The CROWN Discrimination Index

The Measurement That Does Not Yet Exist

Ask a straightforward question — how much hair discrimination is there in France? — and you will find that no one can answer it. Not with precision. Not with data that a legislator could cite in committee, an employer could benchmark against, or a court could accept as evidence.

The United States has made significant progress. The Dove and LinkedIn CROWN Workplace Research Study (2023) found that Black women’s hair is 2.5 times more likely to be perceived as unprofessional. The University of Connecticut’s 2025 Hair Satisfaction Study documented that 54 per cent of Black girls aged twelve report hair-related teasing. These findings have been cited in the legislative proceedings of every US state that has adopted the CROWN Act.

Europe has no equivalent. The OECD’s 2025 report on combatting discrimination in the European Union confirmed that comparable official data does not exist across member states. There is no standardised instrument to measure hair discrimination prevalence. There is no index to quantify its severity. There is no framework to estimate its economic cost.

The CROWN Discrimination Index exists to fill that void.

What the CDI Is

The CROWN Discrimination Index (CDI) is a proprietary composite metric that quantifies the prevalence, intensity, and economic impact of identity-based discrimination. It is designed to transform subjective experience — I was passed over for promotion because of my hair — into objective, standardised, comparable data that institutions can act upon.

The CDI draws on methodological expertise at the Faculty of Psychology and Educational Sciences, University of Geneva. It is modelled on established composite indices that have proven their capacity to shape policy at national and international levels:

• The Human Development Index (HDI) combines life expectancy, education, and income into a single metric that ranks 193 countries and informs billions of dollars in development spending.
• The Gender Inequality Index (GII) quantifies gender-based disadvantage across health, empowerment, and labour market participation, providing the evidence base for gender equality legislation worldwide.
• The Gini coefficient reduces the full complexity of income distribution to a single number that every economist, policymaker, and journalist can interpret.

The CDI applies the same principle to discrimination: reduce complexity to a metric that is rigorous enough for academic publication, standardised enough for cross-national comparison, and accessible enough for legislative deliberation.

Three Pillars of Measurement

The CDI integrates three measurement dimensions, each addressing a specific limitation of existing approaches to discrimination research.

Pillar 1: Survey-Based Measurement Calibrated Against Hardware Data

Traditional discrimination research relies on self-reported data: individuals describe their experiences through questionnaires. This methodology, while valuable, is subject to well-documented biases. Individuals may underreport discrimination due to normalisation (I thought it was just me), or overreport due to heightened awareness in survey contexts. Cultural and linguistic differences affect how discrimination is described and categorised across countries.

The CDI addresses this through a calibration methodology that is, to our knowledge, unique in discrimination research. Survey responses are linked, with informed consent, to hardware-verified diagnostic data from CROWN’s multi-sensor diagnostic device. This creates an objective anchor: the device produces a CROWN Hair DNA profile that precisely characterises the respondent’s hair type, chemical treatment history, and physical condition — data that is not subject to self-report bias.

By correlating objective hair characteristics with reported discrimination experiences, the CDI can identify patterns that survey-only methodology would miss. For example: does the prevalence of discrimination correlate with specific, measurable hair properties (fibre diameter, curl pattern classification, porosity index), or with the broader social category the individual belongs to? This distinction has significant implications for both research and legislation.

The full methodology for the calibration approach is documented separately for academic audiences.

Pillar 2: Severity-Weighted Scoring

Not all experiences of discrimination are equivalent. A comment about hair texture in a social setting and the denial of a job based on hairstyle represent categorically different levels of harm. The CDI accounts for this through a severity-weighting framework that differentiates across a defined spectrum:

• Microaggressions and social encounters — unsolicited touching, “compliments” that reinforce conformity norms, casual remarks
• Institutional encounters — school dress code enforcement, workplace grooming policy application, service refusal
• Professional consequences — documented impact on hiring, promotion, performance evaluation, or termination
• Economic consequences — measurable income effects, conformity spending (chemical treatments, wigs, weaves purchased to meet institutional expectations), career deflection
• Health consequences — psychological distress, clinical anxiety or depression, physical health effects of chemical straightening (including the NIH’s 2022 findings linking chemical relaxers to elevated uterine cancer risk)

Each category carries a calibrated weight reflecting its documented impact on individual wellbeing and economic outcomes. The weighting framework is informed by the existing research literature — including Yale’s 2024 study on economic impact and the Association of Black Psychologists’ designation of hair discrimination as “aesthetic trauma” — and will be refined as CROWN’s own data matures.

Pillar 3: Economic Quantification

Discrimination has economic costs. The CDI quantifies four dimensions:

• Wage gaps attributable to appearance-based discrimination, controlling for education, experience, and industry
• Career deflection — the economic value of career paths not taken because of discriminatory environments
• Healthcare expenditure — the cost of treating discrimination-related psychological and physical health consequences
• Conformity spending — expenditure on chemical straightening, extensions, wigs, and other modifications undertaken not by choice but to meet institutional appearance expectations

This economic dimension serves a specific strategic purpose. Legislators respond to economic arguments. When the CDI can demonstrate that hair discrimination costs the French economy a specific, evidence-based figure annually, the case for legislative action becomes more than moral — it becomes fiscal.

How the CDI Is Calculated

The CDI produces a composite score that integrates all three measurement pillars into a single metric. The score can be disaggregated by geography (country, region, city), by sector (workplace, education, healthcare, public services), by demographic group, and by time period — enabling the kind of comparative analysis that policymaking requires.

The specific algorithms, weighting coefficients, and calibration procedures that produce the CDI score are proprietary. They will be disclosed to the extent required for peer review and academic replication, but are not published on this site.

What we can share is the design philosophy: the CDI is constructed to be sensitive (it detects real changes in discrimination levels), specific (it distinguishes between discrimination types and contexts), comparable (scores are meaningful across countries and time periods), and actionable (the disaggregated components point to specific interventions).

Academic Collaboration

CROWN is developing the CDI in consultation with researchers at the University of Geneva, one of Europe’s leading research universities. The Faculty of Psychology and Educational Sciences brings expertise in survey instrument design, validation methodology, and statistical frameworks that informs CROWN’s approach.

This emerging collaboration is designed to ensure that the CDI meets the standards required for publication in peer-reviewed journals, acceptance as evidence in policy deliberation, and adoption by other researchers for cross-study comparison.

The pilot study — CROWN’s first empirical data collection — is currently in progress. The validation pathway proceeds through three stages: pilot study, peer review, and independent replication. Full details are available on the CDI Methodology page.

Applications

The CDI is designed to serve four primary constituencies:

1. Corporate ESG — Companies benchmark their organisation’s discrimination profile, track improvement over time, and report to stakeholders. Read more

2. Policy Impact Assessment — Governments measure CDI before and after legislative interventions to assess effectiveness.

3. Academic Research — Researchers use CDI as a standardised instrument for cross-national and cross-temporal studies on discrimination.

4. Legal Evidence — CDI data serves as quantitative evidence in employment tribunals, discrimination complaints, and legislative proceedings.

Each application is explored in detail on the CDI Applications page.

What the CDI Is Not

The CDI is not a consumer product. It is not a score that individuals receive about themselves. It is not a rating system for employers. It is a research instrument — a tool for measuring a social phenomenon at population scale, with the rigour required to inform science, policy, and law.

It is also not complete. The pilot study is in progress. The validation pathway is defined but not yet finished. CROWN is transparent about the current stage of development because the credibility of the CDI depends on the same standard of honesty we apply to the evidence it measures.

The CDI pilot study is developed in consultation with the University of Geneva. To learn more about the methodology, visit CDI Methodology. To explore how CDI data can serve your organisation, see CDI Applications. To participate in the research, visit Participate.