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Adverse impact calculator

The four-fifths rule, with the small-cohort guards that decide whether a ratio is a finding or a coincidence.

The four-fifths rule compares each group’s selection rate to the highest group’s rate. A ratio below 0.8 is evidence of adverse impact requiring investigation. It is a screening heuristic from the US Uniform Guidelines, not a legal verdict: falling below it does not establish discrimination, and clearing it does not establish fairness.

Enter your numbers

One row per group, at a single stage of your process. Everything is computed in your browser and nothing is sent anywhere.

GroupApplicantsSelectedSelection rateImpact ratioRemove
25.0%0.80
15.0%0.48 — below the four-fifths threshold
31.1%1.00

Highest selection rate: 31.1%. Every impact ratio above is that group’s rate divided by this one.

Total in this comparison: 245

1 group below the four-fifths threshold. That is evidence of adverse impact requiring investigation, not a finding of discrimination. The next questions are which stage produced it and whether the requirement driving it is genuinely job-related.

How to read the result

The impact ratio is one group’s selection rate divided by the highest group’s selection rate. If your strongest group is selected at 25 per cent and another at 17 per cent, the ratio is 0.68, which is below the threshold and worth looking into.

What it is telling you is that a neutral-seeming practice produced an unequal outcome. Intent is not part of it. The useful next questions are which stage produced the disparity, whether the requirement driving it is genuinely necessary for the role, and whether there is a less exclusionary way to test the same thing.

Measure one stage at a time. A ratio computed across a whole funnel routinely hides a single stage producing all of the effect, and the stage is what you can actually change.

Questions about the four-fifths rule

What is the four-fifths rule?
Compare each group’s selection rate to the highest group’s selection rate. If the ratio is below 0.8, that is evidence of adverse impact requiring investigation. It comes from the US Uniform Guidelines on Employee Selection Procedures, published in 1978.
Does failing the four-fifths rule mean we are discriminating?
No. It means a screening heuristic has fired and the practice needs justification, generally by showing it is job-related and consistent with business necessity. It is evidence requiring investigation, not a finding.
Does passing it mean we are safe?
Also no. Regulators have been explicit that clearing the ratio does not guarantee a practice will not be found to have disparate impact. Intersectional effects and small groups sit comfortably behind a passing ratio.
Why does the calculator warn about small groups?
Because in a group of four people, one selection moves the ratio from 0 to 1. Groups under five are shown but never flagged, and a total under thirty is flagged as too small to analyse, because below those floors the number is noise.
Is my data sent anywhere?
No. Everything is computed in your browser. There is no network request in the calculator and no endpoint to receive one. Given what the inputs are, that seemed like the only defensible design.
Which stage should I measure?
One stage at a time. Adverse impact usually concentrates at a single stage rather than spreading evenly, so a whole-funnel figure tends to average away the thing you are looking for.

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