant students at 3%. La Honda-Pescadero had the highest rate of foster children at 2%.

School districts without large low income populations also tend to serve very few English language learners. For instance, in Hillsborough Elementary where 0% of students qualify for reduced lunch, only 1% of students are English language learners.

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Figure V-10.

Students with Extenuating Circumstances, 2020-2021

Source: California Department of Education and Root Policy Research The overall share of students in these groups has not changed drastically over time. As shown in Figure V-11, there have been slight decreases in the share of students who are English learners and the share of students who qualify for reduced lunch from 2016-2017 School District
Unified School Districts
Cabrillo Unified 20% 37% 0% 2% 3%
La Honda-Pescadero 38% 38% 2% 1% 1%
South San Francisco 21% 34% 0% 1% 1%
High & Elementary School Districts
Jefferson Union High School 36% 44% 0% 0% 0%
Bayshore Elementary 30% 57% 0% 0% 0%
Brisbane Elementary 16% 19% 0% 0% 0%
Jefferson Elementary 14% 27% 0% 1% 0%
Pacifica 9% 18% 0% 1% 0%
San Mateo Union High School 10% 21% 0% 0% 0%
Burlingame Elementary 13% 11% 0% 0% 0%
Hillsborough Elementary 1% 0% 0% 0% 0%
Millbrae Elementary 19% 25% 0% 0% 0%
San Bruno Park Elementary 29% 18% 0% 0% 0%
San Mateo-Foster City 26% 28% 0% 2% 0%
Sequoia Union High School 15% 30% 0% 0% 0%
Belmont-Redwood Shores 10% 7% 0% 0% 0%
Las Lomitas Elementary 7% 6% 0% 0% 0%
Menlo Park City Elementary 6% 7% 0% 0% 0%
Portola Valley Elementary 4% 5% 0% 0% 0%
Ravenswood City Elementary 53% 83% 0% 30% 0%
Redwood City Elementary 38% 56% 0% 2% 1%
San Carlos Elementary 5% 6% 0% 0% 0%
Woodside Elementary 8% 10% 0% 0% 0%
Total 20% 29% <1% 2% <1%
Migrant
Reduced
Lunch
English
Learners
Foster
Children Homeless
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to 2020-2021. Around 2% of students in the county are homeless and this has not changed between 2016-2017 and 2020-2021. Foster youth and migrant students are not shown in the figure, as both have hovered at less than 1% from year to year.

Figure V-11.

Changes in rates of English
Leaners, Reduced Lunch,
and Homelessness, 2016-
2017 to 2020-2021
Note: These data exclude enrollments in SBE
Everest Public High School District, which
in 2015 combined with the Sequoia Union
High School District.

Source: California Department of Education and
Root Policy Research
:

During COVID-19, enrollments decreased by 3% between 2019-2020 and 2020-2021 school years, as families withdrew or did not reenroll their children from public schools.

Enrollment among migrant students decreased much more drastically, by 16% (from 332 students to 279 students). Similarly, enrollment among students who qualify for reduced lunch declined at a higher rate (10%) than the overall student population. Foster children and English learners also experienced enrollment decreases at a rate higher than the total population, with 7% and 10% decreases in enrollment, respectively.

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Figure V-12.

Enrollment Changes by Extenuating Circumstance, San Mateo County, 2019-2020 to 2020-2021

Source: California Department of Education and Root Policy Resear ch

Achievement Gaps
This section details achievement gaps within school districts. Gaps are measured by test scores, meeting California State University or University of California admissions standards, and college-going rates.

Test scores. Figure V-13 indicates the percent of students who met or exceeded English and mathematics testing standards set by the California State Assessment of Student Performance and Progress. Overall, 62% of students in the county met or exceeded English testing standards and 52% met or exceeded mathematics testing standards.

Of all the districts with high schools, San Mateo Union High School District had the highest student pass rates: 70% of their students met or exceeded standards in English testing and 50% met or exceeded standards in mathematics testing.

Among elementary school districts, Portola Valley Elementary School District and Woodside Elementary School District had the highest rates of success in English, with 87% and 88% of students meeting or exceeding English testing standards, respectively. Woodside Elementary School District and Hillsborough Elementary School District had the highest rates of success in mathematics, with 84% and 85% meeting math testing standards, respectively.

In every school district, girls scored higher on English tests than boys. Overall, girls met or exceeded English testing at a rate of 67% while boys met or exceeded English testing at a rate of 57%. The largest gender gap was in Brisbane Elementary School District, where 72%

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of girls met or exceeded English testing standards and just 56% of boys did: a gap of 16 percentage points.

Gender gaps in mathematics were less pronounced, but largest gender gaps were in Cabrillo Unified School District and in La Honda Pescadero Unified School District. In Cabrillo Unified, girls passed mathematics at a rate 7% higher than boys, while in La Honda-Pescadero, boys passed at a rate 6% higher than girls.

Figure V-14.

Students who Met or Exceeded Testing Standards, by Gender and District, 2018-2019

Source: California Department of Education, California Assessment of Student Performance and Progress, and Root Policy Research The gender gap in test scores has started to close in recent years, as indicated in Figure V-

15. In 2014-2015 there was a 11 percentage point gap in girls’ and boys’ English testing pass District
Unified School Districts
Cabrillo Unified 48% 41% 55% 34% 31% 38%
La Honda-Pescadero 43% 36% 49% 31% 34% 28%
South San Francisco 52% 45% 60% 44% 42% 45%
High & Elementary School Districts
Jefferson Union High School 57% 52% 63% 37% 38% 35%
Bayshore Elementary 27% 24% 31% 27% 27% 28%
Brisbane Elementary 64% 56% 72% 54% 56% 53%
Jefferson Elementary 48% 43% 54% 37% 39% 35%
Pacifica 60% 55% 65% 57% 57% 57%
San Mateo Union High School 70% 66% 76% 50% 50% 50%
Burlingame Elementary 80% 75% 84% 78% 78% 78%
Hillsborough Elementary 85% 81% 89% 85% 86% 84%
Millbrae Elementary 63% 57% 70% 58% 58% 58%
San Bruno Park Elementary 50% 47% 53% 41% 43% 38%
San Mateo-Foster City 62% 58% 67% 56% 56% 56%
Sequoia Union High School 68% 64% 72% 50% 50% 50%
Belmont-Redwood Shores 82% 78% 86% 79% 78% 80%
Las Lomitas Elementary 86% 84% 88% 82% 84% 80%
Menlo Park City Elementary 84% 81% 87% 83% 82% 83%
Portola Valley Elementary 87% 83% 91% 83% 84% 82%
Ravenswood City Elementary 22% 20% 23% 15% 16% 13%
Redwood City Elementary 54% 49% 59% 46% 46% 46%
San Carlos Elementary 80% 77% 83% 75% 76% 74%
Woodside Elementary 88% 85% 91% 84% 85% 83%
Total 62% 57% 67% 52% 52% 52%
English Language Arts/Literacy Mathematics
Total Boys Girls Total Boys Girls
ROOT POLICY RESEARCH SECTION V, PAGE 25
rates, and by 2018-2019 this was just a 10 percentage point gap. The figure also indicates that there have been steady gains in the share of students meeting or exceeding testing standards in the county.

Figure V-15.

Students who Met or Exceeded Testing Standards, by Gender, 2014-2015 to 2018-2019

Source: California Department of Education, California Assessment of Student Performance and Progress, and Root Policy Research Very large gaps in test scores by race and ethnicity exist among students in some areas.

Figure V-16 illustrates the rate at which students of various racial and ethnic groups met or exceeded English testing standards.

For the past five years in San Mateo County, Asian, White, and Filipino students have met or exceeded English testing standards at rates higher than the overall student population.

Hispanic, Black/African American, and Pacific Islander students, on the other hand, have been underserved in this realm and have consistently scored lower than the overall student body.

However, across all groups, the rate at which students met or exceed English testing standards has increased since the 2014-2015 school year. Hispanic students have made the largest percentage point gain: 34% met standards in 2014-2015 and 40% met standards in 2019-19, an increase of six percentage points.

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Figure V-16.

Students who Met or Exceeded English Testing Standards, by Race and Ethnicity, 2014-2015 to 2018-2019

Source: California Department of Education, California Assessment of Student Performance and Progress, and Root Policy Research A similar narrative holds in Math testing standards, where scores have improved among each racial and ethnic group from 2014-2015 to 2018-2019. Again, White and Asian students meet or exceed math testing standards at rates higher than the overall population while Hispanic, Pacific Islander, and Black/African American students scored lower.

White and Hispanic students have seen the biggest increases in rates of mathematics success: both have experienced a five percentage point increase in the percent of students who met or exceeded math testing standards.

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Figure V-17.

Students who Met or Exceeded mathematics testing standards, by Race and Ethnicity, 2014-2015 to 2018-2019

Source: California Department of Education, California Assessment of Student Performance and Progress, and Root Policy Research Figure V-18 illustrates the rates at which students of various racial and ethnic groups met or exceeded mathematics testing standards by district.

There were several districts in which the gaps between the overall test pass rates and a specific racial groups’ pass rates were especially wide. For instance, in San Carlos Elementary School District, 75% of the total student body met or exceeded math testing standards, but only 11% of Black/African American students met or exceeded math testing standards— a gap of 64 percentage points.

Other school districts with wide gaps between Black/African American and overall math testing success were Las Lomitas Elementary (46 percentage point gap), Menlo Park City Elementary (43 percentage point gap), and Belmont-Redwood Shores (42 percentage point gap).

Some school districts also had similar gaps in Pacific Islander students’ math passing rates and overall passing rates. For instance, in Menlo Park City Elementary School District, 83% of the student body met or exceeded mathematics testing standards but just 35% of Pacific Islander students passed or exceeded mathematics testing standards—a gap of 48

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percentage points. Millbrae Elementary School District also had a 47 percentage point gap between Pacific Islander students’ and total students’ math test rates.

Figure V-18.

Students who Met or Exceeded Mathematics Testing Standards, by Race/Ethnicity and District, 2018-2019

Source: California Department of Education, California Assessment of Student Performance and Progress, and Root Policy Research Although racial gaps in English testing were less pronounced, San Carlos Elementary School District also had a wide gap between the total student body and Black/African American School District
Unified School Districts
Cabrillo Unified 34% 65% (no data) 38% 16% (no data) 54% La Honda-Pescadero 31% (no data) (no data) (no data) 20% (no data) 46% South San Francisco 44% 75% 19% 60% 29% 33% 46%
High & Elementary School Districts
Jefferson Union High School 37% 75% (no data) 36% 17% (no data) 42% Bayshore Elementary 27% 44% (no data) 38% 17% 14% (no data) Brisbane Elementary 54% 67% (no data) 65% 38% (no data) 60% Jefferson Elementary 37% 61% 15% 42% 23% 20% 30%
Pacifica 57% 74% 38% 48% 38% (no data) 66%
San Mateo Union High School 50% 84% (no data) 46% 22% 20% 63% Burlingame Elementary 78% 92% 53% 66% 50% (no data) 81% Hillsborough Elementary 85% 92% (no data) (no data) 76% (no data) 82% Millbrae Elementary 58% 75% 31% 63% 27% 11% 51%
San Bruno Park Elementary 41% 69% 23% 64% 25% 27% 50%
San Mateo-Foster City 56% 87% 30% 61% 23% 27% 69%
Sequoia Union High School 50% 81% 18% 53% 22% 11% 76%
Belmont-Redwood Shores 79% 92% 37% 77% 52% 43% 79%
Las Lomitas Elementary 82% 93% 36% (no data) 44% (no data) 87% Menlo Park City Elementary 83% 94% 40% (no data) 55% 35% 88% Portola Valley Elementary 83% 89% (no data) (no data) 56% (no data) 89% Ravenswood City Elementary 15% (no data) 9% (no data) 15% 11% (no data) Redwood City Elementary 46% 92% 22% 76% 34% 44% 75%
San Carlos Elementary 75% 91% 11% 85% 51% (no data) 78% Woodside Elementary 84% 92% (no data) (no data) 52% (no data) 89% Total 52% 82% 18% 50% 27% 21% 71%
Overall WhiteAsian Black Filipino Hispanic
Pacific
Islander
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students. Namely, 80% of the student body met or exceeded English testing standards, but only 19% of Black/African American students met or exceeded testing standards—a 61 percentage point gap. Las Lomitas Elementary had a 41 percentage point gap between overall English testing success and Black/African American English testing success.

Other districts had large gaps between the total student body’s English test scores and Pacific Islander students’ test scores. Namely, in Menlo Park City Elementary School District 84% of students met or exceeded English testing standards, but only 40% of Pacific Islander students—a 44 percentage point gap.

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Figure V-19.

Students who Met or Exceeded English Testing Standards, by Race/Ethnicity and District, 2018-2019

Source: California Department of Education, California Assessment of Student Performance and Progress, and Root Policy Research Students with extenuating circumstances across all districts met or exceeded testing standards at lower rates. However, some districts had especially wide disparities between overall test scores and test scores of students with extenuating circumstances.

School District
Unified School Districts
Cabrillo Unified 48% 78% (no data) 54% 28% (no data) 71% La Honda-Pescadero 43% (no data) (no data) (no data) 27% (no data) 61% South San Francisco 52% 76% 36% 66% 38% 44% 56%
High & Elementary School Districts
Jefferson Union High School 57% 81% (no data) 60% 43% (no data) 59% Bayshore Elementary 27% 49% (no data) 33% 20% 14% (no data) Brisbane Elementary 64% 63% (no data) 75% 51% (no data) 79% Jefferson Elementary 48% 62% 28% 59% 34% 33% 43%
Pacifica 60% 65% 32% 52% 45% (no data) 68%
San Mateo Union High School 70% 88% 55% 79% 50% 34% 81% Burlingame Elementary 80% 88% 61% 73% 55% (no data) 83% Hillsborough Elementary 85% 89% (no data) (no data) 77% (no data) 83% Millbrae Elementary 63% 74% 46% 68% 42% 23% 61%
San Bruno Park Elementary 50% 72% 39% 76% 36% 31% 56%
San Mateo-Foster City 62% 85% 41% 68% 34% 37% 77%
Sequoia Union High School 68% 87% 44% 92% 47% 31% 88%
Belmont-Redwood Shores 82% 91% 44% 81% 64% 61% 83%
Las Lomitas Elementary 86% 91% 45% (no data) 65% (no data) 89% Menlo Park City Elementary 84% 92% 60% (no data) 62% 40% 88% Portola Valley Elementary 87% 92% (no data) (no data) 58% (no data) 93% Ravenswood City Elementary 22% (no data) 24% (no data) 21% 18% (no data) Redwood City Elementary 54% 91% 35% 73% 43% 47% 83%
San Carlos Elementary 80% 90% 19% 76% 60% (no data) 83% Woodside Elementary 88% 92% (no data) (no data) 58% (no data) 92% Total 62% 82% 34% 64% 40% 31% 79%
Overall WhiteAsian Black Filipino Hispanic
Pacific
Islander
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For example, English learning students in Portola Valley Elementary, Woodside Elementary, Menlo Park City Elementary, and Brisbane Elementary each met or exceeded mathematics test standards at a rate at least 50 percentage points below the overall test rate in each district. English learning students in Las Lomitas Elementary (54%) had the highest mathematics pass rates, followed by those in Belmont-Redwood Shores (42%) and Burlingame Elementary (40%).

Students with disabilities scored especially high on mathematics tests in Hillsborough Elementary, where 48% met or exceeded standards. Others in Belmont-Redwood Shores (43%) and Woodside Elementary (41%) had high pass rates as well. Students with disabilities in San Carlos Elementary and Las Lomitas Elementary school districts scored far below the overall student body: in these districts, students with disabilities met or exceeded mathematics test standards at 54 percentage points below the overall test rate.

In Jefferson Elementary and Ravenswood Elementary students experiencing homelessness passed math tests at a rate similar to their housed peers. In other districts, however, students experiencing homelessness often scored substantially lower. School districts with the widest math testing gaps between the overall student body and students experiencing homelessness were San Mateo-Foster City and Millbrae Elementary, with a 41 percentage point gap and 42 percentage point gap, respectively.

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Figure V-20.

Students who Met or Exceeded Math Testing Standards, by Special Case and District, 2018-2019

Source: California Department of Education, California Assessment of Student Performance and Progress, and Root Policy Research

School District
Unified School Districts
Cabrillo Unified 34% 4% 5% 4% 9%
La Honda-Pescadero 31% 4% (no data) (no data) 2%
South San Francisco 44% 20% 25% 4% 18%
High & Elementary School Districts
Jefferson Union High School 37% 5% (no data) (no data) 6% Bayshore Elementary 27% 11% (no data) (no data) 9%
Brisbane Elementary 54% 4% (no data) (no data) 12%
Jefferson Elementary 37% 15% 36% (no data) 11%
Pacifica 57% 22% (no data) (no data) 17%
San Mateo Union High School 50% 10% (no data) (no data) 13% Burlingame Elementary 78% 40% (no data) (no data) 29%
Hillsborough Elementary 85% (no data) (no data) (no data) 48% Millbrae Elementary 58% 26% 16% (no data) 25%
San Bruno Park Elementary 41% 12% (no data) (no data) 9% San Mateo-Foster City 56% 11% 15% (no data) 14%
Sequoia Union High School 50% 3% 33% (no data) 9%
Belmont-Redwood Shores 79% 42% (no data) (no data) 43%
Las Lomitas Elementary 82% 54% (no data) (no data) 28%
Menlo Park City Elementary 83% 31% (no data) (no data) 38% Portola Valley Elementary 83% 14% (no data) (no data) 39% Ravenswood City Elementary 15% 5% 11% (no data) 2%
Redwood City Elementary 46% 14% (no data) 29% 14%
San Carlos Elementary 75% 24% (no data) (no data) 21%
Woodside Elementary 84% 27% (no data) (no data) 41%
English
Learners
Experiencing
homelessness Migrant
With
DisabilitiesOverall
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Students with extenuating circumstances also consistently scored lower in English testing than the overall student body.

For instance, English learning students in San Mateo Union High School District, Hillsborough Elementary School District, Sequoia Union High School District, Menlo Park City Elementary School District, and Portola Valley Elementary School District met or exceeded English test standards at a rate at least 60 percentage points below the overall test rate in each district. Hillsborough Elementary had the largest gap at 85 percentage points. Las Lomitas Elementary had the highest success rate among English learners, where 50% met or exceeded English testing standards.

However, students with disabilities in Las Lomitas Elementary and San Carlos Elementary school districts met or exceeded English test standards at rate 55 and 51 percentage points below the overall test rate, respectively. These were the largest gaps in the county.

Students with disabilities at Woodside Elementary did the best on English testing, where 56% passed or exceeded standards.

Among students experiencing homelessness, those at Sequoia Union High School were most likely to meet English testing standards, with 42% meeting or exceeding standards.

The school district with the widest gap between overall English test scores and scores among students experiencing homelessness was Cabrillo Unified with a 34 percentage point gap.

Just three districts reported English testing scores among migrant students. Redwood City Elementary had the highest pass rate at 34% and Cabrillo Unified had the lowest at 16%.

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Figure V-21.

Students who Met or Exceeded English Testing Standards, by Special Case and District, 2018-2019

Source: California Department of Education, California Assessment of Student Performance and Progress, and Root Policy Research

School District
Unified School Districts
Cabrillo Unified 48% 9% 14% 16% 12%
La Honda-Pescadero 43% 9% (no data) (no data) 9%
South San Francisco 52% 21% 35% 20% 18%
High & Elementary School Districts
Jefferson Union High School 57% 3% (no data) (no data) 19% Bayshore Elementary 27% 3% (no data) (no data) 4%
Brisbane Elementary 64% 21% (no data) (no data) 16%
Jefferson Elementary 48% 16% 30% (no data) 15%
Pacifica 60% 12% (no data) (no data) 15%
San Mateo Union High School 70% 11% (no data) (no data) 27% Burlingame Elementary 80% 33% (no data) (no data) 33%
Hillsborough Elementary 85% (no data) (no data) (no data) 47% Millbrae Elementary 63% 19% 34% (no data) 23%
San Bruno Park Elementary 50% 14% (no data) (no data) 12% San Mateo-Foster City 62% 9% 33% (no data) 15%
Sequoia Union High School 68% 8% 42% (no data) 27%
Belmont-Redwood Shores 82% 31% (no data) (no data) 45%
Las Lomitas Elementary 86% 51% (no data) (no data) 31%
Menlo Park City Elementary 84% 21% (no data) (no data) 42% Portola Valley Elementary 87% 17% (no data) (no data) 37% Ravenswood City Elementary 22% 6% 16% (no data) 5%
Redwood City Elementary 54% 13% (no data) 34% 16%
San Carlos Elementary 80% 29% (no data) (no data) 28%
Woodside Elementary 88% 18% (no data) (no data) 56%
English
Learners
Experiencing
homelessness Migrant
With
DisabilitiesOverall
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Students who met university requirements. Many high schoolers in the county met admission standards for a University of California (UC) or California State University (CSU) school. Figure V-22 illustrates the percentage of cohort graduates who met admission requirements for a CSU or UC school according to California Department of Education data.

Of the high school districts in San Mateo County, Sequoia Union had the highest rate of graduates who met such admission standards, at 69%. On the other end of the spectrum, Cabrillo Unified and South San Francisco Unified had the lowest rates at 41%.

Figure V-22.

Students Meeting
California University
Admission
Standards, 2019-
2020

Source:

California Department of Education
and Root Policy Research.

Cabrillo Unified and South San Francisco Unified have experienced a decrease in the share of graduates meeting CSU or UC admission standards in recent years. For instance, in 2016-2017, 57% of South San Francisco Unified graduates met these standards, but this decreased by 16 percentage points by 2019-2020. Cabrillo Unified experienced a less drastic decrease over the same period, but the rate still shrunk by two percentage points.

Jefferson Union High School District had the most drastic increase in the share of graduates meeting CSU or UC standards: just 21% of students met these standards in 2016-2017 compared to 48% of students in 2019-2020. La Honda-Pescadero Unified School District experienced a 10 percentage point increase in this success rate over the same period.

Sequoia Union and San Mateo Union experienced more modest increases, but remain the districts with the highest rates of students meeting CSU and UC standards.

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Figure V-23.

Students Meeting
University
Admission
Standards, 2016-
2017 and 2019-2020

Source:

California Department of Education
and Root Policy Research.

Rates at which students met CSU or UC admissions standards varied substantially by race and ethnicity in 2019-2020. In all high school districts in San Mateo County, White and Asian students meet CSU and UC admissions standards at higher rates than the overall student population.

The largest gap is in South San Francisco Unified, where just 41% of students meet CSU or UC admissions standards, but 73% of Asian students meet those standards—a 32 percentage point gap.

On the other end of the spectrum, Black/African American students typically met CSU or UC admissions standards at lower-than-average rates. The largest gap was in San Mateo Union, where just 29% of Black/African American students met CSU or UC standards compared to 68% of students in the district overall.

Filipino students typically met admissions standards at rates similar to the overall student body. For instance, in Jefferson Union, San Mateo Union, and South San Francisco Unified, Filipino students are slightly more likely to have meet CSU and UC standards than the overall student population. In Sequoia Union, they are slightly less likely to have met admission standards than the overall student population.

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In La Honda-Pescadero, Hispanic students are slightly more likely to have met CSU or UC standards than the overall student body. However, in all other school districts, Hispanic students are less likely to have met CSU and UC standards than the overall student body.

The largest disparity is in San Mateo Union, where just 46% of Hispanic students meet the university admissions standards compared to 68% of students overall.

Finally, Pacific Islander students in Jefferson Union were slightly more likely to have met California university admissions standards compared to the overall student body, but in Sequoia Union and San Mateo Union they were substantially less likely.

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Figure V-24.

Students Meeting University Admission Standards, by Race and Ethnicity, 2019-2020

Source: California Department of Education and Root Policy Research As expected, students with extenuating circumstances were less likely to meet CSU or UC admissions standards than students in the county overall. In all school districts where data are available, students with disabilities, students experiencing homelessness, English learners, foster youth, and migrant students met CSU or UC admission standards at lower rates than the overall student population.

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English learners in Sequoia Union and San Mateo Regional met CSU or UC admission standards at higher rates than their peers in other school districts. However, compared to the overall student body within their own school districts, they had a larger gap than other districts. Namely, in Sequoia Union, 69% of students met admissions standards compared to just 32% of students learning English— a 37 percentage point gap.

Similarly, students with disabilities in Sequoia Union had the highest rate of meeting admissions standards (31%) compared to peers with disabilities in other districts, but also had the largest gap (38 percentage points) compared to the district’s overall student body.

Migrant students met admission standards at the lowest rate in South San Francisco Unified (27%) and at the highest rate in Sequoia Union (45%). However, in Cabrillo Unified, their rates were only eight percentage points lower than that of the overall student body, the smallest gap in the county.

Approximately 36% of students experiencing homelessness in Sequoia Union met CSU or UC admission standards, which was higher than rates in San Mateo Union (21%) and Jefferson Union (21%).

Just San Mateo Union and Sequoia Union had enough foster youth to report their rate of meeting CSU or UC admission standards. In Sequoia Union, 29% met admissions standards and 22% in San Mateo Union met admissions standards.

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Figure V-25.

Students Meeting
University
Admission
Standards, 2019-
2020

Source:

California Department of Education
and Root Policy Research.

Notes; La-Honda Pescadero Unified
is excluded from these data as they
do not report admission standards
data for these special groups, likely
due to small sample size.

College-going rates. The college-going rate is defined as the percentage of public high school students who completed high school in a given year and subsequently enrolled in any public or private postsecondary institution (in-state or out-of-state) in the United States within 12 or 16 months of completing high school.

Most school districts in the county have a college-going rate at 70% or higher. San Mateo Union had the highest college-going rate at 77%. La Honda-Pescadero School District is the notable exception, with just 32% of graduates attending college within 12 or 16 months.

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Figure V-26.

College-Going
Rates, 2017-2018

Source:

California Department of Education
and Root Policy Research.

As shown in Figure V-27, La Honda-Pescadero School District previously had the highest college-going rate of all the county’s high school districts, with an 80% college-going rate in 2014-2015 and a 93% college-going rate in 2015-2016. The district experienced a rapid decline in college-going rates, starting in 2016-2017. However, La Honda-Pescadero has especially small sample sizes. For instance, the district had just 26 twelfth-graders in the 2017-2018 school year, meaning that just a couple students going to college (or not) drastically alters the college-going rate in La Honda-Pescadero. All other high school districts in the county have maintained relatively consistent college-going rates.

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Figure V-27.

College-Going
Rates, 2014-2015 to
2017-2018

Source:

California Department of Education
and Root Policy Research.

Within each of the high school districts, college-going rates vary by race and ethnicity.  In every district, White students have a higher college-going rate than Hispanic students, but the largest gaps are in South San Francisco United, where 91% of White students go to college compared to just 68% of Hispanic students, a 23 percentage point gap. Jefferson Union has the smallest gap between the two groups: 77% of White students go to college compared to 71% of Hispanic students.  Among Black/African American students, those at San Mateo Union have the highest college-going rate at 82%. Those at Jefferson Union have the lowest at just 53%, which is 24 percentage points lower than that of White students and 34 percentage points lower than that of Asian students.
 Overall, Asian students have among the highest college-going-rates in the county. The rate is especially high in South San Francisco Unified, where 92% go to college. The rate is lowest in Sequoia Union High School District, where 84% go to college.

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 Filipino students also have generally high rates of college-going. The highest college- going rate among Filipino students is in Sequoia Union (86%) and the lowest is in South San Francisco Unified (73%).
 College-going rates for Pacific Islander students vary substantially by district. For instance, in Sequoia Union 54% go to college, but in South San Francisco Unified 92% go to college.

Figure V-28.

College-going Rates by Race and Ethnicity, 2017-18

Note: Cabrillo Unified and La Honda- Pescadero Unified are not included here because they do not report the data, likely due to small sample sizes.

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Source: California Department of Education and Root Policy Research College-going rates are lower for students with disabilities and those learning English compared to the overall student population across the county.  For instance, the largest gap between overall college-going rates and English learners’ college-going rates is in South San Francisco Unified, where just 52% of English learning students go to college as opposed to 74% of the overall student population— a 22 percentage point gap. Among English learners, San Mateo Union High School District had the highest college-going rate, where 63% of English learners go to college.  Among students with disabilities, South San Francisco Unified also had the largest gap, where 59% of students with disabilities went to college compared to 74% of the overall student population — a 15 percentage point gap. Jefferson Union, on the other hand, had a relatively high college-going rate among students with disabilities that was not very different from the district’s overall college-going rate: 71% went to college which is just five percentage points lower than the district’s overall student population.

Figure V-29.

College-going Rates
for English Learners
and Students with
Disabilities, 2017-
2018

Note:

Cabrillo Unified and La Honda-
Pescadero Unified are not included
here because they do not report the
data, likely due to small sample
sizes.

Source:

California Department of Education
and Root Policy Research.

Gaps in college enrollment by race, ethnicity, disability status, or English learning have stark financial consequences for students in the long-term. Figure V-30 illustrates median annual earnings by educational attainment. College degrees are especially important in San Mateo County: those with a bachelor’s degree in the county earn 115% more than those with a high school diploma. This gap is wider in San Mateo County than in other parts of California and nationwide. The differences between high-school graduate earnings and bachelor's degree earnings are around 100% in California and 76% in the US overall.

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Figure V-30.

Median Annual Earnings by Educational Attainment, 2019

Source: 5-year 2019 American Community Surveys Data.

Unfortunately, the gap between high school graduates’ and college graduates’ earnings have been increasing in San Mateo County. As illustrated in Figure V-31, median earnings for high school graduates increased by just 15% over the last decade (from $31,816 to $36,747) while earnings for college graduates increased by 29% over the same period (from $61,485 to $79,080).

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Figure V-31.

Median Annual Earnings by Educational Attainment in San Mateo County, 2010 to 2019

Source: 5-year American Community Surveys Data.

Because income disparities between college graduates and high school graduates have been increasing, it is increasingly important that school districts in San Mateo County address differences in college-going rates stratified by race, ethnicity, and extenuating circumstances.

Barriers to Success
Many students are unable to achieve academic success because of barriers in home and school. This section explores the available indicators of barriers to success, including chronic absenteeism and dropout rates. It also describes inequities in discipline rates by

ROOT POLICY RESEARCH SECTION V, PAGE 47
race and ethnicity, which has been linked both to discrimination by education professionals as well as a major barrier to students’ future success.

Chronic absenteeism. Academic studies have found that if a student is chronically absent, it reduces their math and reading achievement outcomes, educational engagement, and social engagement.12 Chronic absenteeism also has spillover effects and negatively impacts students who themselves are not chronically absent. For instance, one study found that students suffer academically from having chronically absent classmates— as exhibited across both reading and math testing outcomes.13 Students are considered chronically absent if they were absent for 10% or more of the days during a school year. Note, however, students are exempt from chronic absenteeism calculations if they receive instruction through a home or hospital instructional setting, are attending community college full-time, or were not expected to attend more than 31 days.

In the county overall, 10% of students were chronically absent during the 2018-2019 school year.14 This is a slight increase from the 2016-2017 school year, where just 9% of students overall were chronically absent.

Chronic absenteeism rates were higher in districts with a large number of students experiencing economic and housing precarity. For instance, Ravenswood Elementary, which has a 30% rate of homelessness among students, had one of the higher rates of chronic absenteeism at 16%. La Honda-Pescadero and Sequoia Union high school districts also had high rates of chronically absent students at 16% and 17%, respectively.

When disaggregating by race and ethnicity, just 3% of Asian students were chronically absent, and 7% of White and Filipino students were chronically absent. On the other end of the spectrum, Pacific Islander students (26%), Black/African American students (18%), and Hispanic students (15%) had notably higher rates of chronic absenteeism than the overall student population (10%). Chronic absenteeism among Pacific Islander students has increased in recent years, as illustrated in Figure V-32.

12 Gottfried, Michael A. "Chronic absenteeism and its effects on students’ academic and socioemotional outcomes." Journal of Education for Students Placed at Risk (JESPAR) 19.2 (2014): 53-75. 13 Gottfried, Michael A. "Chronic absenteeism in the classroom context: Effects on achievement." Urban Education 54.1 (2019): 3-34.
14 Because of the physical school closures during the COVID-19 pandemic, the California Department of Education determined that 2019–2020 absenteeism data are not valid, therefore, we present data from the 2018-2019 school year.

ROOT POLICY RESEARCH SECTION V, PAGE 48
Figure V-32.

Chronic
Absenteeism by
Race/Ethnicity,
2016-2017 to 2018-
2019
Source: California Department of
Education and Root Policy
Research

Chronic absenteeism among Pacific Islander students was especially pronounced in San Mateo-Foster City school district where there was a 26 percentage point gap between chronic absenteeism rates for Pacific Islander students (32%) and the overall student body (6%). Other districts had similarly large gaps, including San Bruno Park Elementary (20 percentage points) and South San Francisco Unified (18 percentage points).

Some districts had larger gaps in absenteeism rates between Black/African American students and the overall population. For instance, in San Carlos Elementary, 4% of the overall student body is chronically absent compared to 27% of Black/African American students— a 23 percentage point gap. Jefferson Elementary school district had a 17 percentage point gap between their overall chronic absenteeism rate (12%) and their chronic absenteeism rate among Black/African American students (28%).

Among White students, Bayshore Elementary School District was a major outlier, where 46% of White students were chronically absent compared to just 12% of the total student population. However, it is important to note that this represents a very small sample of White students: just 3% of students at Bayshore Elementary are White, one of lowest in the county.

ROOT POLICY RESEARCH SECTION V, PAGE 49
Figure V-33.

Chronic Absenteeism by District and Race/Ethnicity, 2018-2019

Source: California Department of Education and Root Policy Research In most districts, chronic absenteeism is higher among students with disabilities. In fact, only Bayshore Elementary’s students with disabilities had a lower rate of chronic absenteeism than the overall student body. In all other districts, students with disabilities were more likely to be chronically absent than the overall student population. This was particularly true in Sequoia Union High School District, Jefferson Union High School District, and San Mateo Union High School District, which had gaps between the overall School District
Unified School Districts
Cabrillo Unified 10% 5% (no data) 5% 11% (no data) 10%
La Honda-Pescadero 16% (no data) (no data) (no data) 14% (no data) 18% South San Francisco 13% 4% 16% 7% 17% 31% 12%
High & Elementary School Districts
Jefferson Union High School 15% 8% 22% 11% 22% 18% 15%
Bayshore Elementary 12% 5% 12% 0% 18% 19% 46%
Brisbane Elementary 12% 3% (no data) 12% 17% (no data) 17% Jefferson Elementary 12% 5% 28% 6% 13% 25% 23%
Pacifica 7% 4% 12% 6% 9% 21% 7%
San Mateo Union High School 10% 3% 18% 4% 17% 21% 9%
Burlingame Elementary 5% 2% 15% 5% 10% 20% 5%
Hillsborough Elementary 4% 1% (no data) 4% 4% (no data) 6% Millbrae Elementary 10% 3% 6% 17% 16% 26% 14%
San Bruno Park Elementary 12% 5% 10% 4% 14% 32% 9%
San Mateo-Foster City 6% 2% 9% 2% 10% 32% 4%
Sequoia Union High School 17% 6% 23% 8% 23% 33% 10%
Belmont-Redwood Shores 5% 3% 8% 5% 12% 17% 5%
Las Lomitas Elementary 4% 2% 0% (no data) 7% (no data) 3% Menlo Park City Elementary 3% 1% 8% 7% 5% 14% 3%
Portola Valley Elementary 4% 0% (no data) (no data) 6% (no data) 3% Ravenswood City Elementary 16% 0% 20% (no data) 15% 24% 21% Redwood City Elementary 10% 2% 19% 3% 12% 18% 4%
San Carlos Elementary 4% 2% 27% 8% 7% (no data) 3%
Woodside Elementary 8% 0% 0% (no data) 12% (no data) 7% Total 10% 3% 18% 7% 15% 26% 7%
Total Asian Black Filipino Hispanic
Pacific
Islander White
ROOT POLICY RESEARCH SECTION V, PAGE 50
absenteeism rate and the absenteeism rate among students with disabilities of 13, 12, and 11 percentage points, respectively.

Rates of chronic absenteeism were also higher among English learners than the general population in most districts (with the exception of Ravenswood City Elementary and Jefferson Elementary). Woodside Elementary and Sequoia Union High School districts both had 14 percentage point gaps between absenteeism rates of English learners and the overall student body.

In every school district where the data are available, foster youth had higher rates of chronic absenteeism than the overall population. This was especially true in Sequoia Union High School District, where 63% of foster youth were chronically absent compared to just 17% of the overall student body.

Similarly, in almost all districts with available data, students experiencing homelessness had higher rates of chronic absenteeism than the overall student body. The chronic absenteeism rate among students experiencing homelessness was highest in Burlingame Elementary at 64%.

Migrant students were chronically absent at rates similar to or lower than the total student body in all districts with reported data.

ROOT POLICY RESEARCH SECTION V, PAGE 51
Figure V-34.

Chronic Absenteeism by District and Extenuating Circumstance, 2018-2019

Source: California Department of Education and Root Policy Research

Dropout rates. As previously indicated, workers without a high school degree have the lowest annual earnings compared to others at higher levels of educational attainment. In addition to the economic and housing precarity associated with low earnings, low earnings also often lead to increased incentives to participate in criminal activity. In fact, one study School District
Unified School Districts
Cabrillo Unified 10% 12% 23% 9% (no data) 18%
La Honda-Pescadero 16% 16% (no data) (no data) (no data) 22% South San Francisco 13% 14% 47% 13% 49% 18%
High & Elementary School Districts
Jefferson Union High School 15% 27% 33% (no data) 36% 28% Bayshore Elementary 12% 19% (no data) (no data) (no data) 11% Brisbane Elementary 12% 18% (no data) (no data) (no data) 18% Jefferson Elementary 12% 10% 21% (no data) 24% 16%
Pacifica 7% 11% (no data) (no data) (no data) 14%
San Mateo Union High School 10% 21% 50% (no data) 53% 21% Burlingame Elementary 5% 8% 64% (no data) (no data) 12% Hillsborough Elementary 4% 6% (no data) (no data) (no data) 8% Millbrae Elementary 10% 12% 5% (no data) (no data) 12%
San Bruno Park Elementary 12% 12% (no data) (no data) 18% 20% San Mateo-Foster City 6% 8% 15% (no data) 17% 13%
Sequoia Union High School 17% 31% 52% 16% 63% 29%
Belmont-Redwood Shores 5% 11% (no data) (no data) (no data) 10% Las Lomitas Elementary 4% 6% (no data) (no data) (no data) 5% Menlo Park City Elementary 3% 5% (no data) (no data) (no data) 9% Portola Valley Elementary 4% 3% (no data) (no data) (no data) 9% Ravenswood City Elementary 16% 16% 19% 17% 23% 21%
Redwood City Elementary 10% 12% 30% 6% 32% 16%
San Carlos Elementary 4% 8% 23% (no data) (no data) 11% Woodside Elementary 8% 22% (no data) (no data) (no data) 10% Total
English
Learners
Experiencing
homelessness Migrant
With
Disabilities
Foster
Youth
ROOT POLICY RESEARCH SECTION V, PAGE 52
suggest that high school dropouts are 3.5 times more likely than high school graduates to be imprisoned at some point during their lifetime.15 Another study found that raising the high school completion rate by one percent for all men ages 20 through 60 would save the US $1.4 billion annually in crime related costs.16 Dropping out of high school also has adverse health costs: for instance, research has shown that high school dropouts are more likely to smoke and have a marijuana disorder in adulthood.17 For these reasons, reducing high school dropout rates in San Mateo County is pivotal to the health and economic prosperity of the community.

In this report, dropout rates shown for high school districts with available data and are defined as the percentage of cohort students who did not graduate with a regular high school diploma, did not complete high school, and are not still enrolled as a "fifth year senior".

In the 2019-2020 academic year, dropout rates were highest in Sequoia Union High School District, where 10% of students dropped out. This is similar to South San Francisco Unified, where 9% of students dropped out. In both these districts, and in Cabrillo Unified, dropout rates have increased since 2016-2017.

Dropout rates have decreased by one percentage point over the same period in San Mateo Union High School District, from 5% to 4%. Jefferson Union had the lowest dropout rate in the county at just 3%, which after slightly higher rates in 2017-18 and 2018-19, is the same as its 2016-2017 rate.

15 Monrad, Maggie. "High School Dropout: A Quick Stats Fact Sheet." National High School Center (2007). 16 U.S. Department of Justice, Bureau of Justice Statistics. (2002). Correctional populations in the United States, 1998 (NCJ-192929). Washington: U.S. Government Printing Office. 17 Gonzalez, Jennifer M. Reingle, et al. "The long-term effects of school dropout and GED attainment on substance use disorders." Drug and alcohol dependence 158 (2016): 60-66.

ROOT POLICY RESEARCH SECTION V, PAGE 53
Figure V-35.

Dropout Rates by
District, 2016-2017 to
2019-2020
Note: La Honda-Pescadero Unified
School District is excluded
from these data.

Source: California Department of
Education and Root Policy
Research

In all school districts in the county, dropout rates are higher for boys than for girls.

Jefferson Union had the smallest gender gap, where 3% of girls dropped out and 4% of boys dropped out. Sequoia Union had the widest gender gap, where 13% of boys dropped out compared to just 7% of girls.

Figure V-36.

Dropout Rates by
Gender, 2019-2020
Note: La Honda-Pescadero Unified
School District is excluded
from these data.

Source: California Department of
Education and Root Policy
Research

Pacific Islander, Black/African American, and Hispanic students in the county often had higher dropout rates than those in other racial and ethnic groups.

ROOT POLICY RESEARCH SECTION V, PAGE 54
 In Sequoia Union High School District, dropout rates were highest among Pacific Islander students, where 20% dropped out in the 2019-2020 academic year. Dropout rates were also especially high among Hispanic and Black/African American students in Sequoia Union, at 16% and 12% respectively.
 In districts with lower dropout rates, for instance, Jefferson Union, the highest dropout rates still found among Black/African American (7%) and Hispanic students (6%).  Notably, however, in South San Francisco Unified, White students were more likely to drop out than any other racial or ethnic group. In fact, 12% of White students dropped out compared to 11% of Hispanic students, 5% of Filipino students, and 3% of Asian students. Data for Black/African American and Pacific Islander students were not available for South San Francisco Unified due to small sample sizes.

Figure V-37.

Dropout Rates by Race, 2019-2020

ROOT POLICY RESEARCH SECTION V, PAGE 55
Source: California Department of Education and Root Policy Research In all school districts in the county, students with disabilities, students experiencing homelessness, foster youth, and students learning English had higher dropout rates than the overall population.
 Among students with disabilities, the highest dropout rate was in Sequoia Union, where 24% dropped out. The gap between overall dropout rates and dropout rates among students with disabilities was wide in Sequoia Union at 14 percentage points.  Cabrillo Unified, on the other hand, had less than a one percentage point gap between the dropout rate of overall students (6%) and students with disabilities (6%).  Among students learning English, Sequoia Union had the highest dropout rate at 27%, while Jefferson Union had the lowest dropout rate at 8%.  Sequoia Union also had the highest rate of dropout among students experiencing homelessness at 29% while Jefferson Union, again, had the lowest at 15%.  Foster Youth in Sequoia Union had an exceptionally high dropout rate a t 40%. San Mateo Union is the only other district in the county which reported these data in 2019- 2020, and found only 18% of foster youth dropped out.
 Migrant students at South San Francisco Unified actually dropped out at a rate slightly lower than the general student body: just 8% of migrant students dropped out compared to 9% of the overall student body. However, those in Cabrillo Unified were 11 percentage points more likely than the total student body to dropout.

ROOT POLICY RESEARCH SECTION V, PAGE 56
Figure V-38.

Dropout Rates by Extenuating Circumstance, 2019-2020

Source: California Department of Education and Root Policy Research

Disproportionate discipline rates. Strict discipline policies may stigmatize suspended students and expose them to the criminal justice system at a young age, setting them up for limited economic and social success down the line. Research has found that suspensions not only negatively affect the suspended students, but also their peers.

ROOT POLICY RESEARCH SECTION V, PAGE 57
Students in schools with higher suspension rates are more likely to drop out or school and less likely to attend a four-year college.18
Other academic studies have found that students from African American and Latino families are more likely than their White peers to receive expulsion or out of school suspension as consequences for the same or similar problem behavior.19 This means that Black/African American and Hispanic students suffer more of the economic and social consequences than their White peers for the same behaviors.

Luckily, in every high school district in San Mateo County, suspension rates have decreased since 2011-2012. La Honda-Pescadero School District experienced the largest decrease: it was the district with the highest suspension rate in 2011-2012 at 10%, but now has the lowest suspension rate at just 1% in 2019-2020. San Mateo Union also experienced a rapid decrease in suspension rates over the same period, with a rate of 9% in 2011-2012 to a rate of 3% in 2019-2020.

18 Bacher-Hicks, Andrew, Stephen B. Billings, and David J. Deming. The school to prison pipeline: Long-run impacts of school suspensions on adult crime. No. w26257. National Bureau of Economic Research, 2019. 19 Skiba, Russell J., et al. "Race is not neutral: A national investigation of African American and Latino disproportionality in school discipline." School Psychology Review 40.1 (2011): 85-107.

ROOT POLICY RESEARCH SECTION V, PAGE 58
Figure V-39.

Suspension Rates, 2011-2012 to 2019-2020

Source: California Department of Education and Root Policy Research In many school districts across San Mateo County, Hispanic students are disciplined at disproportionately higher rates compared to their peers. Figure V-40 compares each racial/ethnic group’s share of suspensions to their share of the overall student population.  In all districts except for La Honda-Pescadero, Hispanic students make up a larger share of suspensions than their overall share of the student body. For instance, in San Mateo Union, 34% of students are Hispanic, but 66% of suspended students are Hispanic, making a 32 percentage point overrepresentation gap.  In most districts, Black and Pacific Islander students are also overrepresented in terms of suspension rates, but these rates are slight compared to those of Hispanic students.

For instance, in Sequoia Union, just 2% of the student body identified as Pacific Islander but 8% of suspended students were Pacific Islander.  Asian and Filipino students were underrepresented in terms of suspension rates. For example, in Jefferson Union High School District, 31% of students identified as Filipino but just 10% of suspended students were Filipino, a 21 percentage point gap. In San

ROOT POLICY RESEARCH SECTION V, PAGE 59
Mateo Union High School, 22% of students identified as Asian but just 5% of suspended students were Asian, a 17 percentage point gap.  White students were also underrepresented in discipline rates in most districts except for La Honda-Pescadero, where they were overrepresented by 30 percentage points.

They were substantially underrepresented in Cabrillo Unified (with a gap of 21 percentage points) and Sequoia Union (18 percentage points).

ROOT POLICY RESEARCH SECTION V, PAGE 60
Figure V-40.

Suspension Rates by Race and Ethnicity, 2019-2020

Notes: the percentage of suspensions and shares of racial groups do not sum to 100% because we exclude students with no repor ted race, with more than one reported race, where districts did not report racial/ethnic data due to small sample sizes. Gaps of 15 percentage points or more are highlighted.

Source: California Department of Education and Root Policy Research

School District
Asian Students
Share of Student Body 1% 14% 22% 9% 13%
Share of Suspensions 1% 7% 5% 1% 3%
Gap 0% -7% -17% -8% -10%
Black Students
Share of Student Body 1% 1% 3% 1%
Share of Suspensions 5% 1% 6% 2%
Gap 4% 0% 3% 1%
Filipino Students
Share of Student Body 1% 31% 6% 2% 23%
Share of Suspensions 0% 10% 2% 0% 9%
Gap -1% -21% -4% -2% -14%
Hispanic Students
Share of Student Body 52% 32% 61% 34% 41% 48%
Share of Suspensions 79% 46% 33% 66% 62% 69%
Gap 27% 14% -28% 32% 21% 21%
Pacific Islander Students
Share of Student Body 1% 2% 2% 2%
Share of Suspensions 4% 4% 8% 3%
Gap 3% 2% 6% 1%
White Students
Share of Student Body 40% 14% 37% 26% 38% 7%
Share of Suspensions 19% 16% 67% 14% 20% 7%
Gap -21% 2% 30% -12% -18% 0%
Cabrillo
Unified
Jefferson
Union
High
La Honda-
Pescadero
San
Mateo
Union
High
Sequoia
Union
High
South San
Francisco
Unified
ROOT POLICY RESEARCH SECTION V, PAGE 61
Staff demographics. Diversity of school staff has been shown to improve outcomes for students of color. For instance, one recent study found that students are less likely to be removed from school as punishment when they and their teachers are the same race.

This effect is driven almost entirely by black students, especially black boys, who are markedly less likely to be subjected to exclusionary discipline when taught by black teachers. There is little evidence of any benefit for white students of being matched with white teachers.20 Other research in California has found that, when students have a teacher of their race, they are more likely to attend class, therefore reducing chronic absenteeism.21 Even more studies have found that having a teacher of a student’s own race substantially improves their math and reading achievement.22

In San Mateo County, the demographics of faculty and staff are fairly similar to that of its students. Figure V-41 illustrates the share of the county’s faculty and staff who are Asian, Black/African American, Hispanic, Filipino, Pacific Islander, and White, and compares those shares to the racial/ethnic breakdown of the county’s student body.

There is a slightly larger share of White and Black/African American staff than students, meaning that Black/African American and White student groups are more likely to interact with same-race staff and faculty than other racial groups. Asian students are less likely to interact with a same-race staff of faculty member: 17% of the student body is Asian compared to just 8% of staff and faculty.

20 Lindsay, Constance A., and Cassandra MD Hart. "Teacher race and school discipline: Are students suspended less often when they have a teacher of the same race?." Education Next 17.1 (2017): 72-79. 21 Gottfried, Michael, J. Jacob Kirksey, and Tina L. Fletcher. "Do High School Students With a Same-Race Teacher Attend Class More Often?." Educational Evaluation and Policy Analysis (2021): 01623737211032241. 22 Dee, T. S. (2004). Teachers, race, and student achievement in a randomized experiment. Review of economics and statistics, 86(1), 195-210.

ROOT POLICY RESEARCH SECTION V, PAGE 62
Figure V-41.

Staff and Student
Demographics,
2020-2021
Notes: Percentages do not always
sum to 100% because we
do not show shares of staff
with no reported race, with
more than one reported
race, or Native American
staff.

Source: California Department of
Education and Root Policy
Research

Since 2011-2012, the county’s school districts have diversified in that there has been a 13 percentage point decrease in the share of White faculty and staff and a 10 percentage point increase in Hispanic faculty and staff. However, there has been a slight decrease (by two percentage points) in the share of faculty and staff who identify as Black/African American. There has been a two percentage point increase in the share of Asian and Filipino faculty and staff, and a one percent increase in the share of Pacific Islander faculty and staff.

ROOT POLICY RESEARCH SECTION V, PAGE 63
Figure V-42.

Faculty and Staff Demographics, 2011-2012 to 2020-2021

Notes: Percentages do not always sum to 100% because we do not show shares of staff with no reported race, with more than one reported race, or Native American staff.

Source: California Department of Education and Root Policy Research Figure V-43 illustrates faculty and staff racial and ethnic diversity for the 2020-2021 school year by district.
 Portola Valley has the least diverse faculty and staff in the county, with 59% identifying as White.
 Ravenswood Elementary has the most diverse faculty and staff: the district has the highest share of Pacific Islander (5%), Black/African American (12%) and Hispanic (72%) faculty and staff.
 South San Francisco Unified School District has the highest share of Asian faculty and staff at 14%.
 Brisbane Elementary and Jefferson Elementary have the highest shares of Filipino faculty and staff at 28%.

ROOT POLICY RESEARCH SECTION V, PAGE 64
Figure V-43.

Faculty and Staff Race/Ethnicity, by District, 2020-2021

Notes: Percentages do not always sum to 100% because we do not show shares of staff with no reported race, with more than one reported race, or Native American staff.

Source: California Department of Education and Root Policy Research School District
Unified School Districts
Cabrillo Unified 0% 1% 1% 46% 0% 51%
La Honda-Pescadero 0% 5% 5% 39% 0% 51%
South San Francisco 14% 3% 16% 34% 2% 28%
High & Elementary School Districts
Jefferson Union High School 3% 3% 13% 26% 1% 43%
Bayshore Elementary 13% 4% 17% 61% 0% 4%
Brisbane Elementary 7% 0% 28% 20% 4% 42%
Jefferson Elementary 13% 3% 28% 25% 0% 29%
Pacifica 7% 2% 8% 23% 2% 54%
San Mateo Union High School 11% 5% 6% 34% 3% 40%
Burlingame Elementary 8% 5% 11% 27% 3% 45%
Hillsborough Elementary 2% 1% 7% 20% 1% 55%
Millbrae Elementary 13% 3% 9% 25% 0% 48%
San Bruno Park Elementary 4% 2% 13% 26% 4% 48%
San Mateo-Foster City 13% 2% 7% 33% 3% 37%
Sequoia Union High School 2% 12% 2% 54% 4% 26%
Belmont-Redwood Shores 13% 2% 3% 39% 0% 42%
Las Lomitas Elementary 7% 7% 0% 42% 0% 42%
Menlo Park City Elementary 3% 1% 3% 28% 1% 40%
Portola Valley Elementary 4% 4% 0% 33% 0% 59%
Ravenswood City Elementary 2% 12% 1% 72% 5% 3%
Redwood City Elementary 4% 5% 2% 65% 1% 21%
San Carlos Elementary 8% 6% 3% 37% 1% 42%
Woodside Elementary 12% 8% 0% 30% 0% 49%
Total 8% 5% 8% 40% 2% 35%
WhiteAsian Black Filipino Hispanic
Pacific
Islander
ROOT POLICY RESEARCH SECTION V, PAGE 65
Figure V-44 illustrates the gap between faculty/staff representation and the student body.

For instance, at San Bruno Park Elementary, 15% of the students are White while 48% of the faculty/staff are White, leaving a 33 percentage point gap.

If schools are striving for a distribution of faculty/staff that reflects the racial and ethnic distribution of their student body, the closer to a 0 percentage point gap, the better.

Schools like San Bruno Park Elementary fall short of meeting this goal, in that there is a large overrepresentation of White faculty/staff compared to the student body. Many other districts have a large overrepresentation of White faculty/staff, including Millbrae Elementary (32 percentage point gap), Jefferson Union High School District (29 percentage point gap), and South San Francisco Unified School District (22 percentage points). There are just a few school districts where the share of White students is higher than the share of White faculty, particularly Woodside Elementary and Menlo Park City Elementary, both with a 15 percentage point gap.

Across most school districts, the share of Asian students is larger than the share of Asian faculty/staff. This suggests that Asian students are less likely than their peers to interact with a same-race teacher or staff member. The largest disparity is in Millbrae Elementary, where just 13% of the faculty identify as Asian compared to 46% of the student body, a 33 percentage point gap.

In many school districts, there is a dearth of Hispanic faculty and staff. For instance, in La Honda-Pescadero, 63% of students are Hispanic compared to 39% of faculty, a 24 percentage point gap. In other districts, however, there is a larger share of Hispanic faculty/staff than students. In Las Lomitas Elementary, for instance, 13% of students are Hispanic and 42% of faculty/staff are Hispanic. Recall that Las Lomitas Elementary commonly has high-performing English language learnings students. This may be partly due to the district’s large portion of Hispanic faculty/staff.

Though district wide there are approximately the same portions of Filipino students as there are faculty/staff, Jefferson Union High School stands out as a district where Filipino students are less likely to interact with a same-race teacher or staff member. In Jefferson Union, 29% of students are Filipino compared to just 13% of faculty/staff.

In all districts, there only very small gaps in the share of students that identify as Pacific Islander and the share of faculty/staff that identify as Pacific Islander. All in all, they are represented in approximately equal proportions.

ROOT POLICY RESEARCH SECTION V, PAGE 66
Figure V-44.

Difference Between Staff and Student Populations, by District, 2020-2021

Notes: The figure shows percentage point gaps in student representation versus faculty/staff rep resentation (calculated as the share of faculty/staff minus the share of students).

Source: California Department of Education and Root Policy Research

School District
Unified School Districts
Cabrillo Unified -1% 1% 0% -6% 0% 11%
La Honda-Pescadero 0% 5% 4% -24% 0% 16%
South San Francisco 0% 2% -7% -14% 0% 22%
High & Elementary School Districts
Jefferson Union High School -12% 2% -16% -5% 0% 29%
Bayshore Elementary -6% 1% -4% 20% -4% 1%
Brisbane Elementary -13% -1% 16% -8% 4% 18%
Jefferson Elementary -6% 1% 3% -11% -1% 18%
Pacifica -1% 1% -1% -3% 2% 15%
San Mateo Union High School -12% 4% 1% 2% 1% 12%
Burlingame Elementary -19% 5% 8% 11% 3% 4%
Hillsborough Elementary -30% 1% 5% 15% 1% 7%
Millbrae Elementary -33% 2% 3% 5% -2% 32%
San Bruno Park Elementary -12% 1% 3% -15% -1% 33%
San Mateo-Foster City -13% 1% 4% -4% 1% 16%
Sequoia Union High School -7% 10% 1% 9% 2% -9%
Belmont-Redwood Shores -19% 1% 0% 27% -1% 8%
Las Lomitas Elementary -11% 6% -1% 29% 0% -11%
Menlo Park City Elementary -10% 0% 2% 11% 0% -15%
Portola Valley Elementary -2% 4% 0% 19% 0% -7%
Ravenswood City Elementary 2% 7% 1% -12% -2% 2%
Redwood City Elementary 0% 4% 1% -5% 0% 2%
San Carlos Elementary -10% 5% 2% 23% 1% -7%
Woodside Elementary 8% 6% 0% 14% -1% -15%
Total -9% 4% 0% 2% 0% 9%
Asian Black Filipino Hispanic
Pacific
Islander White

1 Alvin Jen
From: Farhad Mortazavi
Sent: Wednesday, January 11, 2023 4:36 PM
To: Jeremy Levine; Alvin Jen
Subject: RE: Housing Element Drafts Public Records Request Hi Jeremy,

Thank you for your email and for your comments - we will share your insight with the city council at their hearing on January 25
th.

Thank you for your assistance on this very important process.

- Farhad

From: Jeremy Levine <[email protected]>
Sent: Saturday, January 7, 2023 3:57 PM
To: Alvin Jen <[email protected]>
Cc: Farhad Mortazavi <[email protected]>
Subject: Re: Housing Element Drafts Public Records Request

Alvin and Farhad,

Have Colma staff made any substantial changes in response to HLC's or HCD's recommendations? I just skimmed the latest draft and I did not see the addition of many new policies and programs in response to HLC's input.

Thank you for any help you can provide,
Jeremy

--
Jeremy Levine (he • him)
Policy Manager
Housing Leadership Council of San Mateo County
(925) 451-4620

On Thu, Oct 6, 2022 at 12:18 PM Jeremy Levine <[email protected]> wrote:

Also, if it would be helpful, I am happy to provide a version of these comments directly to the council for their consideration.

--
Jeremy Levine (he • him)
Policy Manager
Housing Leadership Council of San Mateo County
(925) 451-4620

On Thu, Oct 6, 2022 at 11:35 AM Jeremy Levine <[email protected]> wrote:

Good to hear from you Alvin. Colma is a unique place, and it was helpful to get an insider perspective on the community.
2 I've spent some time reflecting on our conversation, and I want to reiterate my core principles before offering feedback. All communities, large and small, are equally responsible to plan for housing. Colma, blessed with abundant transit access and nearby businesses, is an excellent location for growth. The entire Colma community, including its retail workforce, deserves housing options to accommodate their need.

With these principles in mind, I would like to revisit HLC's earlier policy recommendations. I understand that CSG staff are reluctant to change zoning standards in the Sterling Park neighborhood. If CSG wants to limit policy changes in the Sterling Park area, then significant changes will be required elsewhere. These changes should include:
• Opportunity sites need clear development plans. The housing element should specify exactly what incentives the PD zones will offer to promote housing on the relevant site. These incentives should be significantly greater than those already provided by state law.
• The Kohl's site in particular represents a great opportunity for new housing, but I'm not optimistic about its redevelopment over the next eight years under current plans. The parking lot was full in the middle of the day on a Friday. However, I believe this site could potentially be made viable with the right incentives:
o As part of its analysis, the city should consider the term of the lease for the Kohl's site as well as all other commercial uses that would need to be terminated in order for development to occur there. The element should also consider environmental factors and other potential risks, such as CEQA lawsuits.

Lastly, the element should describe the feasibility study Colma commissioned for the Kohl's site back in 2014 (if I am remembering correctly) and explain why the town has not yet taken any actions to incentivize development there. This analysis must be provided to consider Kohl's as an opportunity site at all.
o In order to make the Kohl's site a viable opportunity site, Colma should provide irresistible incentives for housing there in order to count the site in its RHNA allocation. Incentives should include at least 80 du/ac, at least 5 stories, FAR of 4 or more, lot coverage of 80% or more, limited setbacks and stepbacks, and by-right approval.
• Colma needs a few other new policies to promote affordable housing. These should include:
o Impact fee exemptions and planning and building fees deferral for 100% affordable housing projects.

This would be a strong AFFH policy.
o Commercial linkage fee to apply to all new commercial development in Colma, with revenue to be dedicated to subsidizing 100% affordable housing projects.

I also recommend that Colma create a new zoning district to apply to all commercial land in response to new state laws recently signed by the governor, particularly AB 2011 and AB 2097. AB 2011 will allow housing by ministerial approval on all commercially zoned land in Colma; AB 2097 will eliminate parking minimums within 0.5 miles of transit stops. Colma should create a new zoning district that reflects state regulations, plus a few extra incentives, and claim credit in the housing element.

I understand CSG can only do so much without council direction. I recommend that you urge your council members to proactively respond to public comments and work directly with the Housing Leadership Council. I will continue to be available to provide assistance.

Regards,
Jeremy
--
Jeremy Levine (he • him)
Policy Manager
Housing Leadership Council of San Mateo County
(925) 451-4620

On Tue, Oct 4, 2022 at 9:03 AM Alvin Jen <[email protected]> wrote:
3 Hi Jeremy,

I am catching up on emails. You are very welcome! I hope the tour was beneficial and provided a further perspective of our sites. We are open to you providing us a more catered programs for our housing element and other suggestions that we may have not covered that day.

Best,

Alvin Jen
Assocciate Planner, CSG Consultants

Town of Colma
Planning Department
1198 El Camino Real, Colma, CA 94014
www.colma.ca.gov
[email protected]
650.757.8888 main
650.997.8314 direct
650.757.8890 fax

From: Jeremy Levine <[email protected]>
Sent: Friday, September 23, 2022 3:31 PM
To: Alvin Jen <[email protected]>
Cc: Farhad Mortazavi <[email protected]>
Subject: Re: Housing Element Drafts Public Records Request

Great to see you today Alvin, thank you for taking the time to show me around town. I look forward to working with the town on preparing a second housing element draft.

Have a great weekend,
4 Jeremy

--
Jeremy Levine (he • him)
Policy Manager
Housing Leadership Council of San Mateo County
(925) 451-4620

On Fri, Sep 23, 2022 at 9:08 AM Jeremy Levine <[email protected]> wrote:

ETA now 9:35… on the train but facing serious delays.

On Fri, Sep 23, 2022 at 8:32 AM Alvin Jen <[email protected]> wrote:

Hi Jeremy,

Thanks for the update. I’ll see you soon!

-Alvin

From: Jeremy Levine <[email protected]>
Sent: Friday, September 23, 2022 8:29 AM
To: Alvin Jen <[email protected]>
Cc: Farhad Mortazavi <[email protected]>
Subject: Re: Housing Element Drafts Public Records Request

Sounds good Alvin, will do! I’m excited for the tour today.

5 FYI BART has a technical error so my train is significantly delayed. Looking like I’ll be closer to a 9:20 arrival, will keep you updated.

Cheers,
Jeremy

--
Jeremy Levine (he • him)
Policy Manager
Housing Leadership Council of San Mateo County
(925) 451-4620

On Thu, Sep 22, 2022 at 7:38 AM Alvin Jen <[email protected]> wrote:

Good morning Jeremy,

I have attached the comment provided to the Town from HCD dated 9/14/22.

For tomorrow, when you arrive at the Colma BART station, please call me on my direct line 650-997-8314. I can coordinate where I can pick you up and begin our tour. Once we conclude the tour of the potential sites and town, I was hoping we could stop by Town Hall and have a discussion. I’ll see you tomorrow.

Best,

Alvin Jen
Assocciate Planner, CSG Consultants

6 Town of Colma
Planning Department
1198 El Camino Real, Colma, CA 94014
www.colma.ca.gov
[email protected]
650.757.8888 main
650.997.8314 direct
650.757.8890 fax

From: Jeremy Levine <[email protected]>
Sent: Wednesday, September 21, 2022 8:53 AM
To: Alvin Jen <[email protected]>
Cc: Farhad Mortazavi <[email protected]>
Subject: Re: Housing Element Drafts Public Records Request

Good morning Alvin, I'm still looking forward to Friday! Would you please share HCD's review letter for Colma's housing element with me? I would like to review before we meet, but the website where HCD normally keeps this information has not been updated recently.

Regards,
Jeremy

--
Jeremy Levine (he • him)
Policy Manager
Housing Leadership Council of San Mateo County
(925) 451-4620

To help protect your privacy,
Micro so ft Office prevented auto matic downlo ad o f this picture from the Internet. 7 On Tue, Sep 13, 2022 at 6:01 PM Jeremy Levine <[email protected]> wrote:

Excellent, I look forward to it!

--
Jeremy Levine (he • him)
Policy Manager
Housing Leadership Council of San Mateo County
(925) 451-4620

On Tue, Sep 13, 2022 at 9:03 AM Alvin Jen <[email protected]> wrote:

Hi Jeremy,

No worries. Yes. Let’s meet on the 23rd at 9:00 AM. I can pick you up from the BART station and we can work our way around town. A hard stop at 11:45 AM would not be a problem.

Best,

Alvin Jen
Assistant Planner, CSG Consultants

Town of Colma
Planning Department
1198 El Camino Real, Colma, CA 94014
www.colma.ca.gov
[email protected]
650.757.8888 main
650.997.8314 direct
650.757.8890 fax
To help protect your privacy,
Micro so ft Office prevented auto matic downlo ad o f this picture from the Internet. 8 From: Jeremy Levine <[email protected]>
Sent: Tuesday, September 13, 2022 9:00 AM
To: Alvin Jen <[email protected]>
Cc: Farhad Mortazavi <[email protected]>
Subject: Re: Housing Element Drafts Public Records Request

Hi Alvin, sorry again for the late followup--lots of action going on with other cities' housing elements. I'd be happy to come to Colma on the 23rd, I'll just have a hard stop at 11:45. How would meeting at 9am at Colma BART work for you?

If the 23rd no longer works, I could also do the afternoon on the following Wednesday, 9/28.

Hoping we can work something out!
Jeremy

--
Jeremy Levine (he • him)
Policy Manager
Housing Leadership Council of San Mateo County
(925) 451-4620

On Mon, Aug 29, 2022 at 8:10 AM Alvin Jen <[email protected]> wrote:

Good morning Jeremy,

Unfortunately, September 16th will not work for me. How about the following Friday, September 23?

Best,
9 Alvin Jen
Assistant Planner, CSG Consultants

Town of Colma
Planning Department
1198 El Camino Real, Colma, CA 94014
www.colma.ca.gov
[email protected]
650.757.8888 main
650.997.8314 direct
650.757.8890 fax

From: Jeremy Levine <[email protected]>
Sent: Friday, August 26, 2022 6:02 PM
To: Alvin Jen <[email protected]>
Cc: Farhad Mortazavi <[email protected]>
Subject: Re: Housing Element Drafts Public Records Request

No problem, I can do 9:30-11:30 on Friday 9/16.

--
Jeremy Levine (he • him)
Policy Manager
Housing Leadership Council of San Mateo County
(925) 451-4620

On Fri, Aug 26, 2022 at 4:04 PM Alvin Jen <[email protected]> wrote:

To help protect your privacy,
Micro so ft Office prevented auto matic downlo ad o f this picture from the Internet. 10 Hi Jeremy,

Now I have to apologize for my delayed response. Is there another time next month that would work for you? I am starting a new assignment and will no longer be in Colma on Wednesdays and Thursdays. Starting September 7th, I will be on-site in Town Hall Mondays, Tuesdays, and Fridays.

Best,

Alvin Jen
Assistant Planner, CSG Consultants

Town of Colma
Planning Department
1198 El Camino Real, Colma, CA 94014
www.colma.ca.gov
[email protected]
650.757.8888 main
650.997.8314 direct
650.757.8890 fax

From: Jeremy Levine <[email protected]>
Sent: Thursday, August 18, 2022 9:39 PM
To: Alvin Jen <[email protected]>
Cc: Farhad Mortazavi <[email protected]>
Subject: Re: Housing Element Drafts Public Records Request

Pardon my delay Alvin, I can do a tour scheduled for September 15. How would 9:30- 11:30 a.m. work for you? I would take BART over, unless you prefer I drive.

--
To help protect your privacy,
Micro so ft Office prevented auto matic downlo ad o f this picture from the Internet. 11 Jeremy Levine (he • him)
Policy Manager
Housing Leadership Council of San Mateo County
(925) 451-4620

On Wed, Aug 10, 2022 at 7:41 AM Alvin Jen <[email protected]> wrote:

Good morning Jeremy,

We’re happy to host you. Can we tentatively schedule it for September 15? As you may know, Colma is fairly small, so I don’t anticipate more than a couple of hours for the tour and chat.

Regarding the PD, I’m happy to discuss it when we meet in person and would also appreciate any strategies that you believe could work for our Town. Let’s touch base the week leading up to September 15, to coordinate.

Best,

Alvin Jen
Assistant Planner, CSG Consultants

Town of Colma
Planning Department
1198 El Camino Real, Colma, CA 94014
www.colma.ca.gov
[email protected]
650.757.8888 main
650.997.8314 direct
650.757.8890 fax
To help protect your privacy,
Micro so ft Office prevented auto matic downlo ad o f this picture from the Internet. 12 From: Jeremy Levine <[email protected]>
Sent: Tuesday, August 9, 2022 12:59 PM
To: Alvin Jen <[email protected]>
Subject: Re: Housing Element Drafts Public Records Request

Hi Alvin, thank you for your thoughtful responses. They are very helpful. I would be happy to plan a driving tour of Colma! What's your schedule like September 14-16? Mine is wide open those days.

I'm still curious about a few things. What specific flexibility does the PD zone allow for housing development on Colma's opportunity sites? The housing element only describes allowances of 30 du/ac in most cases, which is quite low. There is no description of height, setbacks, parking, or other requirements that affect the likelihood of redevelopment for housing on the sites Colma's draft housing element proposes. I would be surprised if Colma truly has no opportunity to create greater incentives for affordable housing on its opportunity sites, especially the Kohl's site.

Is some barrier preventing the city from changing its base zoning to allow higher density housing over a larger area? I don't understand the reliance on planned development zones, which seem to allow for discretionary approval, calling into question the validity of all opportunity sites located in a PD zone.

Thank you for your ongoing assistance and patience with me, Jeremy

--
Jeremy Levine (he • him)
Policy Manager
Housing Leadership Council of San Mateo County
(925) 451-4620

On Mon, Aug 1, 2022 at 9:53 AM Alvin Jen <[email protected]> wrote:
13 Hi Jeremy,

I would be happy to provide some insight regarding the public comment draft and the draft submitted to HCD.

• Colma is a unique town unlike any jurisdiction in San Mateo County and California. 75% of our

2.2 square mile jurisdiction is dedicated cemetery land. • The 3.07-acre site located at El Camino and F Street was removed from consideration from our inventory at the request of Italian Cemetery (property owner). I mentioned this during our phone call earlier last month. The city planner, Farhad Mortazavi, sat in several meetings with the Italian Cemetery board members since the draft was made available for comment. Unfortunately, they changed their mind and requested that their property be removed as an opportunity site. As you may know, this was a big hit to our site inventory and with this new challenge, we distributed low- income units to other sites.
• In both the public draft and draft to HCD, 7733 and 7778 El Camino is currently vacant, and we plan to have at least 8 and 7 low-units there. The rest of the low-income sites would be located at 1200 El Camino Real at the Kohl’s site.
• Regarding programs for this cycle, we believe that what we have submitted to HCD will support new development given the existing conditions of this Town. Most, if not all the sites have been identified as part of our General Plan Update, adopted this past March 2022. Furthermore, the site at El Camino Real and Collins is zoned PD which allows more flexibility than any program could provide.
• If HCD does not feel that our policies and programs are not sufficient for the 6 th cycle Housing Element, we will strategize and adjust accordingly.

If you would like to have a driving tour of the Town, visit some of our potential sites, as well as get an understanding of the lay of the land, I would be happy to host you.

Best,

Alvin Jen
Assistant Planner, CSG Consultants

14 Town of Colma
Planning Department
1198 El Camino Real, Colma, CA 94014
www.colma.ca.gov
[email protected]
650.757.8888 main
650.997.8314 direct
650.757.8890 fax

From: Jeremy Levine <[email protected]>
Sent: Friday, July 29, 2022 10:06 AM
To: Alvin Jen <[email protected]>
Cc: [email protected]
Subject: Re: Housing Element Drafts Public Records Request

Thanks for getting back to me Alvin, I want to clarify a few things:

It seems like the most significant change between the draft released for public comment and the draft submitted to HCD is that the city removed the vacant F street site from the opportunity site list and identified a handful of alternative sites for affordable housing. Formerly, the city planned for all of its low- income units at the vacant F Street site; now, the city has redistributed those low- income units to the Kohl's site and a handful of other sites, all of which are non-vacant. Almost all of the city's low- and very low- income housing is planned for the Kohl's site, with a few lower income units planned for other sites. There are still no new policies or programs. Beyond zoning for denser housing, the city has no other incentives to encourage affordable housing at the Kohl's site or elsewhere.

Is this a correct summary of the changes Colma made to its housing element between the public comment period and submission to HCD? If not, please explain changes I missed.

Thank you for all your hard work and patience with me,
Jeremy

To help protect your privacy,
Micro so ft Office prevented auto matic downlo ad o f this picture from the Internet. 15 --
Jeremy Levine (he • him)
Policy Manager
Housing Leadership Council of San Mateo County
(925) 451-4620

On Tue, Jul 26, 2022 at 7:41 AM Alvin Jen <[email protected]> wrote:

Hi Jeremy,

We received a voicemail from you regarding questions about the site inventory map from the Housing Element. Feel free to respond to this email with your questions and I can do my best to answer them.

Best,

Alvin Jen
Assistant Planner, CSG Consultants

Town of Colma
Planning Department
1198 El Camino Real, Colma, CA 94014
www.colma.ca.gov
[email protected]
650.757.8888 main
650.997.8314 direct
650.757.8890 fax

To help protect your privacy,
Micro so ft Office prevented auto matic downlo ad o f this picture from the Internet. 16 From: Jeremy Levine <[email protected]>
Sent: Monday, July 25, 2022 11:59 AM
To: Alvin Jen <[email protected]>
Subject: Re: Housing Element Drafts Public Records Request

Thank you!

--
Jeremy Levine (he • him)
Policy Manager
Housing Leadership Council of San Mateo County
(925) 451-4620

On Fri, Jul 22, 2022 at 4:01 PM Alvin Jen <[email protected]> wrote:

Hi Jeremy,

The attached file is the April 29, 22 public comment version.

Best,

Alvin Jen
Assistant Planner, CSG Consultants

Town of Colma
Planning Department
1198 El Camino Real, Colma, CA 94014
www.colma.ca.gov
[email protected]
To help protect your privacy,
Micro so ft Office prevented auto matic downlo ad o f this picture from the Internet. 17 650.757.8888 main
650.997.8314 direct
650.757.8890 fax

From: Jeremy Levine <[email protected]>
Sent: Thursday, July 21, 2022 6:42 PM
To: [email protected]
Subject: Housing Element Drafts Public Records Request

Good evening Alvin,

Would you please share the draft housing element released for public comment by Colma on April 29 as well as the draft that you submitted to HCD on June 15? I noticed only the draft submitted to HCD is online, and I would like to compare some of the changes that the town made before submission.

Thank you for your assistance,
Jeremy

--
Jeremy Levine (he • him)
Policy Manager
Housing Leadership Council of San Mateo County
2905 El Camino Real
San Mateo, CA 94403
www.hlcsmc.org
650.242.1764

Facebook • Twitter • LinkedIn • Instagram • Become A Member! 18 --
--
Jeremy Levine (he • him)
Policy Manager
Housing Leadership Council of San Mateo County
2905 El Camino Real
San Mateo, CA 94403
www.hlcsmc.org
650.242.1764

Facebook • Twitter • LinkedIn • Instagram • Become A Member! --
--
Jeremy Levine (he • him)
Policy Manager
Housing Leadership Council of San Mateo County
2905 El Camino Real
San Mateo, CA 94403
www.hlcsmc.org
650.242.1764

Facebook • Twitter • LinkedIn • Instagram • Become A Member! City of Colma
1198 El Camino Real
Colma, CA 94014
RE: Housing Element Public Comment
To the honorable Colma city council,
The Housing Leadership Council (HLC) appreciates this opportunity to comment on the city of Colma’s housing element. HLC works with communities and their leaders to create and preserve quality affordable homes. We were founded by service providers and affordable housing professionals over 20 years ago to change the policies at the root cause of our housing shortage.

Over the past Regional Housing Needs Allocation cycle, Colma has made admirable efforts to invest in affordable housing. Colma is one of the few cities in San Mateo County to have surpassed the total number of units from its 5th RHNA cycle, with 75 units permitted in Colma from 2015-2020, well above the RHNA allocation of 59 units. Colma was particularly successful because of the Veterans Village project, 66 units of affordable housing for veterans.

Nonetheless, Colma faces significant challenges for meeting its 6th RHNA cycle goals. Colma’s RHNA allocation has more than tripled, from 59 units to 202 units. New guidelines, like the mandate to Affirmatively Further Fair Housing, put new responsibilities on cities to remove constraints to housing development and proactively promote fair housing.

With this letter, HLC provides proposals for changes and additions that will produce more housing for the community’s most vulnerable residents. We want to be a partner to the city, sharing our knowledge of state law and best practices to facilitate fair housing.

Thank you for your consideration,
Jeremy Levine
Policy Manager, Housing Leadership Council of San Mateo County

Needs and Fair Housing Analyses and Outreach
● Connect identified housing needs directly to potential policies Colma could implement to address those needs. See “Goals, Policies, and Programs” section of this letter for specific recommendations for new policies.
● Integrate Fair Housing Implementation Plan into Goals, Policies, and Programs. Expand Action 2.1 into several actions with discrete deadlines to implement new policies that remove specific constraints to housing.
● Create and implement an outreach plan to engage the entire Colma community in the housing element process, including all households and local employees. Such a plan requires housing element-specific meetings and workshops as well as renewed mailers and other forms of outreach to contact segments of the Colma community that the city has not adequately heard from.

With their Needs and Fair Housing Analyses, cities consider housing needs that are going unmet under status quo local regulations. Cities are required to proactively seek input from all segments of the community in order to inform their needs and fair housing analyses.1 Needs should be connected directly to the local constraints creating that need and then addressed by new goals, policies, and programs.

In its needs analysis, Colma’s draft housing element accurately recognizes “Affordable housing is limited and the ability to add affordable housing is constrained by land use.”2 Colma further recognizes that the limited availability of affordable housing occurs because “there are no areas of the town that are zoned for multifamily housing, which is disproportionately occupied by residents of color” (p. 47). Colma acknowledges that the lack of affordable housing is the primary reason that 100% of its ELI households face “overcrowding, overpayment,” and substandard living conditions.3 HLC appreciates Colma’s honest, unflinching analysis of the ways its land use restrictions limit housing availability.

Considering Colma’s largely accurate appraisal of some significant unmet housing needs, HLC is confused why not one policy or program takes substantive new actions to remove land use constraints in ways that facilitate more multifamily housing production. The housing element process requires that Colma take substantive steps to address identified housing needs. HLC provides recommendations for Colma to implement new policies and programs in the “Goals, Policies, and Programs” portion of this letter.

Some housing needs go unrecognized entirely, particularly the need created by Colma’s massive jobs-housing imbalance. The draft housing element considers that “Colma has more than three times as many jobs as residents,”4 but does not recognize that Colma lacks the 4 Draft housing element, p. 15
3 Draft housing element, p. 40
2 Draft housing element, p. 46
1 Gov. Code, §§ 65583, subd. (c)(10)(A), 8899.50, subds. (a), (b), (c); see also AFFH Final Rule and Commentary (AFFH Rule), 80 Fed. Reg. 42271, 42348-42351, 42353-42360, esp. 42353-42354 (July 16, 2015).; See page 24 of HCD’s Affirmatively Furthering Fair Housing Guidebook. housing to provide for its workforce. In the same paragraph, Colma presents data indicating that 60% of its workforce earns less than $3,333 per month. Colma’s success adding 75 units in the past RHNA cycle stands in contrast to its local jobs growth: Over the same period, Colma added 170 jobs. Such disparities undermine Colma’s success at building affordable veterans housing:
66 units of affordable housing for veterans comes nowhere close to meeting the needs of Colma’s workforce.

The state of California has invested tens of millions of dollars in Colma’s economic development through the Colma BART station. Colma’s access to a regional workforce–and thus a plentiful tax base–is in large part possible exclusively because of the community’s proximity to a BART station. Considering the state’s investment, Colma has a responsibility to ambitiously pursue policy changes that will help the city meet the housing needs of its entire community, including its workforce, and generate riders and revenue for our regional transportation network.

Unfortunately, throughout Colma’s draft housing element, the city frequently fails to connect identified needs to new policy proposals intended to remove constraints to meeting those needs. For example, when considering one special needs population, people with disabilities, Colma’s analysis accurately describes community need but then abdicates responsibility to meet that unique need: “The three major needs for people with disabilities are low cost (subsidized) rents, handicapped accessible homes, and buildings near public transportation.

These needs are very similar to the desires of other segments of the population. Policies that promote affordable housing generally are also good for the disabled community.”5 While technically accurate, this statement ignores the AFFH mandate for Colma to actively promote policies that cater to the unique needs of special populations.6 In the unique case of populations with special disabilities, Colma must actively take steps to promote housing accessibility for those groups–for example, by allowing higher densities for projects with extra ADA-accessible units built within 0.5 miles of Colma’s BART station. Again, HLC recommends specific policies the city could implement to remedy this gap in our goals, policies, and programs section.

Action 2.1 in Colma’s Fair Housing Plan has the seeds of a successful housing element.7 This action lists a series of constraints that the city may decide to remove in order to meet its quantified housing goals. However, this action lacks specificity and clear timelines for the removal of constraints. Rather than identifying specific policy changes, the action describes broad constraints, without identifying how they will actually be removed in a way that facilitates new housing production.

Furthermore, the entirety of the Fair Housing Action Plan is not reflected in the draft housing element’s goals, policies, and programs. If the city intends to remove constraints to new housing 7 Draft housing element, p. 48
6 Gov. Code, § 65583, subds. (a)(7), (c)
5 Draft housing element, p. 33
as described in its Fair Housing Action Plan, then the policies described in the Fair Housing Action Plan must be integrated into the city’s formal goals, policies, and programs.

Colma may be more effective at identifying housing needs and implementing new policies into its housing element if it pursues a more robust community outreach process. HCD’s Affirmatively Furthering Fair Housing Guidebook states that the “housing element requires a diligent effort to include all economic segments of the community.”8 Furthermore, “The element must describe meaningful, frequent, and ongoing community participation, consultation, and coordination that is integrated with … the overall housing element.”9 Colma claims that it sent fliers informing “every resident” about the housing element, citing 361 households. According to census data included in Colma’s own housing element, Colma had 835 households as of 2020.10 How did Colma’s outreach miss more than half of its households? Furthermore, large segments of Colma’s community seem to have been left out of consideration of the housing element entirely. With an estimated 4,070 jobs in the community–leading to a whopping jobs-housing balance of 4.73–Colma’s workforce comprises an important part of the community. Yet the draft housing element indicates that the City of Colma has not made any specific attempts to contact the community of local employees, to identify their housing needs, or to consider how the city might better meet those needs.

Residents and local workers alike have not had many opportunities to learn about or engage with the housing element, as Colma does not seem to have held a single housing element-specific meeting. In its outreach section, the draft element describes planning staff participating in a number of events, none of which were specific to the housing element. To date, the city does not appear to have held any housing element workshops to inform the community or to have devoted adequate time to public meetings enabling the community to share feedback with the council.

Site Inventory
● Provide site-by-site analysis of likelihood of development for each site in the inventory, considering guidelines from HCD’s Site Inventory Guidebook. ● Identify concrete policy changes that the city is making that will make development feasible in the site inventory on a site-by-site basis.

With their site inventories, cities demonstrate capacity to accommodate the regional housing needs allocation. In order to demonstrate capacity, cities identify specific sites where they expect housing at various levels of affordability to be built. If more than 50% of the low-income housing is planned to be built on non-vacant sites (i.e. a lot with some pre-existing use), then 10 Draft housing element, p. 11, Table H-7
9 Gov. Code, §§ 65583, subds. (c)(9), (c)(10), 8899.50, subds. (a), (b), (c); see also AFFH Final Rule and Commentary (AFFH Rule), 80 Fed. Reg. 42271, 42292-42302, 42353-42360, esp. 42354-42356 (July 16, 2015)
8 HCD’s Affirmatively Furthering Fair Housing Guidebook, p. 12; Gov. Code, § 65583, subd. (c)(9) “the nonvacant site’s existing use is presumed to impede additional residential development, unless the housing element describes findings based on substantial evidence that the use will likely be discontinued during the planning period.”11 In Colma, more than 50% of the low-income housing is predicted to come from nonvacant sites; in fact, Colma’s entire low-income housing designation relies on just two sites.

Colma provides limited evidence to justify the inclusion of 100% of its low-income housing on non-vacant sites. For the Kohl’s site at 1200 Camino Real, the city claims a realistic capacity of 161 units, 53 of which would be very low-income units (the entirety of the city’s allocation), without presenting any evidence of a track record of similar development occurring or demonstrating that Colma has funding or other policies in place to facilitate such development.

For the vacant site at F Street and Camino Real, Colma uses similarly dubious methodology, also providing no evidence that the city can realistically expect 30 low-income units to be developed at the property. The site inventory also explicitly recognizes that “Rezoning this property to a ‘Planned Development’ land use designation” would remove the constraints that make it unlikely to be developed over the 6th RHNA cycle. But the goals, policies, and programs portion of the housing element does not identify a policy to rezone the F Street and Camino Real site as a Planned Development zone. HLC thinks the city must make a firm commitment in its goals, policies, and programs to rezone the F Street and Camino Real site if it is to be considered as an opportunity site.

At its core, Colma’s site inventory relies on the dubious claim that the rate of housing development in Colma will triple from 75 units in the 5th RHNA cycle to 202 units in the 6th RHNA cycle without any substantive changes to local policies. HLC proposes that Colma implement ambitious new policies to ensure the mandated new housing actually gets built.

Goals, Policies, and Programs
● Implement new goals, policies and programs that substantively change local policies in ways that promote new housing development to meet existing need. ● Remove goals, policies, and programs that have already been implemented from prior cycles. Remove proposals that would erect new constraints to housing development. ● Give policies and programs specific, discrete deadlines for program implementation.

Deadlines for meeting the quantified objectives do not count; the city must make specific commitments to implement the policies that will facilitate accomplishment of the quantified objectives.

The goals, policies, and programs portion of a housing element gives Colma an opportunity to commit to concrete changes that will help the city address unmet housing needs. In a presentation to the 21 Elements consortium, HCD describes common errors jurisdictions across 11 HCD Site Inventory Guidebook, p. 27
California have been making in the draft housing elements they submit: “Programs are status quo, do not support the narrative in the housing element, or do not have specific actions and timelines to demonstrate a beneficial impact in planning period. Lack of clear commitments (e.g., “uses Explore, Consider, Evaluate the feasibility, Study….”) or objectives.”12 In their housing elements, cities are required to implement new programs, and those programs must make clear commitments to change local policies in ways that promote fair housing with specific actions, timelines, and measurable metrics for success.

HLC appreciates the progress Colma has made on implementing an inclusionary housing ordinance, promoting by-right group housing, and enabling the development of the 66-unit veterans projects a few times. Many other policies mentioned in Colma’s housing element represent admirable actions Colma has taken in the past to promote fair housing.

HLC fully supports Colma’s fifth cycle housing element policies, but we think the city needs to distinguish between old policies from the 5th RHNA cycle and new policies for the 6th cycle.

None of Colma’s policies and programs has a concrete timeline: Almost all are “Ongoing,” and a few are “Completed.” Many programs describe local ordinances or actions that were taken years ago. Most of the rest describe rote compliance with state law.

Furthermore, none of Colma’s policies and programs indicate intent to pursue new policies that remove constraints to new housing and actively promote new development. In fact, some of Colma’s policies suggest that the city has not done its due diligence to identify housing needs or the constraints that prevent those needs from being met.

Program 4.6 describes outreach that Colma is legally required to have done through the housing element process: “Reach out to local service providers of special needs groups to assist in the identification and analysis of constraints to the provision of housing for persons with disabilities. Identify unmet needs and – to the degree possible – overcome any constraints, including lack of capacity and available resources.” This isn’t a new program, it’s an admission that Colma has not yet met the prerequisites for a successful housing element.

Colma’s single new policy proposal, Program 3.9, would potentially add a new constraint to housing. Program 3.9 promises to “consider the creation of a funding district or other funding mechanism to assure that the project will pay for Town services.” This program directly contradicts the policy that it supposedly supports, as it describes a new potential cost for large high-density residential uses, not an incentive.13
Given these shortfall, HLC does not comment on Colma’s current goals, policies, and programs, as we believe the city needs to make substantive revisions. Below, we propose a series of new policies that will promote housing production in Colma, protect renters, and foster fair housing throughout the community. In its draft housing element, we propose that Colma distinguish between recycled policies from prior housing elements and new policies. 13 Draft housing element, p. 85
12 HCD presentation, Housing Elements in the 6th Cycle: Common Shortfalls, Slide 5 New Policies to Promote Housing Opportunity
Proposed Measure(s) Policy Text and Justification
Provide extra density bonus
incentives for very low- and
extremely low-income units.

Cities will be more likely to facilitate the
state-mandated ELI units required by RHNA if they
provide extra incentives for developers to build
those units.

Incentivizing Housing in
Commercial Developments
Commit to expanding Colma’s Planned
Development zones to all commercially zoned
properties.

Eliminate Parking Minimums
for Special Needs
Populations
Eliminate parking minimums for housing geared
toward the elderly or developmentally disabled
populations throughout the town. Allow parking
reductions or waivers for all very low- and
extremely low-income housing within 1 mile of a
regional transit stop or transit corridor.

These communities do not drive, so requiring
parking for their dwellings increases cost with no
additional benefit to the residents.

Strengthen Renter
Protections Beyond Those
Required by the Tenant
Protection Act of 2019 (AB
1482)
Colma could do significantly more to protect
tenants beyond the requirements of state law,
including:
- Require just cause for eviction from day
one of occupancy
- Allow compensated relocation option for all
“no-fault” evictions
- Allow right of first return for all evictions
related to redevelopment
Fair Housing Throughout the
Community
Commission an EIR to study the environmental
impacts of upzoning to allow the mullin density (30
du/ac in Foster City) in all neighborhoods located
within 0.5 miles of transit.

Missing Middle Housing Conditional upon an EIR finding such upzoning to pose no threat to public health and safety, upzone
all residential zones within 0.5 miles of BART to
allow commercial development and densities of at
least 30 du/ac.

Expand Sources of Funds for
the City Affordable Housing
Fund.

HLC supports Colma’s plans to use preexisting city
revenue to subsidize affordable housing, especially
because of Colma’s large tax base. In order to
raise reliable revenue, however, the city may
benefit from an internal revenue-raising proposal,
such as:
1) Vacancy Tax - Parcel taxes in the
form of a vacant property tax have
been used by cities (VPT, Oakland)
to fund affordable housing and
homeless services; as well as to
entice owners of undeveloped sites
to either sell or build homes on their
parcels.
2) Transfer Tax - A one-time tax
payment that is levied by a
government on the transfer of
ownership to property (i.e. sale of a
home) from one individual or entity
School Sites/Religious and
Nonprofit-Owned Sites
Implement an overlay zone allowing higher
densities, parking minimum waivers, and looser
objective standards for affordable housing on
school-, religious-, and nonprofit-owned sites
regardless of other zoning standards. Allowing
denser affordable housing on these types of sites
can often help these organizations better fulfill their missions by providing more housing to those they
serve.

Rental Registry Create a rental registry listing all properties available for rent in the city, especially affordable
rentals.

Facilities and Services for
Special Needs
Provide expedited permit review or by-right
approvals for housing projects that include facilities
that address special needs populations, including
but not limited to the physically and mentally
disabled, large families, and extremely low-income
households.

Fee Exemptions for 100%
Affordable Housing Projects
According to the 21 Elements Fee Survey
jurisdictions charge fees ranging from
$6,824-$167,210 per unit in multifamily housing.

These additional fees can make many affordable
housing projects, which rely on public subsidy,
infeasible. Waiving or lowering fees for 100%
affordable housing projects can promote the
production of more affordable housing across a
spectrum of income levels.

Upon completing further outreach with stakeholders, HLC recommends that Colma implement additional goals, policies, and programs informed by the feedback received by the city. 1 Alvin Jen
From: Alvin Jen
Sent: Thursday, January 12, 2023 8:16 AM
To: Mollahan, Ben @ San Jose; [email protected]
Cc: Farhad Mortazavi
Subject: RE: Housing Element Inventory sites 2023-2031
Good morning Ben,

Thank you for reaching out to us. We are not proposing any rezoning on the parcels that we have identified in our site inventory. On page H-73, you can find a table for the sites along or near El Camino Real corridor regarding multifamily residential projects. If there are additional questions, please feel free to reach out to us.

Best,

Alvin Jen
Associate Planner, CSG Consultants

Town of Colma
Planning Department
1198 El Camino Real, Colma, CA 94014
www.colma.ca.gov
[email protected]
650.757.8888 main
650.997.8314 direct
650.757.8890 fax

From: Mollahan, Ben @ San Jose <[email protected]>
Sent: Wednesday, January 11, 2023 10:52 PM
To: [email protected]
Subject: Housing Element Inventory sites 2023-2031

Hi all,

My name is Ben Mollahan with CBRE capital markets. After reviewing your cities 2023-2031 Housing Element Draft, we noticed there is not a list of site inventory for potential conversions. Can you please provide an excel list or something similar to that below that San Carlos has?

Our clients want to help the city and this will be the first stepping stone to doing so. 2 Thank you,
Ben

Ben Mollahan
Associate | Lic. 02136790
CBRE Capital Markets | Multifamily Properties
2 25 W. Santa Clara Street, 12th Floor | San Jose, CA 95113 C +1 925 330 3642
[email protected] | www.cbre.com

Details about the personal data CBRE collects and why, as w ell as your data privacy rights under applicable law, are available at CBRE – Privacy Policy.
1 Alvin Jen
From: Alvin Jen
Sent: Wednesday, January 11, 2023 9:44 AM
To: Susy Kalkin
Cc: Farhad Mortazavi
Subject: RE: Housing Element - ALCU Review
Hi Suzy,

We anticipate these two parcels developing at approximately 55’ with density bonuses.

Thanks,

Alvin Jen
Associate Planner, CSG Consultants

Town of Colma
Planning Department
1198 El Camino Real, Colma, CA 94014
www.colma.ca.gov
[email protected]
650.757.8888 main
650.997.8314 direct
650.757.8890 fax

From: Susy Kalkin <[email protected]>
Sent: Monday, January 9, 2023 8:48 AM
To: Alvin Jen <[email protected]>
Cc: Farhad Mortazavi <[email protected]>
Subject: RE: Housing Element - ALCU Review

Hi Alvin,
Thanks for the info. Just wanted to check back on the 7733 & 7778 ECR sites - is there any outside maximum height limit
with density bonuses?
Thanks,
Susy

From: Alvin Jen <[email protected]>
Sent: Friday, January 6, 2023 4:48 PM
To: Susy Kalkin <[email protected]>
Cc: Farhad Mortazavi <[email protected]>
Subject: RE: Housing Element - ALCU Review

CAUTION: This email originated from outside of San Mateo County. Unless you recognize the sender's email address and know the content is safe, do not click links, open attachments or reply.

Hi Susy,

2 No changes to the opportunity sites. Current residential standards for R-S zone is 27’ (this applies to the parcel on B Street), R zone is 36’ and C zone is 36’. For the Kohl’s site we kept it consistent as up to 72’ which is defined in our 2040 General Plan (adopted March 2022). The other sites 7733 and 7778 El Camino Real may be higher if the developer utilizes density bonuses due to proximity near the Colma BART station.

Please reach out if there are more questions that I can help answer.

Best,

Alvin Jen
Associate Planner, CSG Consultants

Town of Colma
Planning Department
1198 El Camino Real, Colma, CA 94014
www.colma.ca.gov
[email protected]
650.757.8888 main
650.997.8314 direct
650.757.8890 fax

From: Susy Kalkin <[email protected]>
Sent: Friday, January 6, 2023 4:27 PM
To: Alvin Jen <[email protected]>
Subject: RE: Housing Element - ALCU Review

Hi Alvin,
Thanks for this. Can I assume there were no changes to the opportunity sites? I also have a question for you – what is the maximum height that could be possible on any of the opportunity sites?– I can’t imagine it could create a concern, but just need the info for the staff report.

Thanks,
Susy

From: Alvin Jen <[email protected]>
Sent: Thursday, January 5, 2023 5:41 PM
To: Susy Kalkin <[email protected]>
Subject: RE: Housing Element - ALCU Review

CAUTION: This email originated from outside of San Mateo County. Unless you recognize the sender's email address and know the content is safe, do not click links, open attachments or reply.

Hi Suzy,

Happy New Year! I wanted to provide some updates regarding the Town of Colma’s progress on the Housing Element.

There weren’t many changes from this draft and the draft sent to you on 12/21/22, just formatting and minor edits.

• In compliance with AB 215, we are notifying you that we have revised the Housing Element, and it has been posted on the Town’s website, https://www.colma.ca.gov/housing-element/ • “Housing Element Draft Public Review – January 2023” and “Appendix B Colma Fair Housing Assessment January 2023)” are the latest versions.
3 • The changes are reflected with “redlines” edits left on. • The original version of the Draft and associated appendices were sent to HCD in June and are located here:
https://www.colma.ca.gov/previous-housing-element-dr afts/ • HCD provided their official comment letter to the Town on September 14, 2022. The comment letter is on the Housing Element webpage.
• On January 11, 2023, there will be a public hearing where the latest draft will be considered by City Council for adoption. Details on that meeting can be found here: https://www.colma.ca.gov/city-council-meetings/

Any comments regarding the Housing Element can be sent to me at [email protected].

If there are any further questions, please do not hesitate to reach out.

Thanks,

Alvin Jen
Associate Planner, CSG Consultants

Town of Colma
Planning Department
1198 El Camino Real, Colma, CA 94014
www.colma.ca.gov
[email protected]
650.757.8888 main
650.997.8314 direct
650.757.8890 fax

From: Susy Kalkin <[email protected]>
Sent: Wednesday, December 21, 2022 11:43 AM
To: Alvin Jen <[email protected]>
Subject: RE: Housing Element - ALCU Review

Hi Alvin,

Is there any need for the ALUC to review the redline version separate from the clean copy?

Susy

From: Alvin Jen <[email protected]>
Sent: Wednesday, December 21, 2022 9:15 AM
To: Susy Kalkin <[email protected]>
Cc: Farhad Mortazavi <[email protected]>
Subject: RE: Housing Element - ALCU Review

CAUTION: This email originated from outside of San Mateo County. Unless you recognize the sender's email address and know the content is safe, do not click links, open attachments or reply.

Hi Suzy,

I’ve attached 3 documents: C/CAG’s application, the Draft Housing Element with no redlines, the Draft Housing Element with redlines.

4 If there are any questions, please feel free to reach out to me.

Thanks,

Alvin Jen
Associate Planner, CSG Consultants

Town of Colma
Planning Department
1198 El Camino Real, Colma, CA 94014
www.colma.ca.gov
[email protected]
650.757.8888 main
650.997.8314 direct
650.757.8890 fax

Town Hall will be closed for the holidays beginning midday, December 21, 2022 to January 2, 2023

From: Susy Kalkin <[email protected]>
Sent: Wednesday, December 21, 2022 9:01 AM
To: Alvin Jen <[email protected]>
Cc: Farhad Mortazavi <[email protected]>
Subject: Re: Housing Element - ALCU Review

Hi Alvin,
Please send it to me.

Thanks,
Susy
From: Alvin Jen <[email protected]>
Sent: Wednesday, December 21, 2022 8:56 AM
To: Susy Kalkin <[email protected]>
Cc: Farhad Mortazavi <[email protected]>
Subject: Housing Element - ALCU Review

CAUTION: This email originated from outside of San Mateo County. Unless you recognize the sender's email address and know the content is safe, do not click links, open attachments or reply.

Hi Suzy,

The Town of Colma would like to submit its Housing Element for ALCU’s review. Do you have a best contact for us to submit the Application for Land Use Consistency Determination and our Housing Element Draft.

Best,
Alvin Jen
Associate Planner, CSG Consultants

5 Town of Colma
Planning Department
1198 El Camino Real, Colma, CA 94014
www.colma.ca.gov
[email protected]
650.757.8888 main
650.997.8314 direct
650.757.8890 fax

Town Hall will be closed for the holidays beginning midday, December 21, 2022 to January 2, 2023

1 Alvin Jen
From: Alvin Jen
Sent: Wednesday, January 11, 2023 9:44 AM
To: Susy Kalkin
Cc: Farhad Mortazavi
Subject: RE: Housing Element - ALCU Review
Hi Suzy,

We anticipate these two parcels developing at approximately 55’ with density bonuses.

Thanks,

Alvin Jen
Associate Planner, CSG Consultants

Town of Colma
Planning Department
1198 El Camino Real, Colma, CA 94014
www.colma.ca.gov
[email protected]
650.757.8888 main
650.997.8314 direct
650.757.8890 fax

From: Susy Kalkin <[email protected]>
Sent: Monday, January 9, 2023 8:48 AM
To: Alvin Jen <[email protected]>
Cc: Farhad Mortazavi <[email protected]>
Subject: RE: Housing Element - ALCU Review

Hi Alvin,
Thanks for the info. Just wanted to check back on the 7733 & 7778 ECR sites - is there any outside maximum height limit
with density bonuses?
Thanks,
Susy

From: Alvin Jen <[email protected]>
Sent: Friday, January 6, 2023 4:48 PM
To: Susy Kalkin <[email protected]>
Cc: Farhad Mortazavi <[email protected]>
Subject: RE: Housing Element - ALCU Review

CAUTION: This email originated from outside of San Mateo County. Unless you recognize the sender's email address and know the content is safe, do not click links, open attachments or reply.

Hi Susy,

Please reach out if there are more questions that I can help answer.

Best,

Alvin Jen
Associate Planner, CSG Consultants

Town of Colma
Planning Department
1198 El Camino Real, Colma, CA 94014
www.colma.ca.gov
[email protected]
650.757.8888 main
650.997.8314 direct
650.757.8890 fax

From: Susy Kalkin <[email protected]>
Sent: Friday, January 6, 2023 4:27 PM
To: Alvin Jen <[email protected]>
Subject: RE: Housing Element - ALCU Review

Thanks,
Susy

From: Alvin Jen <[email protected]>
Sent: Thursday, January 5, 2023 5:41 PM
To: Susy Kalkin <[email protected]>
Subject: RE: Housing Element - ALCU Review

CAUTION: This email originated from outside of San Mateo County. Unless you recognize the sender's email address and know the content is safe, do not click links, open attachments or reply.

Hi Suzy,

Happy New Year! I wanted to provide some updates regarding the Town of Colma’s progress on the Housing Element.

There weren’t many changes from this draft and the draft sent to you on 12/21/22, just formatting and minor edits.

Any comments regarding the Housing Element can be sent to me at [email protected].

If there are any further questions, please do not hesitate to reach out.

Thanks,

Alvin Jen
Associate Planner, CSG Consultants

Town of Colma
Planning Department
1198 El Camino Real, Colma, CA 94014
www.colma.ca.gov
[email protected]
650.757.8888 main
650.997.8314 direct
650.757.8890 fax

From: Susy Kalkin <[email protected]>
Sent: Wednesday, December 21, 2022 11:43 AM
To: Alvin Jen <[email protected]>
Subject: RE: Housing Element - ALCU Review

Hi Alvin,

Is there any need for the ALUC to review the redline version separate from the clean copy?

Susy

From: Alvin Jen <[email protected]>
Sent: Wednesday, December 21, 2022 9:15 AM
To: Susy Kalkin <[email protected]>
Cc: Farhad Mortazavi <[email protected]>
Subject: RE: Housing Element - ALCU Review

CAUTION: This email originated from outside of San Mateo County. Unless you recognize the sender's email address and know the content is safe, do not click links, open attachments or reply.

Hi Suzy,

I’ve attached 3 documents: C/CAG’s application, the Draft Housing Element with no redlines, the Draft Housing Element with redlines.

4 If there are any questions, please feel free to reach out to me.

Thanks,

Alvin Jen
Associate Planner, CSG Consultants

Town of Colma
Planning Department
1198 El Camino Real, Colma, CA 94014
www.colma.ca.gov
[email protected]
650.757.8888 main
650.997.8314 direct
650.757.8890 fax

Town Hall will be closed for the holidays beginning midday, December 21, 2022 to January 2, 2023

From: Susy Kalkin <[email protected]>
Sent: Wednesday, December 21, 2022 9:01 AM
To: Alvin Jen <[email protected]>
Cc: Farhad Mortazavi <[email protected]>
Subject: Re: Housing Element - ALCU Review

Hi Alvin,
Please send it to me.

CAUTION: This email originated from outside of San Mateo County. Unless you recognize the sender's email address and know the content is safe, do not click links, open attachments or reply.

Hi Suzy,

Best,
Alvin Jen
Associate Planner, CSG Consultants

5 Town of Colma
Planning Department
1198 El Camino Real, Colma, CA 94014
www.colma.ca.gov
[email protected]
650.757.8888 main
650.997.8314 direct
650.757.8890 fax

Town Hall will be closed for the holidays beginning midday, December 21, 2022 to January 2, 2023

Staff Report – 2022-23 Capital Program Update Page 1 of 5

STAFF REPORT
T
O: Mayor and Members of the City Council
FROM: Pak Lin, Administrative Services Director
Brad Donohue, Director of Public Works
VIA: Brian Dossey, City Manager
MEETING DATE: January 25, 2023
SUBJECT: 2022-2023 Capital Program Update

RECOMMENDATION
Staff recommends that the City Council adopt the following resolutions approving:

RESOLUTION AMENDING THE FISCAL YEAR 2022-23 CAPITAL IMPROVEMENT BUDGET TO $14,279,680, INCLUDING ADDING FOUR NEW PROJECTS, CLOSING OUT ONE CAPITAL PROJECT; CARRYING OVER $531,496 OF UNSPENT PROJECT BUDGET TO FY 2022-23; TRANSFERRING $1,431,828 FROM GENERAL FUND (11) TO STREET CIP FUND (32); AND, RELEASING UNSPENT FUNDING OF $82,275 TO CAPITAL RESERVE, AND $3,220 TO FLEET REPLACEMENT FUND, PURSUANT TO CEQA GUIDELINE 15378.

EXECUTIVE SUMMARY
The Town conducts periodic reviews of its operating budget and its capital program. A periodic review provides transparency and accountability. Attachment B of this report summaries 20 actively funded Capital projects in FY 20 22-23. The report contains a brief description of each capital project, the status each project as of December 31, 2022, and the corresponding financial information.

The FY 2021-22 Capital Program included a total project budget of $4.02 million, spent $3.40 million, and resulting in an available project budget of $616,991. Many of the projects in the capital program are multi -years and unspent portion s of the budget is car ried-over until the project is completed. Of the $616,991 of available project budget funds, $531,496 needs to carry over and $85,495 can be released back to the corresponding reserve fund balances.

Adding the FY 2022-23 additional investment of $4.72 million and the additional request of $9.03 million, the total FY 2022 -23 capital program is $14. 28 million. The additional request includes four new projects that has State and County grant funds. The Town’s responsibility is $1.48 million and will require a General Fund transfer of $1.43 million.

Item #7
Staff Report – 2022-23 Capital Program Update Page 2 of 5

FISCAL IMPACT
Increase the FY 202 2-23 Capital Program Budget to $14, 279,680, which includes $531 ,496 of carryover funds from FY 2021 -22, $ 1,431,828 of General Fund Transfer, and $7,551,500 of various State and Local grants.

The Town will also release $84,167 of unused project funding to various fund reserves.

BACKGROUND
Annually, after the fiscal year is closed, the Town reviews its capital program to identify and summarize project budget carryover and funding release of completed projects. The Adopted FY 2022-23 Capital Program totaled $8.74 million, with $4.02 million from prior years funding and $4.72 million in new capital investments.

ANALYSIS
As shown in Table 2, below, the FY 2021-22 Capital Program has an available balance of $616,991 by June 30, 2022, of which, $531,496 is needed to be carried over to FY 2022-23.

Category 1: Streets, Sidewalks, and Bikeways
Annual Roadway Rehabilitation and Preventive Maintenance Program (906) 150,000$ 292,900$ 442,900$ El Camino Real Bicycle and Pedestrian Improvement (923) - 2,000,000 2,000,000 F-Street Retaining Wall (902) 47,000 400,000 447,000 Mission Road Bicycle and Pedestrian Improvement Project (903) 2,860,000 - 2,860,000 Mission Road Landscaping (908) 29,000 343,200 372,200 Mission Road Crosswalk (909) 11,000 119,009 130,009 Town-Wide Bicycle and Pedestrian Master Plan (910) - 100,000 100,000 Category 2: Sewers & Storm Drains
Storm Drain System Assessment and Mapping (972) - 70,000 70,000 Category 3: City Facilities & Long-Range Plans
Colma Museum Facility Repair & Painting (951) 75,000 - 75,000 Facility Parking Lot Upgrades (953) 99,025 140,975 240,000 Housing Element Update (996) 100,000 110,000 210,000 Public Arts Program (980) - 15,000 15,000 Town-Wide Branding (959) - 100,000 100,000 Urban Tree Master Plan& Improvement (998) - 100,000 100,000 Zoning Code Update (997) 100,000 80,000 180,000 Category 4: Major Equipment, Technology & Fleet
Equipment Purchase and Replacement (984) 233,339 150,000 383,339 Financial Software Replacement (965) 100,000 430,000 530,000 IT Infrastructure Upgrades (986) 50,000 50,000 100,000 Vehicle Replacement (987) 164,000 220,000 384,000 Total 4,018,364$ 4,721,084$ 8,739,448$
Total
Capital Program
[a] + [b]
Table 1
FY 2022/23 Capital Program Update
Project Title (Number)
Project Budget
Thru 6/30/2022
[a]
FY 2022-23
Investment
[b]
Staff Report – 2022-23 Capital Program Update Page 3 of 5

Unlike the operating budget, the capital programs budget is for the life of the project and not reset at the end of each fiscal year. The summary above and the carryover budget request in the resolution is administrative in nature and aids in the year-end audit process.

The FY 2022-23 Investment (Column [d]) accounts for the Council adopted capital budget in June and subsequent budget amendments from July 1, 2022 through December 31, 2022. The table also includes four new projects and a budget amendment request for the Annual Roadway Rehabilitation Program in the amount of $27,100.

Additional Request (Budget Amendments)
• Annual Roadway Rehabilitation and Preventative Maintenance Program (906).

The FY 2022 -23 roadway improvement project involves slurry seal at Hillside and Lawndale. This project is to piggyback off the South San Francisco roadway improvement project in that v icinity. Through preliminary assessment of the construction cost s, staff realized that the project will cost around $320,000 to cover the cost of construction, construction management, and contingency. Staff is recommending to use a portion of the unused project budget to fund this project.
• El Camino Real Segment B Design (915). This is a new capital project. The details of the project can be found in Attachment C. The design of El Camino Real Segment B project includes grant funding of $603,000 and a required local match of $67,000. The local match of $67,000 needs to be funded through General Fund.

Additional
Request @
12/31/2022
[d] Fund No Amount
Category 1: Streets, Sidewalks, and Bikeways
Annual Roadway Rehabilitation and
Preventive Maintenance Program (906) 150,000$ 0$ 150,000$ 150,000$ 292,900$ 27,100$ 470,000$ Fund 32 (27,100)$ El Camino Real Bicycle and Pedestrian
Improvement (923) 0$ 0$ 0$ 0$ 2,000,000$ 2,000,000$ El Camino Real Segment B Design (915) 0$ 0$ 0$ 0$ 0$ 670,000$ 670,000$ El Camino Real Segment B Construction
Project (916) 0$ 0$ 0$ 0$ 0$ 5,800,000$ 5,800,000$ El Camino Real & Mission Rd Access to
Transient Multimodal Crossing Improvement
(904) 0$ 0$ 0$ 0$ 0$ 180,000$ 180,000$ Fund 32 (16,672)$ Serramonte Blvd West Phase 1 Project (911) 0$ 0$ 0$ 0$ 0$ 2,350,000$ 2,350,000$ F-Street Retaining Wall (902) 47,000$ 40,542$ 6,458$ 6,458$ 400,000$ 406,458$ Mission Road Bicycle and Pedestrian
Improvement Project (903) 2,860,000$ 2,860,000$ 0$ 0$ 0$ 0$ Fund 32 43,772$ Mission Road Landscaping (908) 29,000$ 21,420$ 7,580$ 7,580$ 343,200$ 350,780$ Mission Road Crosswalk (909) 11,000$ 0$ 11,000$ 11,000$ 119,009$ 130,009$ Town-Wide Bicycle and Pedestrian Master
Plan (910) 0$ 0$ 0$ 0$ 100,000$ 100,000$ Category 2: Sewers & Storm Drains
Storm Drain System Assessment and Mapping
(972) 0$ 0$ 0$ 0$ 70,000$ 70,000$ Category 3: City Facilities & Long-Range Plans
Colma Museum Facility Repair & Painting (951) 75,000$ 11,245$ 63,755$ 63,755$ 0$ 63,755$ Facility Parking Lot Upgrades (953) 99,025$ 0$ 99,025$ 99,025$ 140,975$ 240,000$ Housing Element Update (996) 100,000$ 84,351$ 15,649$ 15,649$ 110,000$ 125,649$ Public Arts Program (980) 0$ 0$ 0$ 0$ 15,000$ 15,000$ Town-Wide Branding (959) 0$ 0$ 0$ 0$ 100,000$ 100,000$ Urban Tree Master Plan& Improvement (998) 0$ 0$ 0$ 0$ 100,000$ 100,000$ Zoning Code Update (997) 100,000$ 21,971$ 78,029$ 78,029$ 80,000$ 158,029$ Category 4: Major Equipment, Technology & Fleet
Equipment Purchase and Replacement (984) 233,339$ 160,720$ 72,619$ (0)$ 150,000$ 150,000$ Fund 31 72,619$ Financial Software Replacement (965) 100,000$ 0$ 100,000$ 100,000$ 430,000$ 530,000$ IT Infrastructure Upgrades (986) 50,000$ 40,344$ 9,656$ (0)$ 50,000$ 50,000$ Fund 31 9,656$ Vehicle Replacement (987) 164,000$ 160,780$ 3,220$ 0$ 220,000$ 220,000$ Fund 61 3,220$ Total 4,018,364 3,401,373 616,991 531,496 4,721,084 9,027,100 14,279,680 85,495 Table 2
FY 2022/23 Capital Program Update
Project Title (Number)
Fund Release
Project Budget
Thru 6/30/2022
[a]
Spending Thru
6/30/2022
[b]
Unspent
Project Budget
at 7/1/2022
[a] - [b]
Project Budget
Carryover to
7/1/2022
[c]
FY 2022-23
Investment
[d]
Available
Project
Budget
in FY22/23
[c] + Σ[d]
Staff Report – 2022-23 Capital Program Update Page 4 of 5 • El Camino Real Segment B Construction (916) . This is a new capital project with grant funding of $4.64 million. A local match of $1.16 million is required to be funded through General Fund Transfer. See Attachment D for more information on this project. • El Camino Real & Mission Rd Access to Transient Multimodal Crossing Improvement (904). This is a new project , and the project description is available as Attachment E. The total project budget is $180,000 with $162,000 in grant funding and $18,000 in local match. Staff is recommending using a portion of the unused project budget to fund the local match.
• Serramonte Blvd West Phase 1 Project (911) . This is a new project with a project budget of $2.35 million. As described in Attachment F, the Town submitted the grant application in September 2022. The grant award is $1.83 million, and the local match is $203,500.

Closed Projects
• Mission Road Bicycle and Pede strian Project was completed in July 2021 and can be closed. The Town received $43,772 in extra grant fundings, allowing the Town to reallocate the funds to Annual Roadway Rehab (906) - $27,100 and ECR/Mission Rd Project (904) - $16,672.
• The Equipment Purchase and Replacement (984) , IT Infrastructure Upgrades (986) and the Vehicle Replacement (987) programs are ongoing in nature. The FY 2021-22 program year project can be closed and the available fundings can be released back to its corresponding reserve balances or to offset part of the additional requests.

Fund Release Summary
Total funds to be released back to the various reserve balances is $85 ,495 with the following amounts:

Fund 31 – Capital reserve $82,275
Fund 61 – Fleet Replacement reserve $3,220
Total $85,495

General Fund Transfers
As discussed above, three of the four new projects wi th grant funding requires General Fund support.

Project Name
Grant
Funding
General Fund
Transfer
Other Local
Match
Total Project
Cost
El Camino Real Segment B Design (915) $ 603,000 $ 67,000 $ 670,000 El Camino Real Segment B Construction Project
(916) $ 4,640,000 $ 1,160,000 $ 5,800,000 El Camino Real & Mission Rd Access to Transient
Multimodal Crossing Improvement (904) $ 162,000 $ 1,328 $ 16,672 $ 180,000 Staff Report – 2022-23 Capital Program Update Page 5 of 5 Serramonte Blvd West Phase 1 Project (911) $ 2,146,500 $ 203,500 $ 2,350,000 Total General Fund Transfer $ 7,551,500 $ 1,431,828 $ 16,672 $ 9,000,000 St
aff is anticipating a General Fund surplus of $1.7 million in FY 2021- 22, which can be entirely transferred to the Capital Program to support the local match requirements listed above and other grant funded projects currently under review. The final FY 2021-22 General Fund surplus will be presented as part of the annual audit report and the transfers can be considered at that time.

In addition to the FY 2021-22 General Fund surplus, staff will research other local match grants to reduce the burden on the Town’s General Fund.

Reasons For the Recommended Action/Findings
Staff recommends the City Council adopt the resolution amending the FY 2021-22 Capital Improvement Program Budget to be $14,279 ,680 as listed in Table 2 above. This approval includes:

1. Carry over of $531,496 from FY 2021-22 to FY 2022-23; 2 . Increase Annual Roadway Rehabilitation and Preventative Maintenance Program by $27,100;

3. Add the four new projects listed under “Additional Request” above, totaling $9.0 million;

4. Transfer $43,772 of available project fundings to offset the additional requests for Annual Roadway Rehab and ECR/Mission Rd projects.

5. Transfer $1.43 million from the General Fund (11) to Street Capital Fund (32) with the creation of the four new projects

6. Release $85,495 of available unused funds with $82,275 to Capital reserve Fund 31 and $3,220 to Fleet Replacement Fund 61.

C
ouncil Adopted Values
P
eriodic review of the Capital Program is an exercise of government transparency, fiscal accountability, and thoughtfulness in the use of public funds. Periodic review provides a brief project scope and progress update, project budget and spending summary, and explanation for budget amendments and project delays. It allows the City Council to thoughtfully decide and direct staff whether to continue the current course or to shift priorities.

NCLUSION
Overall, the Town’s capital program stayed within program budget.

ATTACHMENTS
A. Resolution
B. Capital Program Status Through December 31, 2022
C. ECR Segment B Design Project
D. ECR & Mission Signalization Design Project
E. ECR Segment B Construction Project
F. Serramonte Blvd West Phase I Project

Res 2023-##, 2022-23 Capital Program Update Page 1 of 3 RESOLUTION NO. 2023-##

OF THE CITY COUNCIL OF THE TOWN OF COLMA
RES
OLUTION AMENDING THE FISCAL YEAR 2022-23 CAPITAL IMPROVEMENT BUDGET TO $14,279,680, INCLUDING ADDING FOUR NEW PROJECTS, CLOSING OUT ONE CAPITAL PROJECT; CARRYING OVER $531,496 OF UNSPENT PROJECT BUDGET TO FY 2022-23; TRANSFERRING $1,431,828 FROM GENERAL FUND (11) TO STREET CIP FUND (32); AND, RELEASING UNSPENT FUNDING OF $82,275 TO CAPITAL RESERVE, AND $3,220 TO FLEET REPLACEMENT FUND, PURSUANT TO CEQA GUIDELINE 15378.

The City Council of the Town of Colma does resolve as follows.

1. Background
(a) On June 8, 2022, the City Council approved and adopted the FY 2022-23 Budget which consists of FY 2022-23 operating budget appropriations and the FY 2022-23 capital improvement; (b) The Adopted FY 2022 -23 Capital Program totaled $8.74 million, with $4.02 million from prior years funding and $4.72 million in new capital investments; (c) The FY 2021 -22 Capital Program had an available balance as of June 30, 2022 of $616,991, of which $531,496 is requested to be carried over to FY 2022-23, $82,275 is requested to be released and returned to Capital reserve, and $3,220 is requested to be released and returned to Fleet Replacement;
(d) Mission Road Bicycle and Pedestrian Improvement Project (903) is complete and the available fund of $43,772 is requested to be reallocated to Annual Roadway Rehab Project ($27,100) and the El Camino Real & Mission Road Access Project ($16,672); (e) In review of the FY 2022- 23 Capital Program, Staff found that that Annual Roadway Rehabilitation and Preventative Maintenance Program budget needs to be increased by $27,100 to $442,900 and the following four new projects need to be added to the capital program Project Name Grant
Funding Local Match Total Project
Cost
El Camino Real Segment B Design (915) $ 603,000 $ 67,000 $ 670,000 El Camino Real Segment B Construction
Project (916) $ 4,640,000 $ 1, 160,000 $ 5,800,000 El Camino Real & Mission Rd Access to
Transient Multimodal Crossing
Improvement (904)
$ 162,000 $ 18,000 $ 180,000
Serramonte Blvd West Phase 1 Project
(911) $ 2,146,500 $ 2 03,500 $ 2,350,000
(f) St
aff is also requesting t ransfer of $1,431,828 from General Fund (11) to Street Capital Fund (32) to fund the Local Match;
(g) The City Council duly considered the proposed budget amendments and public comments, Attachment A
Res 2023-##, 2022-23 Capital Program Update Page 2 of 3 if any, thereon.

2. Findings and Order.

The City Council hereby approves and orders the following changes:
(a) Summary of New FY 202 2-23 Capital Program Budget . Table 1 titled “2022/23 Capital Program Update” shall be and is hereby approved as the new FY 2022-23 Capital Program Budget.

(b) Summary of Project Closeout. Table 2, columns titled “Fund Release” below, summarizes project budgets to be closed and the amount to be released to various funds , including the reallocation of $43,772 from Mission Road Bicycle and Pedestrian project (903) to Annual Roadway Rehab (906) and El Camino Real/Mission Road Access (904) projects.

Additional
Request @
12/31/2022
[d]
Category 1: Streets, Sidewalks, and Bikeways
Annual Roadway Rehabilitation and
Preventive Maintenance Program (906) 150,000$ 0$ 150,000$ 150,000$ 292,900$ 27,100$ 442,900$ El Camino Real Bicycle and Pedestrian
Improvement (923) 0$ 0$ 0$ 0$ 2,000,000$ 2,000,000$ El Camino Real Segment B Design (915) 0$ 0$ 0$ 0$ 0$ 670,000$ 670,000$ El Camino Real Segment B Construction
Project (916) 0$ 0$ 0$ 0$ 0$ 5,800,000$ 5,800,000$ El Camino Real & Mission Rd Access to
Transient Multimodal Crossing Improvement
(904) 0$ 0$ 0$ 0$ 0$ 180,000$ 180,000$ Serramonte Blvd West Phase 1 Project (911) 0$ 0$ 0$ 0$ 0$ 2,350,000$ 2,350,000$ F-Street Retaining Wall (902) 47,000$ 40,542$ 6,458$ 6,458$ 400,000$ 406,458$ Mission Road Bicycle and Pedestrian
Improvement Project (903) 2,860,000$ 2,860,000$ 0$ 0$ 0$ 0$ Mission Road Landscaping (908) 29,000$ 21,420$ 7,580$ 7,580$ 343,200$ 350,780$ Mission Road Crosswalk (909) 11,000$ 0$ 11,000$ 11,000$ 119,009$ 130,009$ Town-Wide Bicycle and Pedestrian Master
Plan (910) 0$ 0$ 0$ 0$ 100,000$ 100,000$ Category 2: Sewers & Storm Drains
Storm Drain System Assessment and Mapping
(972) 0$ 0$ 0$ 0$ 70,000$ 70,000$ Category 3: City Facilities & Long-Range Plans
Colma Museum Facility Repair & Painting (951) 75,000$ 11,245$ 63,755$ 63,755$ 0$ 63,755$ Facility Parking Lot Upgrades (953) 99,025$ 0$ 99,025$ 99,025$ 140,975$ 240,000$ Housing Element Update (996) 100,000$ 84,351$ 15,649$ 15,649$ 110,000$ 125,649$ Public Arts Program (980) 0$ 0$ 0$ 0$ 15,000$ 15,000$ Town-Wide Branding (959) 0$ 0$ 0$ 0$ 100,000$ 100,000$ Urban Tree Master Plan& Improvement (998) 0$ 0$ 0$ 0$ 100,000$ 100,000$ Zoning Code Update (997) 100,000$ 21,971$ 78,029$ 78,029$ 80,000$ 158,029$ Category 4: Major Equipment, Technology & Fleet
Equipment Purchase and Replacement (984) 233,339$ 160,720$ 72,619$ (0)$ 150,000$ 150,000$ Financial Software Replacement (965) 100,000$ 0$ 100,000$ 100,000$ 430,000$ 530,000$ IT Infrastructure Upgrades (986) 50,000$ 40,344$ 9,656$ (0)$ 50,000$ 50,000$ Vehicle Replacement (987) 164,000$ 160,780$ 3,220$ 0$ 220,000$ 220,000$ Total 4,018,364 3,401,373 616,991 504,396 4,721,084 8,983,328 14,208,808 Table 1
FY 2022/23 Capital Program Update
Project Title (Number)
Project Budget
Thru 6/30/2022
[a]
Spending Thru
6/30/2022
[b]
Unspent
Project Budget
at 7/1/2022
[a] - [b]
Project Budget
Carryover to
7/1/2022
[c]
FY 2022-23
Investment
[d]
Available
Project
Budget
in FY22/23
[c] + Σ[d]
Res 2023-##, 2022-23 Capital Program Update Page 3 of 3 (
c) Drawdown on Reserve . The Annual Roadway Rehabilitation and Mission Road Improvement projects require a transfer of $1,431,828 from the General Fund (11) to Street Capital Fund (32). The City Council hereby orders and approves the drawdown on reserve and approves this change to amend the Fiscal Year 2022-2023 Capital Improvement Budget.

Certification of Adoption
I certify that the foregoing Resolution No. 2023-## was duly adopted at a regular meeting of the City Council of the Town of Colma held on January 25, 2023, by the following vote:

N
ame Voting Present, Not Voting Absent
Aye No Abstain Not Participating
Joanne F. del Rosario, Mayor
John Irish Goodwin
Helen Fisicaro
Ken Gonzalez
Carrie Slaughter
Voting Tally
D
ated: ____________________ _____________________________________ Joanne F. del Rosario, Mayor
At
test: ____________________________
Caitlin Corley, City Clerk
Additional
Request @
12/31/2022
[d
] Fund No Amount
Category 1: Streets, Sidewalks, and Bikeways
Annual Roadway Rehabilitation and
Preventive Maintenance Program (906) 150,000$ 0$ 150,000$ 0$ 292,900$ 27,100$ 442,900$ Fund 32 (27,100)$ El Camino Real & Mission Rd Access to
Transient Multimodal Crossing Improvement
(
904) 0$ 0$ 0$ 0$ 0$ 180,000$ 180,000$ Fund 32 (16,672)$ Mission Road Bicycle and Pedestrian
Improvement Project (903) 2,860,000$ 2, 860,000$ 0$ 0$ 0$ 0$ Fund 32 43,772$ Category 2: Sewers & Storm Drains
None 0$ 0$ 0$ 0$ 0$ 0$
Category 3: City Facilities & Long-Range Plans
None 0$ 0$ 0$ 0$ 0$ 0$
Category 4: Major Equipment, Technology & Fleet
Equipment Purchase and Replacement (984) 233,339$ 160,720$ 72,619$ (0)$ 150,000$ 150,000$ Fund 31 72,619$ IT Infrastructure Upgrades (986) 50,000$ 40,344$ 9,656$ (0)$ 50,000$ 50,000$ Fund 31 9,656$ Vehicle Replacement (987) 164,000$ 160,780$ 3,220$ 0$ 220,000$ 220,000$ Fund 61 3,220$ Total 3,457,339 3,221,845 235,494 (1) 712,900 207,100 1,042,899 85,495 FY 2022-23
Investment
[d
]
Available
Project
B
udget
in FY22/23
[c] + Σ[d]
Fund Release
Table 2
FY 2021/22 Project Closeout Summary
Project Title (Number)
Project Budget
Thru 6/30/2022
[a
]
Spending Thru
6/30/2022
[b
]
Unspent
Project Budget
a
t 7/1/2022
[a] - [b]
Project Budget
Carryover to
7/1/2022
[c
]

Town of Colma Attachment B
FY 2022-23 Capital Project Update
Status Through December 31, 2022
Category 1: Streets, Sidewalks, and Bikeways
Annual Roadway Rehabilitiation and Preventative Maintenance Program (906) Ongoing Program Funding and Spending History
Funding Source
Project
Funding
Budget
Actual
Project
Funding Spending
Total Project
Budget
Project Cost
Thru 6/30/22
Project Cost
FY 2022-23
Total Project
Spending
FY 2021/22: F-Street Roadway (mill & fill)
Measure M - - Construction (81003) 150,000 - 149,069 149,069 Measure A (22) 72,600 72,600 Planning & Design (81002) - - - - Measure W (26) 31,950 31,950 - - - -
Gas Tax & RMRA (21) 45,450 45,450 - - - -
Total Funding 150,000 150,000 Total Spending to Date 150,000 - 149,069 149,069 Pending Grant/Other Reimbursements - Available Project Budget 931 FY 2022/23: Hillside & Lawndale - Slurry
Measure A (22) 80,000 80,000 Construction (81003) 292,900 - - - Measure W (26) 60,000 60,000 Planning & Design (81002) - - - - Gas Tax & RMRA (21) 80,000 80,000 - - - -
General Fund 72,900 72,900 - - - -
Total Funding 292,900 292,900 Total Spending to Date 292,900 - - - Pending Grant/Other Reimbursements - Available Project Budget 292,900 El Camino Real Bicycle and Pedestrian Improvement (923) - PSR Funding Source
Project
Funding
Budget
Actual
Project
Funding Spending
Total Project
Budget
Project Cost
Thru 6/30/22
Project Cost
FY 2022-23
Total Project
Spending
Measure W Grant () 1,800,000 - Design (81002) 2,000,000 - - - General Fund 200,000 200,000 Construction (81003) - - - - Total Funding 2,000,000 200,000 2,000,000 - - -
Pending Grant/Other Reimbursements 1,800,000 Available Project Budget 2,000,000 Description: The project includes a re-design of El Camino Real (ECR). It incorporates a lane reduction in each direction so that Class 4 bike lanes can be designated on the Northbound and Southbound directions. The project also includes continuous compliant sidewalks, additional bicycle and pedestrian safety features, new traffic signals, landscaping, reconfiguration of the Mission Road (“the Y”) intersection, and bioretention storm drain infrastructure along ECR. The project presents a vision for residents and visitors to travel safely, comfortably, and with ease.

Status: Funding agreement was received. Staff is preparing the Request for Proposal (RFP), to be published by beginning of February 2023.

Funding and Spending History
Description: The Annual Roadway Rehabilitation and Preventative Maintenance Program includes minor repairs, such as crack sealing, and major rehabilitation, such as slurry seal and mill and fill. The goal of the program is to maintain the Town’s Pavement Condition Index at 80 or above. The project includes mill and fill @ 300 Block of F Street (FY 2021-22) and slurry seal @ Hillside & Lawndale (FY 2022-23).

Status: The Notice of Completion for the mill and fill @ 300 Block of F-Street was accepted by the City Council on October 26, 2022. The slurry seal @ Hillside & Lawndale is scheduled for spring/summer of 2023. Staff will be coordinating with the City of South San Francisco to complete the Hillside slurry project.

Page 1 ends

Town of Colma Attachment B
FY 2022-23 Capital Project Update
Status Through December 31, 2022
Category 1: Streets, Sidewalks, and Bikeways Cont
F-Street Retaining Wall (902)
Funding Source
Project
Funding
Budget
Actual
Project
Funding Spending
Total Project
Budget
Project Cost
Thru 6/30/22
Project Cost
FY 2022-23
Total Project
Spending
Capital Reserve 40,000 40,000 Design (81002) 47,000 40,542 7,910 48,452 General Fund 407,000 407,000 Project Management (71010) 80,000 - - - - Construction (81003) 320,000 - 194,608 194,608
Total Funding 447,000 447,000 447,000 40,542 202,518 243,059 Pending Grant/Other Reimbursements - Available Project Budget 203,941 Mission Road Bicycle and Pedestrian Improvement Project (903) Completed Funding and Spending History
Funding Source
Project
Funding
Budget
Actual
Project
Funding Spending
Total Project
Budget
Project Cost
Thru 6/30/22
Project Cost
FY 2022-23
Total Project
Spending
General Fund 590,000 590,000 Prof Consult (71010) 238,608 246,804 - 246,804 OBAG-TLC (35005) 525,000 558,740 Plng&Design (81002) 401,668 403,403 403,403 OBAG-LSR (35006) 100,000 100,000 Construction (81003) 2,219,724 2,209,793 2,209,793 Measure A (22) 350,000 350,000
Safe Route to School (35007) 200,000 220,000
Gas Tax/RMRA (21) 117,000 117,000
Measure M (35131) 330,000 320,032
PLAN JPA 10,000 10,000
Proj Realloc 638,000 638,000
- - - - -
Total Funding 2,860,000 2,903,772 2,860,000 2,860,000 - 2,860,000 Pending Grant/Other Reimbursements (43,772) Available Project Budget - Description: In 2019, the Engineering Department surveyed the retaining wall on F Street. The survey determined that the deterioration of the F- Street wall is likely due to poor drainage. The first phase of the project is design, specifications, plans, and construction estimates. The second phase includes soliciting bids for construction and construction management services.

Status: Project has been completed. Notice of Completion will be presented to the City Council for approval in March, as a consent item.

Funding and Spending History
Description: The Mission Road Bicycle and Pedestrian Improvements Project includes implementation of several safety related improvements for pedestrians, bicyclists and vehicles along Mission Road between El Camino Real and Lawndale Boulevard.

Status: Completed. Received extra grant funding to offset project cost in the amount of $43,772. Available project funding will be released and recorded as Capital Fund Reserve.

Page 2 ends

Town of Colma Attachment B
FY 2022-23 Capital Project Update
Status Through December 31, 2022
Category 1: Streets, Sidewalks, and Bikeways Cont
Mission Road Crosswalk (909)
Funding Source
Project
Funding
Budget
Actual
Project
Funding Spending
Total Project
Budget
Project Cost
Thru 6/30/22
Project Cost
FY 2022-23
Total Project
Spending
Capital Reserve 11,000 11,000 Design (81002) 11,000 - - - General Fund 119,000 119,000 Project Management (71010) 16,758 - - - - Construction (81003) 102,252 - - -
Total Funding 130,000 130,000 130,009 - - -
Pending Grant/Other Reimbursements - Available Project Budget 130,009 Mission Road Landscaping (908)
Funding Source
Project
Funding
Budget
Actual
Project
Funding Spending
Total Project
Budget
Project Cost
Thru 6/30/22
Project Cost
FY 2022-23
Total Project
Spending
Capital Reserve 29,000 29,000 Design (81002) 29,000 15,109 1,466 16,575 General Fund 343,200 343,200 Project Management (71010) 57,200 6,311 - 6,311 - Construction (81003) 286,000 - - -
Total Funding 372,200 372,200 372,200 21,420 1,466 22,887 Pending Grant/Other Reimbursements - Available Project Budget 349,313 Description: Design and construct a high visibility crosswalk on Mission Road at the back entrance to the Treasure Island mobile home park. The high visibility crosswalk will be delineated with pre-emptive signage, viable pavement markings and pedestrian activated solar powered Rectangular Rapid Flashing Beacons (RRFB’s). Part of the design portion of the project is to design speed humps for the roadway. This will be introduced into the bid documents as a bid alternative.

Status: Project is delayed due to weather and supply chain issues. Tentatively scheduled to start in February 2023.

Funding and Spending History
Description: After completion of the Mission Road Bicycle and Pedestrian Improvement Project in FY 2020-21, a second phase of the project was added to landscape the open area between Holy Cross’s Historic Rock Wall and the back of sidewalk that fronts Holy Cross Cemetery on Mission Road. The landscape design will be to emphasize drought resistance low maintenance plants and shrubs. The tree pallet will be a species of trees that thrive in Colma’s microclimate along with providing color to enhance the roadway frontage and shade for those who walk through the Mission Road Residential and Business District. The landscape area will have rest stops that will be constructed to meet accessibility requirements, park benches, trash receptacles, and a dog mitt station.

Status: Project is delayed due to weather. Tentatively scheduled to start in February 2023.

Funding and Spending History

Page 3 ends

Town of Colma Attachment B
FY 2022-23 Capital Project Update
Status Through December 31, 2022
Category 1: Streets, Sidewalks, and Bikeways Cont
Town-Wide Bicycle and Pedestrian Master Plan (910)
Funding and Spending History
Funding Source
Project
Funding
Budget
Actual
Project
Funding Spending
Total Project
Budget
Project Cost
Thru 6/30/22
Project Cost
FY 2022-23
Total Project
Spending
TDA Art 3 Grant (32-35003) 90,000 - Design (81002) 100,000 - - - General Fund 10,000 10,000
Total 100,000 10,000 100,000 - - -
Total Eligible for Grant Reimbursement 90,000 Available Project Budget 100,000 Category 2: Sewer and Storm Drain
Storm Drain System Assessment and Mapping (972)
Funding Source
Project
Funding
Budget
Actual
Project
Funding Spending
Total Project
Budget
Project Cost
Thru 6/30/22
Project Cost
FY 2022-23
Total Project
Spending
General Fund (11) 70,000 - Design (81002) 70,000 - - - Total Funding 70,000 - Total Spending to Date 70,000 - - - Pending Grant/Other Reimbursements 70,000 Available Project Budget 70,000 Description: Col
ma was awarded funding through the Transportation Development Act Article 3 (TDA3) Pedestrian and Bicycle Program for a Bicycle and Pedestrian Master Plan. The Colma Bicycle and Pedestrian Master Plan will envision a safer, more connected active transportation system in the Town of Colma. This project will build on the El Camino Real Bike and Pedestrian Plan, the Serramonte Collins Master Plan, the Hillside Boulevard complete streets improvement project, the Mission Road improvement project, and Systemic Safety Analysis Report (SSAR) performed by the Town of Colma.

Status: Received grant funding agreement in October. Staff has begun working on the master plan and the study session is tentatively scheduled for May 2023.

Description: The project will review and analyze the Town's 11 miles of the Storm Drain System. The process will begin with starting to assess the current Storm Drainage system by way of internally videotaping the system in its current state. The video will provide several insights; it will unveil any needed repairs and unrecorded blind or illegal connections. The videotaping equipment used to view the interior of the storm drain lines will also have the capabilities of recording the data and allowing the data to be mapped in the Town’s Geographical Information System (GIS). The findings that come through the videotaping process will allow staff to budget for repairs or enhancements to the storm drain system.

Only portions of the system will be addressed each year. The project is expected to be a 3-year effort; funding will be requested on an annual basis for the specific scope of work for each year.

Status: Project is scheduled to start in Spring of 2023. RFP will be sent out in February 2023.

Funding and Spending History

Page 4 ends

Town of Colma Attachment B
FY 2022-23 Capital Project Update
Status Through December 31, 2022
Category 3: Facilities and Long-Range
Colma Museum Repair & Rehab (951)
Funding Source
Project
Funding
Budget
Actual
Project
Funding Spending
Total Project
Budget
Project Cost
Thru 6/30/22
Project Cost
FY 2022-23
Total Project
Spending
General Fund (11) 75,000 75,000 Construction (81003) 75,000 11,245 - 11,245 Total Funding 75,000 75,000 Total Spending to Date 75,000 11,245 - 11,245 Pending Grant/Other Reimbursements - Available Project Budget 63,755 Facility Parking Lot Upgrades and Repairs (953)
Funding Source
Project
Funding
Budget
Actual
Project
Funding Spending
Total Project
Budget
Project Cost
Thru 6/30/22
Project Cost
FY 2022-23
Total Project
Spending
General Fund (11) 240,000 99,025 Construction (81003) 240,000 - - - Total Funding 240,000 99,025 Total Spending to Date 240,000 - - - Pending Grant/Other Reimbursements 140,975 Available Project Budget 240,000 Housing Element Update (996)
Funding and Spending History
Funding Source
Project
Funding
Budget
Actual
Project
Funding Spending
Total Project
Budget
Project Cost
Thru 6/30/22
Project Cost
FY 2022-23
Total Project
Spending
Capital Reserve (31) 125,000 15,000 Plng&Design (81002) 210,000 84,351 44,297 128,648 LEAP Grant (31) 65,000 - - - -
REAP Grant (31) 20,000 - - - -
Total Funding 210,000 15,000 Total Spending to Date 210,000 84,351 44,297 128,648 Pending Grant/Other Reimbursements 195,000 Available Project Budget 81,352 Description: The Historical Museum Facility is currently in need of painting. The work includes minor building repairs such as plaster touch up, dry rot repairs, and window and trim repairs or replacement.

Status: Due to supply shortage, the window installation was delayed to FY 2022-23. The next phase of the project includes exterior painting, Description: Several of the Town owned facility parking lots are in need of reconstruction and/or resurfacing along with striping and Americans with Disabilities Act (ADA) upgrades. This project will address long term parking lot maintenance and reconstruction needs at: Creekside Villas, the Colma Community Center and Historical Museum, the Colma Police Station and the Public Works Maintenance Corporation Yard. The work will vary from facility to facility ranging from reconstruction, (Mill and fill) to minor surface treatments, such as crack sealing and slurry coats. All facilities will be restriped. Installation of additional ADA stalls will be considered if feasible for the Colma Community Center parking lot.

Given the recent increase in oil prices and construction escalation costs, it is estimated that the project will increase by more than 20% over original estimates that were presented several years ago.

Status: Project is postponed to Spring of 2023 for a more competitive bid, Staff is combining all facility parking lot improvements into one bid package.

Funding and Spending History
Description: Pursuant to state law, the Town is required to update its General Plan Housing Element and be adopted by the City Council and certified by the State by January of 2023.

Status: The first draft was submitted to the Housing and Community Development (HCD) for review. The Town received comments from HCD, and are under final review by Staff. The comments are under review by Staff, and the City Council approved report will be submitted to HCD by Jan 31, 2023. The Town expects a few more rounds of comments and reviews between HCD and Staff.

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tentatively scheduled for Spring/Summer of 2023.

Funding and Spending History
Town of Colma Attachment B
FY 2022-23 Capital Project Update
Status Through December 31, 2022
Category 3: Facilities and Long-Range CONT
Public Arts Program (980)
Funding and Spending History
Funding Source
Project
Funding
Budget
Actual
Project
Funding Spending
Total Project
Budget
Project Cost
Thru 6/30/22
Project Cost
FY 2022-23
Total Project
Spending
General Fund 15,000 - Construction (81003) 15,000 - - - Total Funding 15,000 - Total Spending to Date 15,000 - - - Pending Grant/Other Reimbursements 15,000 Available Project Budget 15,000 Town-Wide Branding (959)
Funding Source
Project
Funding
Budget
Actual
Project
Funding Spending
Total Project
Budget
Project Cost
Thru 6/30/22
Project Cost
FY 2022-23
Total Project
Spending
General Fund 100,000 - Prof & Contract Srvc (71010) 100,000 - - - Total Funding 100,000 - Total Spending to Date 100,000 - - - Pending Grant/Other Reimbursements 100,000 Available Project Budget 100,000 Description: The 2012 Economic Development Plan identified several strategies within the framework of the study. One of the strategies was to create Branding and Promotional Materials emphasizing Colma’s commercial activities. Phase 1 of this project will be to prepare an RFP and hire a firm to develop a community branding campaign. The process will involve local outreach, surveys, interviews with business leaders, and other research, and utilizing this information to establish creative options for the community’s brand. Phase 2 will be to launch an expanded image and branding campaign highlighting Colma’s brand through logo, marketing brochures, letterhead, street light banners, promotional campaigns, advertisements and tag lines. Staff will look to partner with local businesses and shopping centers for funding opportunities.

Status: This project has been deferred by the City Council until further notice.

Funding and Spending History
Description: The Town of Colma’s Strategic Plan for 2020-2022 includes an objective of developing a public art and wayfaring program, in the interest of building upon our community identity and maintaining quality of life. On October 13, 2021 and February 23, 2022 the Planning Department presented a public art study session to the City Council in order to gauge interest in implementing public art in Colma. In FY 2022-23 staff is proposing 2-4 pieces of small public art. Once approved, staff would recommend designs that are decorative and that depict uncontroversial subjects.
- Paint or vinyl-wrap two utility cabinets
- Paint on bike rack at the Colma Community Center
Status: Staff is contacting different non-profit organizations to involve kids in the public arts program.

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Town of Colma Attachment B
FY 2022-23 Capital Project Update
Status Through December 31, 2022
Category 3: Facilities and Long-Range CONT
Urban Tree Master Plan & Improvement (998)
Funding Source
Project
Funding
Budget
Actual
Project
Funding Spending
Total Project
Budget
Project Cost
Thru 6/30/22
Project Cost
FY 2022-23
Total Project
Spending
General Fund 100,000 - Prof & Contract Srvc (71010) 100,000 - - - Total Funding 100,000 - Total Spending to Date 100,000 - - - Pending Grant/Other Reimbursements 100,000 Available Project Budget 100,000 Zoning Code Update (997)
Funding and Spending History
Funding Source
Project
Funding
Budget
Actual
Project
Funding Spending
Total Project
Budget
Project Cost
Thru 6/30/22
Project Cost
FY 2022-23
Total Project
Spending
Capital Reserve (31) 100,000 100,000 Plng&Design (81002) 180,000 21,971 30,288 52,260 General Fund 80,000 -
Total Funding 180,000 100,000 Total Spending to Date 180,000 21,971 30,288 52,260 Pending Grant/Other Reimbursements 80,000 Available Project Budget 127,741 Status: Project is scheduled to be presented to the City Council in May/June of 2023.

Description: An Urban Tree Master Plan outlines the objectives and actions needed to sustain, protect, and enhance trees along streets, parks, and open space area. The Town’s trees have been tagged and entered into a GIS database. The next step is to contract with a certified arborist to survey and assess the health of town trees and provide a tree maintenance schedule that includes pruning, fertilizing, and replacing trees. The result of the study will be incorporated into the existing GIS database, along with tree maintenance and replacement schedule.

Cost for the tree survey and incorporating the results into the GIS database is estimated at $100,000.

The project also includes tree replacement; however, an analysis of the existing tree conditions is required prior to any replacement. Staff is recommending a budget of $200,000 for future year tree replacement.

Status: Staff is working with an arborist and preparing the RFP.

Funding and Spending History
Description: Pursuant to state law, the Town of Colma is required to amend its zoning code and zoning map after the adoption of the General Plan, anticipated by the end of calendar year 2021. The General Plan and zoning must be consistent with one another.

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Town of Colma Attachment B
FY 2022-23 Capital Project Update
Status Through December 31, 2022
Category 4: Major Equipment, Technology, & Fleet Projects Equipment Purchase and Replacement (984) Ongoing Program Funding and Spending History
Funding Source
Project
Funding
Budget
Actual
Project
Funding Spending
Total Project
Budget
Project Cost
Thru 6/30/22
Project Cost
FY 2022-23
Total Project
Spending
FY 2021/22: In-Car and Body-Worn Camera
General Fund (11) 201,000 201,000 Technology System (80005) 141,000 69,608 69,608 Technology Hardware (81005) 60,000 61,013 61,013
Total Funding 201,000 201,000 Total Spending to Date 201,000 130,621 - 130,621 Pending Grant/Other Reimbursements - Available Project Budget 70,379 FY 2021/22: Council Chamber AV System
General Fund (11) 32,339 32,339 Technology System (80005) 32,339 30,099 30,099 Technology Hardware (81005) - - -
Total Funding 32,339 32,339 Total Spending to Date 32,339 30,099 - 30,099 Pending Grant/Other Reimbursements - Available Project Budget 2,240 FY 2022-23: PD Radio Encryption
General Fund (11) 130,000 - Technology System (80005) 130,000 - - - Technology Hardware (81005) - - - -
Total Funding 130,000 - Total Spending to Date 130,000 - - - Pending Grant/Other Reimbursements 130,000 Available Project Budget 130,000 FY 2022-23: PD Lawnet Upgrade
General Fund (11) 20,000 - Technology System (80005) 20,000 - 12,703 12,703 Technology Hardware (81005) - - - -
Total Funding 20,000 - Total Spending to Date 20,000 - 12,703 12,703 Pending Grant/Other Reimbursements 20,000 Available Project Budget 7,297 Status: The PD dispatch center radio and equipment upgrade (FY 2019-20) project was completed in FY 2020-21, as scheduled. The available project budget of $32,339 was reallocated to the Council Chamber AV System Upgrade to allow for hybrid council meetings. The Council Chamber AV System Upgrades (FY 2021-22) and Body Worn and In-Car Camera (FY 2021-22) were completed under budget. The PD Radio Encryption Upgrade will be on hold while the San Mateo County Police Chief Association research on the best system. This collaboration is important for the public safety departments to ensure smoother cross agency collaborations during emergencies. The PD Lawnet Equipment Upgrade is underway and will be completed by June 30, 2023.

Description:

This Capital Improvement Project covers the purchase of major equipment Town-wide. The projects include:
• Police Station Dispatch Center Radio and Equipment Upgrade (FY 2019-20) - Project Budget $217,661 • Council Chamber AV System Upgrades (FY 2021-22) - Project Budget $32,339 • Body Worn and In-Car Camera (FY 2021-22) - Project Budget $191,000 • Lawnet Equipment Upgrade (FY 2022-23) - $20,000
• PD Radio Encryption Upgrade (FY 2022-23) - $120,000

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Town of Colma Attachment B
FY 2022-23 Capital Project Update
Status Through December 31, 2022
Category 4: Major Equipment, Technology, & Fleet Projects CONT Financial Software Replacement (965)
Funding Source
Project
Funding
Budget
Actual
Project
Funding Spending
Total Project
Budget
Project Cost
Thru 6/30/22
Project Cost
FY 2022-23
Total Project
Spending
General Fund (11) 100,000 100,000 Prof Consulting Srvc (71010) 15,000 - - - Capital Reserve (31) 430,000 430,000 Technology (81005) 515,000 - - - Total Funding 530,000 530,000 Total Spending to Date 530,000 - - - Pending Grant/Other Reimbursements - Available Project Budget 530,000 IT Infrastructure Upgrades (986) Ongoing Program
Funding and Spending History
Funding Source
Project
Funding
Budget
Actual
Project
Funding Spending
Total Project
Budget
Project Cost
Thru 6/30/22
Project Cost
FY 2022-23
Total Project
Spending
FY 2021/22 Technology Upgrade
General Fund (11) 50,000 50,000 Software & Network (81005) 50,000 40,344 - 40,344 Total Funding 50,000 50,000 Total Spending to Date 50,000 40,344 - 40,344 Pending Grant/Other Reimbursements - Available Project Budget 9,656 FY 2022/23 Technology Upgrade
General Fund (11) 50,000 50,000 Software & Network (81005) 50,000 - 16,449 16,449 Total Funding 50,000 50,000 Total Spending to Date 50,000 - 16,449 16,449 Pending Grant/Other Reimbursements - Available Project Budget 33,551 Description: Ongoing program for technology infrastructure upgrades.

Status: For FY 2021-22, the Town completed Office 365 migration and server upgrades. The FY 2022-23 Program will include scheduled desktop and hardware replacements.

Description: Financial Software Replacement will begin with a need assessment of Town operations, identify most suitable ERP system for financial data, and purchase and transition data from current financial software to the new system. Project was postponed due to COVID-19 and shifting the project funding to other projects. The projected total project cost is $530,000.

Status: The project will begin after the 2023-24 budget session.

Funding and Spending History

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Town of Colma Attachment B
FY 2022-23 Capital Project Update
Status Through December 31, 2022
Category 4: Major Equipment, Technology, & Fleet Projects Cont.

Vehicle Replacement (987) Ongoing Program
Funding and Spending History
Funding Source
Project
Funding
Budget
Actual
Project
Funding Spending
Total Project
Budget
Project Cost
Thru 6/30/22
Project Cost
FY 2022-23
Total Project
Spending
FY 2021/22 Vehicle Replacement
Fleet Replacement (61) 164,000 164,000 PD Patrol - 2 Chevy Tahoe (80002) 124,000 150,244 - 150,244 Police Non-Patrol (80002) 40,000 10,536 - 10,536
Total Funding 164,000 164,000 Total Spending to Date 164,000 160,780 - 160,780 Pending Grant/Other Reimbursements - Available Project Budget 3,220 FY 2022/23 Vehicle Replacement
Fleet Replacement (61) 220,000 220,000
PD Patrol - Explorer & F-150 (80002) 150,000 - - - PWs Veh (80002) 70,000 - 63,126 63,126
Total Funding 220,000 220,000 Total Spending to Date 220,000 - 63,126 63,126 Pending Grant/Other Reimbursements - Available Project Budget 156,874 Description: This Capital Improvement Project covers the purchase of vehicles and major fleet items Town-wide. In the FY 2021-22, the Police Department will replace the patrol supervisor vehicle (Flex Fuel Tahoe, $64k) , a patrol (Hybrid Explorer, $60k) and one detective vehicle (Honda, $40k) . The cost of these three vehicles is estimated at $164,000, including outfitting with public safety equipment. In FY 2022-23, the Public Works Supervisor's truck and 2 patrol vehicles are scheduled for replacement.

Status: The Town purchased the 2 patrol vehicles and repurposed an existing vehicle for the detective car in FY 2021-22. For FY 2022-23, Police is in the midst of securing 2 patrol vehicles and the all electric PWs vehicle was purchased early in the fiscal year.

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El Camino Real Segment B Design Project (915)
Design of El Camino Real Complete Street Project from Mission Road to Arlington Dr, City of South San Francisco
Project Scope
The Project involves the design phase (plans, specifications and estimates) of the El Camino Real Segment B which is a component of the larger ECR Bicycle and Pedestrian Improvement Project. The project will provide new bike paths and sidewalks that are absent from this portion of ECR (Safe Route 82). This project will also provide safe harbor at the redesigned bus stops. Segment B will address green street and storm water treatment objectives where achievable, available landscape areas will be designed to be drought tolerant and incorporate stormwater treatment facilities. Another aspect of this project is to remove barriers such as utility poles and underground overhead utilities . Street lighting will also be installed along this portion of ECR where it’s currently nonexistent.

Status as of December 31, 2022
Preparation of Cycle 6 Pedestrian and Bicycle grant application which was due 9/21/2022.

Schedule for FY 2022-23 and Thereafter
B egin End____
PS&E 07/2023 12/2024
Impact on Operation
This is a design project and will have no impact on Operation.

Project Funding and Spending Plan
Phase Cycle 6 Ped & Bike
Program –
Measure W
Funding Amount
Local Fund Total
PS&E $603,000 $67,000 $670,000
Total $603,000 $67,000 $670,000
Attachment C

El Camino Real/Mission Road Access to Transient
Multimodal Crossing Improvements (904)
Project Scope
The Project involves the design phase (Plans, Specifications and Estimates) of the El Camino Real and Mission Road intersection which is a component of the larger ECR Bicycle and Pedestrian Improvement Project. The plan development portion of the project consists of, reengineering the intersection and realigning Mission Road to intersect with ECR at 90 degrees, a new traffic signal system, pavement stripping, markings and street signage, hardscape/landscape features and various pedestrian and bicycle enhancements.

S
tatus as of December 31, 2022
The ACR/TDM grant application was under evaluation by San Mateo County Transportation Authority by June 30, 2022.

Schedule for FY 2022-23 and Thereafter
B egin End____
PS&E 07/ 2023 12/2024
Impact on Operation
This is a design project and will have no impact on the Operation.

Project Funding and Spending Plan
Phase ACR/TDM Program
– Measure W
Funding Amount
Local Fund Total
Design (PS&E) $162,000 $18,000 $180,000
Total $162,000 $18,000 $180,000
Attachment D

El Camino Real Segment B Construction Project (916)
Construction of El Camino Real Complete Street Project from Mission Road to City of South San Francisco (Segment B)
Project Scope
The Project involves the construction phase of the El Camino Real Segment B project which is a component of the larger ECR Bicycle and Pedestrian Improvement Project. The project will provide new bike paths and sidewalks that are absent from this portion of ECR (S tate Route 82). This project will also provide safe harbor at the redesigned bus stops. Segment B will address green street and storm water treatment objectives where achievable, available landscape areas will be designed to be drought tolerant and incorporate stormwater treatment facilities. Another aspect of this project is to remove barriers such as utility poles and underground overhead utilities. Street lighting will also be installed along this portion of ECR where it’s currently nonexistent.

Status as of December 31, 2022
Preparation of OBAG 3 grant application which was due 7/1/2022.

Schedule for FY 2022-23 and Thereafter
Be gin End____
C onstruction 01/2026 06/2027
Impact on Operation
When the construction of the project is complete, the Town will need to provide annual landscape maintenance in coordination with Caltrans similar to the current maintenance work of the existing landscape on El Camino Real.

Project Funding and Spending Plan
Phase OBAG 3 Funding
Amount
Local Fund Total
Construction $4,640,000 $1,160,000 $5,800,000
Total $4,640,000 $1,160,000 $5,800,000
Attachment E

Serramonte Boulevard West Bicycle and Pedestrian
Improvement Project (Phase I) (911)
P
roject Scope
Phase I of the project involves design (plans, specifications and estimates) and construction of the Serramonte Blvd West. The project will take a four -lane roadway and reduce it down to two lanes (one lane in each direction), and provide a center turn lane for those entering or exiting the various retail outlets along the Boulevard. The pilot lane reduction will provide right of way to build separated Class IV bike lanes in both directions. The project will also provide two mid-block high visibility crosswalks with rectangular rapid flashing beacons (RRFB) along with safe harbor refuge island. A "Quick Build" option will be implemented into the phase one project to provide temporary low- cost landscape barriers to separate bicyclists and pedestrians from vehicular traffic. This project will include the signalizing of the Serramonte Blvd and Serra Center Intersection.

Status as of December 31, 2022
Preparation of Cycle 6 Pedestrian and Bicycle grant application which was due 9/21/2022.

Schedule for FY 2022-23 and Thereafter
B egin End____
P A/Environmental Document 03/2023 06/2023
PS&E 04/2023 12/2023
Right-of-Way 06/2023 12/2023
Construction 01/2024 03/2025
Impact on Operation
Phase I of the project will require traffic impact monitoring and collect feedback from the stakeholders. The Town will need to provide annual landscape maintenance to the temporary planters that will be installed along the buffer zone of Class IV bike lanes.

Project Funding and Spending Plan
Phase Cycle 6 Ped & Bike
Program –
Measure W
Funding Amount
Local Fund Total
PS&E $432,000 $48,000 $480,000
Construction $1,399,500 $155,500 $1,555,000
Total $1,831,500 $203,500 $2,035,000
Attachment F

Colma City CouncilJanuary 25, 2023

Colma City Council
January 25, 2023