Attachment C — Community & Economic Development Committee (ced), February 26, 2024

1 Attachment C – Disparate Impact Analysis Summary
This analysis was conducted using a model developed by Charles MacNulty from the City of San Francisco’s Mayor’s Office of Housing and Community Development. Mr. MacNulty’s work is based on methods used in case law in employment and housing cases. It has been supported by the United States Housing and Urban Development Department and the California Housing and Community Development Department. There is no single analysis to show disparate impact, which is why this analysis uses two models:
• The Four-Fifths test uses the Equal Employment Opportunity Commission Method, the Langlois Method, and
• The Standard Deviation Analysis.
1) Four-Fifths test: This measures whether a selection rate for a minority race/ethnic group is less than four-fifths (80%) of the selection rate for the largest race/ethnic group. The courts generally regard a selection rate of less than four-fifths (or less than 80%) as evidence of adverse impact. The City’s quantitative disparate impact model uses two versions of this test:
a. EEOC: Used by the U.S. Equal Employment Opportunity Commission (EEOC), this method compares the selection rates of the minority group against each majority group.

For example, if the selection rate for Asian applicants divided by the selection rate for White applicants (the racial majority in San José) is less than 80%, then the preference would fail this test.

Note: In San José, there is no racial group that is a majority. However, the White population is considered the majority group, given the history of racism and systemic bias/privilege.
b. Langlois Variation: This method compares the selection rates for minority applicants with the preference to the selection rate of the same group without the preference.

For example, if the selection rate for Asians with the residency preference is less than 80% of the selection rate for Asians without the preference, then the preference would fail the test.
2) Standard Deviation Analysis: The standard deviation analysis measures the probability of a nonbiased selection system by statistically evaluating the difference between occupancy with and without preference. A z-score (count of standard deviations from the mean) greater than two to three indicates a possible selection bias.

To simplify the math, an example of disparate impact would be if a city were to impose a 100% neighborhood preference for affordable housing, meaning that neighborhood residents were 2 given priority for all new affordable housing units in their neighborhood. If City Council District A is comprised of only 10% Asian Americans and 90% White residents, but the city as a whole is 50% Asian American residents and 50% White residents, this program would adversely impact Asian American residents relative to White residents, since we would expect that only 10% of the affordable housing units in that City Council District would go to Asian Americans even though Asian Americans are half of the city-wide population. In other words, staff must consider if the proposed Tenant Preference Program will distort what is normally expected given the underlying population.

The two methodologies apply San José’s demographic data to the proposed preferences framework to determine disparate impact.

The following data was available to conduct these tests to ensure no adverse impact would occur toward protected classes due to the proposed Tenant Preference Program.

Protected
Class
Data Source Income Levels Analyzed Geographic Areas Analyzed Race
Comprehensive
Housing
Affordability
Strategy (CHAS)
50% of the Area Median
Income (AMI) or below,
80% of AMI or below
High Displacement Areas:

Census tracts experiencing
definitive displacement and at
risk of displacement in San
José.