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INDICATORS REFERENCE

Discrimination Analysis Indicators

Discrimination Analysis covers 200 indicators across 6 discrimination groups. Each signal has a stable slug and code for programmatic access. Representative signals are shown publicly; the complete reference is available to customers.

View Discrimination Groups Features

200

Indicators

6

Discrimination Groups

16

Languages

33

Avg / Group

Overview Discrimination Groups Indicators Features

6 results

Showing 6 representative indicators of 200. The complete taxonomy is available to customers.

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#	Indicator	Slug	code	Discrimination Group
001	discrimination	`discrimination`	`conduct_bias.discrimination`	Conduct Bias
002	race based discrimination	`race_based_discrimination`	`identity_origin.race_based_discrimination`	Identity Origin
003	religion discrimination	`religion_discrimination`	`identity_status.religion_discrimination`	Identity Status
004	sex discrimination	`sex_discrimination`	`identity_personal.sex_discrimination`	Identity Personal
005	hiring discrimination	`hiring_discrimination`	`context_access.hiring_discrimination`	Context Access
006	discriminatory harassment	`discriminatory_harassment`	`conduct_hostile.discriminatory_harassment`	Conduct Hostile

Browse by Discrimination Group

Alternatively, explore indicators grouped by their parent discrimination group:

1

Conduct Bias

conduct_bias

40 Indicators

The complete signal list for this discrimination group is available to customers. Request access to view it.

2

Identity Origin

identity_origin

30 Indicators

The complete signal list for this discrimination group is available to customers. Request access to view it.

3

Identity Status

identity_status

40 Indicators

The complete signal list for this discrimination group is available to customers. Request access to view it.

4

Identity Personal

identity_personal

30 Indicators

The complete signal list for this discrimination group is available to customers. Request access to view it.

5

Context Access

context_access

40 Indicators

The complete signal list for this discrimination group is available to customers. Request access to view it.

6

Conduct Hostile

conduct_hostile

20 Indicators

The complete signal list for this discrimination group is available to customers. Request access to view it.

Reading Discrimination Analysis output

What you can safely infer from a result - and what you must not.

Intended task

Flag documented exclusionary and discriminatory language patterns tied to protected classes - for human or policy review.

Input requirements

text - the only field analyzed; up to 4,096 Unicode code points. Over the limit is rejected with input_too_long, never truncated.
language - must be a language this analyzer supports. Unsupported codes are rejected with 400 unsupported_language, never analyzed as a different language.
analyzers - include "discrimination"; up to 2 analyzers per request, one billed run each.
No context beyond text - no user IDs, history, profiles, or attachments are read or inferred.
Sees only the submitted text - the writer's identity, role, and the document's legal context are not inputs.

Ordinary positive

“Applicants must be under 40 and born in this country - no exceptions.”

employment_discrimination very high

age high

nationality_origin high

Safe inference: The text matches documented exclusion patterns on two protected classes. Route it to review with the labels attached.

Confusing negative · Quotation

“The handbook's old rule - "applicants must be born in this country" - was struck down in 2019.”

What happens: The exclusion pattern can still match the quoted clause. Signals flag the language for review - they do not read the surrounding context that makes this a compliance document describing a repealed rule.

Why it's tricky: Audits, legal analysis, and journalism all quote discriminatory language. Ambiguous phrasing ("we need someone young and energetic") may produce weak or no signals - absence is "not detected," never clearance. Both cases are why flagged text goes to review, not to automatic verdicts.

What you can safely infer

Which documented protected-class patterns the text matched, and at what strength.
That the result is reproducible - the receipt ties the labels to the configuration that produced them.

What you must not infer

✕That unlawful discrimination occurred - legality is a determination for your counsel and jurisdiction.
✕The author's intent, or that a specific person was harmed.
✕That clean text contains no exclusionary content - a missing signal is "not detected," never "compliant."

Boundary: Discrimination signals flag exclusionary language for review - they do not determine that unlawful discrimination occurred, and they say nothing about intent.

Signal reference Evaluation evidence Understanding signals API reference Evaluate on your data

Using Indicators in API Responses

When you call /v1/analyze, the response includes matched indicators with signal-match scores. Each signal is identified by its code and includes a level field (“category” or “label”). A score expresses signal-match strength under a particular analyzer configuration. It is not a probability that the signal or a downstream action is correct. Validate action thresholds on representative labeled data.

{
    "language": "en",
    "language_source": "declared",
    "signals": [
        {
            "analyzer": "discrimination",
            "code": "protected_class_bias",
            "label": "Protected Class Bias",
            "score": 0.93,
            "level": "category"
        },
        {
            "analyzer": "discrimination",
            "code": "ethnic_exclusion",
            "label": "Ethnic Exclusion",
            "score": 0.91,
            "level": "label",
            "parent": "protected_class_bias"
        }
    ],
    "meta": {
        "analyzers": [
            {
                "name": "discrimination",
                "status": "completed",
                "applicability": "analyzable",
                "assessment": "signals_detected",
                "signal_count": 2,
                "billed": true
            }
        ]
    },
    "usage": {
        "analyzer_runs": 1
    },
    "verification": {
        "configuration": "sqcfg_5DDA6HPF",
        "fingerprint": "fp_8a72...19f",
        "input_commitment": "ic_31bd...a42",
        "signature": "sig_ed25519_4c1f...e2a",
        "key_id": "edk_af4f218e"
    }
}

Back to Discrimination Analysis Docs View Discrimination Groups

Quickstart Guide

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API Reference

Full endpoint documentation

Benchmark Results

Per-language Top-3 Hit Rate

Pricing

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Playground

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Indicator Dictionary

Browse all 200 indicators

Benchmark Methodology

How we measure Top-3 Hit Rate

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