Short answer: LL144 uses different calculation paths depending on what the AEDT produces. Selection or classification outputs use selection-rate analysis, while scoring outputs use the full-sample median, scoring rates and impact ratios. Correctly documenting the output meaning is therefore a prerequisite to the audit.
For selection or classification outputs, 6 RCNY §5-301 requires selection rates and impact ratios. For scoring outputs, it requires the full-sample median, scoring rates and impact ratios. Scoring rate is the rate at which individuals in a category receive a score above the sample median.
How do selection rate and scoring rate differ?
| Question | Selection / classification | Scoring |
|---|---|---|
| Primary rate | Selection rate | Scoring rate |
| Population benchmark | Most selected category | Full-sample median, then highest scoring category |
| Impact ratio | Category selection rate ÷ highest selection rate | Category scoring rate ÷ highest scoring rate |
Why does AEDT output mapping matter?
Auditors should not force a score-based workflow into a binary-selection model or vice versa. The audit should document what the AEDT actually outputs and how the employer or agency uses that output.
Frequently asked questions
It is the rate at which individuals in a category receive a score above the full sample's median score.
It is the rate at which individuals in a category move forward in the hiring process or are assigned a classification by an AEDT.
Potentially. If an AEDT produces multiple relevant outputs or groups, the applicable calculation set must be mapped to the actual workflow and rule requirements.
How should the output type be documented before an audit?
Use this page for general information only. For a specific workflow, review the LL144 scope framework or request an independent bias-audit scope review. Do not send candidate-level data through ordinary email.