The four-fifths rule is the cornerstone of employment discrimination analysis. It's the benchmark used in NYC LL144 audits, EEOC investigations, and disparate impact lawsuits. Yet many HR professionals and compliance officers don't fully understand how it works or where it comes from.
This article explains the four-fifths rule from first principles.
Origins: The 1978 Uniform Guidelines
The four-fifths rule comes from the Uniform Guidelines on Employee Selection Procedures, jointly adopted in 1978 by the EEOC, Department of Labor, Department of Justice, and Civil Service Commission. These guidelines established a framework for determining whether employment selection procedures have an adverse impact on protected groups.
Section 4D of the Guidelines states: "A selection rate for any race, sex, or ethnic group which is less than four-fifths (4/5) (or eighty percent) of the rate for the group with the highest rate will generally be regarded by the Federal enforcement agencies as evidence of adverse impact."
The Calculation
The four-fifths rule involves two calculations:
Step 1: Calculate Selection Rates
For each demographic group, divide the number selected by the total number of applicants in that group.
Selection Rate = Number Selected / Total Applicants
Step 2: Calculate Impact Ratios
Compare each group's selection rate to the group with the highest selection rate.
Impact Ratio = Group's Selection Rate / Highest Selection Rate
A Worked Example
Suppose a company receives 500 applications and makes 100 hires. The breakdown by race is:
| Group | Applicants | Hired | Selection Rate | Impact Ratio |
|---|---|---|---|---|
| White | 250 | 60 | 24% | 1.00 |
| Asian | 100 | 22 | 22% | 0.92 |
| Hispanic | 80 | 12 | 15% | 0.63 |
| Black | 70 | 6 | 8.6% | 0.36 |
In this example, White applicants have the highest selection rate (24%), so they're the reference group. Hispanic applicants have an impact ratio of 0.63 (15% / 24%), and Black applicants have an impact ratio of 0.36 (8.6% / 24%). Both are below the 0.80 threshold, indicating potential adverse impact.
Important Nuances
It's a "Rule of Thumb," Not a Safe Harbor
The Guidelines explicitly state that the four-fifths rule is a "rule of thumb." Passing it doesn't guarantee a procedure is non-discriminatory, and failing it doesn't automatically prove discrimination. Courts and agencies consider additional factors, including statistical significance and practical significance.
Small Sample Sizes Matter
With small samples, random variation can produce misleading impact ratios. If you have only 10 applicants in a group, a single hiring decision changes the selection rate by 10 percentage points. This is why serious audits supplement the four-fifths rule with statistical significance testing (like Fisher's exact test or z-tests).
Intersectional Analysis
NYC LL144 requires analysis not just by sex and race/ethnicity separately, but by their intersection (e.g., "Black female," "Asian male"). This can reveal disparities hidden in aggregate data.
What Happens When You Fail
Failing the four-fifths rule doesn't mean you must immediately stop using the selection procedure. Under the Uniform Guidelines, an employer can continue using a procedure with adverse impact if it can demonstrate "validity"—that the procedure is job-related and consistent with business necessity.
However, even with validity, the employer should also show there's no alternative procedure with less adverse impact that would serve the same purpose.
How Paritas Applies the Rule
Every Paritas audit calculates impact ratios using the four-fifths rule, but we go further:
- We use a three-tier classification: PASS (≥0.90), MONITOR (0.80-0.89), FLAG (<0.80)
- We apply Fisher's exact test and z-tests for statistical significance
- We calculate 95% confidence intervals around each impact ratio
- We flag cases where statistical and practical significance diverge
- We provide remediation recommendations when ratios fall below threshold