ethnic statistics : fighting against discrimination patrick simon – ined social statistics and...

Ethnic statistics : Fighting against discrimination

Patrick Simon – INED

Social Statistics and Ethnic diversityShould we count, how and why ?

CIQSS and INEDMontréal, 6-8 december 2007

SSED 6-8 december 2007

Outline

Statistics and discrimination : what are we talking about ?

Antidiscrimination Policies and the use of statistics

How to measure discrimination ? Categorisation and methodological

issues


What is discrimination ? Legal definition : unfair treatment, could be direct or

indirect

EU “race” directive 2000 : “indirect discrimination shall be taken to occur where an apparently neutral provision, criterion or practice would put persons of a racial or ethnic origin at a particular disadvantage compared with other persons, unless that provision, criterion or practice is objectively justified by a legitimate aim and the means of achieving that aim are appropriate and necessary.”

Sociological : explicit and implicit prejudice, systemic discrimination

Economics : discrimination by taste and statistical discrimination


Why measuring discrimination ? Antidiscrimination laws and policies are making

an extensive use of statistics The indirect discrimination concept and the

related action schemes, are intrinsically linked to statistics by their rationale and objectives. Discrimination can be defined as “disparate treatment”, “underrepresentation”, statistical discrepancies, gaps …

Groups,more than individuals, are targeted by indirect discrimination


Reasons and provisions for monitoring

Statistics provide facts on discrimination : they simply make discrimination as real social facts

Awareness of public opinion and decision makers : discrimination is not an adverse and rare situation

Measuring the extent and impact of discrimination Identifying targets, setting goals, evaluating

policies Legal requirements Equality policies : monitoring is not only a tool, but

the policy itself Providing proofs in lawsuits


Antidiscrimination policies in employment

Equal Opportunity Act (US, 1972)– EEOC founded by the Civil Rights Act (1964)– OFCCP installed by the EO 11246 (1965)

Employment equity (Canada,1986 and 1996)– Women, visible minorities, first nation and disabled persons

Equal Opportunity Policy (UK, 1987/ RRA 1976 and 2000)

Workplace relations act (Australia,1996)– Gender discrimination– Religion and sexual orientation

National Charter on public service in a culturally diverse society (Australia, 1999)

Wet SAMEN (labour market participation, Netherlands, 1998-2003)


Monitoring systems Statistics gathered by a central system (census or

register of population) Registration in administrative files (compulsory or

voluntary) Monitoring by employers or public authorities :

accountability and awarness Situational Testing Lawsuits collection, complaint registers and reports of

activity Reporting, enforcement and controls


Building indicators in equal opportunity schemes

The “four-fifth rule” and the Job Area Acceptance Range (US, EEOC and OFCCP)

Impact ratio analysis, underutilization as a double standard deviation (US, EEOC and OFCCP)

Rating company’s performance in equal opportunities (Canada) :– representation of the designated groups– professional concentration– wage differentials– recruitment, promotions and terminations


Ethnic and racial classifications

For policy purpose : most of the categories are specified by laws and policies (guidelines and standards, CRE, UK; standards of classification, OMB, US)

In censuses : – huge disparities of categorisation in a cross-national

perspective– Ethnicity and race are optional topics– Each country have its own list of categories : a reflection of

the history and of the political model of integration (slavery, colonisation, immigration, national minorities)

How to disentangle race and ethnicity ?


Recommandations of UN for the next census round (2nd revision 2006)

“Ethnicity can be measured using a variety of concepts, including ethnic ancestry or origin, ethnic identity, cultural origins, nationality, race, colour, minority status, tribe, language, religion or various combinations of these concepts.(…) The subjective nature of the term (not to mention increasing intermarriage among various groups in some countries, for example) requires that information on ethnicity be acquired through self-declaration of a respondent and also that respondents have the option of indicating multiple ethnic affiliations. “


Legal, political and methodological issues behind ethnic categorisation

Identity politics and the « Diversity’s Buzz » : a new approach Post 1945 illegitimacy of “race” and racial categories Revealing racial and ethnic divisions or keeping them in the

shade : universalism, uniformity and multiculturalism Different objectives : recognition of identities, targeting « groups

at risks » of discrimination and dealing with the memory of slavery and the post-colonial debate

A methodological challenge : – Grasping the subjective definition of the self

– Moving identities : reliability issues Data protection and privacy : confusions between misuses and

sensitive data


Ethnicity and Race in Census around 2000

87 countries in 138 are collecting data on « ethnicity » (A.Morning, 2005)

Most common terminology (a selection) : – Ethnicity 49– Nationality 20– Race 13– Color 2– Ancestry/origin 6

In 42 countries of the Council of Europe, ethnicity/nationality is collected in 22 countries, religion in 24 and country of birth of the parents in 6 (Simon, 2007).


Methods of collection Self-declaration :

– Open question (11 countries)– Pre-coded list of categories (11 countries)

Third party identification – Employers in the US– Claims from Roma organisations in central and east

Europe Group recognition

– Aboriginal in Australia, American indians in the US and suprem court decision on « race » in the US (Mallone case)

By proxy– Country of birth and citizenship of parents, spoken or

mother language, name and surname


Methodological issues

Discrepancies between benchmark and monitoring by operators

Statistical assessment and the size of the « establishements » or services to be screened

Contradictions between recognition of identities and targeting « groups at risks » of discrimination

Moving identities : reliability issues between sources and through time

Simple indicators for a complex phenomenon (basic indexes vs multivariate analysis : the case for estimating residual discrimination)


Conclusion An international framing to combat discrimination, but no

common tools There is still a debate on the need to measure

discrimination, how to do it, and the kind of data that should be collected

Categorisation is the main issue The continental Europe’s choice : the country of birth of

parents as a proxy for groups at risk of discrimination Introduction in the next Labour force survey (2008) and a

recommendation by Eurostat A violent controversy about a survey on discrimination in

France

ethnic statistics : fighting against discrimination patrick simon – ined social statistics and...

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