Monitoring RacismMonitoring Racismand and

Data ComparabilityData Comparability

Theoretical reflection and practical implementation

Presentation by Peter Fleissner, Head of Unit “Research and Networks”

EUMC, Vienna

Rotterdam, 29 November 2001

2

            

Overview of the presentationOverview of the presentation

i. the RAXEN approach

ii. Approaches of data comparability

iii. approaches for improving comparability

            

i. The RAXEN approach i. The RAXEN approach

4

            

Approach for building up RAXENApproach for building up RAXEN

• Pragmatic approach because of unclear situation on data availability

• Learning exercise and flexible response to problems

• Spiral approach to deal with empirical and theoretical issues on the next higher level over time

• Linguistic context to be analysed

5

            

EUMC

The construction of RAXENThe construction of RAXEN

6

            

2000: RAXEN1 - Seven National Focal 2000: RAXEN1 - Seven National Focal Points doing the “Mapping Exercise”Points doing the “Mapping Exercise”

• Austria: Austrian Academy of Sciences• Finland: Finnish League for Human Rights• Germany: Regional Association for Questions

on Foreigners (RAA Berlin)• Greece: Information Centre for Racism,

Ecology and Non-Violence• Ireland: National Consultative Commission

on Racism and Interculturalism and Equality Authority

• Netherlands: Anne Frank House• UK: Commission for Racial Equality

Contracts already expired

7

            

RAXEN1: Content of the Mapping RAXEN1: Content of the Mapping ExerciseExercise

• contact data for organisations active in the field of racism, xenophobia and anti-Semitism, and general information on their objectives and field of activity

• what activities ("best practice") each organisation has carried out since 1995

• what data have been collected by each organisation in the course of its activities

• what publications have been produced by each organisation

Available on the Internet for seven countriessee: http://eumc.eu.int

8

            

2001 RAXEN2: data collection + 2001 RAXEN2: data collection + mapping exercise in missing countriesmapping exercise in missing countries

Three different categories of information in the areas of racism, xenophobia and anti-Semitism• Negative acts of violence and discrimination• “Good practices”, initiatives to prevent racism, • Background information related to minorities and migrants

In five areas for data collection (2001)• Employment Sector• Racial violence• Education• Legislation• Violence/changed attitudes towards Muslim communities (Rapid

Response Function)

9

            

2001: RAXEN2 - 15 Focal Points2001: RAXEN2 - 15 Focal PointsAustria: Austrian Academy of Sciences (AAS)Belgium: Centre for Equal Opportunities and Opposition to RacismDenmark: The Danish Board for Ethnic Equality (NEL)Finland: Finnish League for Human RightsFrance: Agency for the Development of Intercultural Relations (ADRI)Germany: European Forum for Migration Studies (EFMS)Greece: Information Centre for Racism, Ecology, Peace and Non-Violence

(Infocenter)Ireland:National Consultative Commission on Racism and Interculturalism

(NCCRI) + Equality Authority (EA)Italy: Co-operation for the Development of Emerging Countries (COSPE)Luxembourg: Association for the Support of Immigrant Workers (ASTI)The Netherlands: Anne Frank HousePortugal: NUMeNA (Research center on human and social sciences)

cooperating with the High Commission for Migration and Ethnic MinoritiesSpain: Movement for Peace and Liberty (MPDL)Sweden: EXPO FoundationUnited Kingdom:Commission for Racial Equality (CRE)

10

            

2002:2002: RAXEN3RAXEN3data collection + analyses + updatingdata collection + analyses + updating

Meeting: Working Group on Methodology

Meeting with National Focal Points

Distribution of Results

Data collection in 4 areas and 15 countries

publicly accessible

15 national studies in

employmentracial violenceeducationlegislation

4 comparative studies on EU levelin the above 4 areas

Data collection results and in 15 countries publicly accessible

2002

111

2

3

4

5

6

7

8

9

10

11

12

Peer review of RAXEN2

RAXEN3:

Data CollectionData Collection Update

Mapping Exercises UpdateRapid Response Function

Case Studies

Peer review of RAXEN3

15 NFPs

15 National Studies in the 4 areas of RAXEN2

Comparative studies in the four areas of RAXEN2

Time Meetings Data Collection Analyses Output/Results

11

            

Frameworks for MonitoringFrameworks for Monitoring

1. Natural ScienceSubject -> Filter -> Object

• Objective world assumed, object and its properties are constructed by science

• Properties maybe qualitative or quantitative, space/time related

• Distance from the Object implied:– Classical physics: no influence by observer– Quantum physics: measurement process influences

result, but in a well defined and understood way.

• Some kind of interest involved• All power on the part of the observer

12

            

Frameworks for MonitoringFrameworks for Monitoring2. Social Sciences

Observer -> Filter -> Society <- Reaction <-

• “Object” is of similar type as the observer • Societal construction of “object” and its

properties• Properties maybe qualitative or quantitative• Interaction/negotiation on properties

possible • Power relations important

Subjects

13

            

Frameworks for MonitoringFrameworks for Monitoring3. RAXEN approach: “society is looking at itself”

EUMC (NFPs) Filterlong term short term

Observer -> Filter -> Society <- Reaction <-

• Meta-approach used, similarity to scientific approach• Objects are complex systems with variable categories• Political and cultural processes matter• High sensitivity and relevance

Subjects

            

ii. Approaches of data comparabilityii. Approaches of data comparability

15

            

Approaches towards ComparisonApproaches towards ComparisonIntended goals

From a variety of indicators towards a harmonised approach of measurement

From formal comparability towards comparability of content

Comparabilitybetween the poles of “equality” (latin and old High German

“par” = “pair”) and “difference”, fixed at a “degree of similarity”

Various models, e.g. big differences

– Mosaic approach– Rainbow approach– Complementary approach– Cluster approach– Satellite approach– Harmonised approach small differences

16

            

Mosaic approachMosaic approach

• Each indicator is qualitatively different from the other (different dimension)

• There is a need to explicitly report not only the empirical findings, but also the definitions of the indicator applied

• No or only small sorting/ordering possibilities of indicators used

• Theoretical background needed to be able to assess results

17

            

Rainbow approachRainbow approach

• Each indicator is different from the other

• But the indicators can be sorted/ordered by some (quality) criteria

• Still there is a need to explicitly report not only the empirical findings, but also the definitions of the indicator applied

• Theoretical background/explanation needed to be able to assess results

18

            

Complementary approachComplementary approach

• Two or more indicators refer to the same issue

• The differ in their view on the event• Usually there are different interest groups

reporting (local police, federal police, NGOs), and they have different interpretation

• Make the various views and sources explicit

• Report data from all the sources identified

19

            

Cluster approachCluster approach

• There exist clusters of countries where the same definitions of indicators are applied

(e.g. indicator1 for {c1,c2,c3}; indicator2 for {c4,c5,c6,c7}; indicator3 for {c8}; indicator4 for {c9} )

• Make the definition of the various indicators and sources explicit

• Comparability is possible within the sets of countries with identical indicator

20

            

Satellite approachSatellite approach

• This is an approach used by EUROSTAT in economics

• In a specific area there are some core indicators, which use identical definitions (obligatory part of the reporting procedure)

• In addition to that data are collected which reflect special aspects of the country, region etc. (voluntary part of the reporting procedure)

21

            

Harmonised approachHarmonised approach• This is the ideal goal of data collection (Max

Weber’s “Idealtyp”)• E.g. backed up by the anti-discrimination

directives the Member States developed identical reporting frameworks on racial crimes and all their subcategories.

• There are no longer qualitative differences between the results, only quantitative ones.

• Still it might be questioned if the connotations of the categories used do not have a different location in the cultural frameworks of the various regions or Member States of the European Union

            

iii. RAXEN approach for improving iii. RAXEN approach for improving comparabilitycomparability

23

            

Aggregation schemeAggregation scheme

Preconditions• Atoms describe finest partition of

indicators in the area• Atoms do not overlap• Area is fully covered by atoms

Aggregation level used depends on the availability of data

24

            

AB

CJ

KI

H

G

F

E

D

ABC

A

Layer 1: Finest Topology – atomic level

DEFG IH JK

ABCDEFG IHJK

ABCDEFGIHJK

Layer 2: Finer Topology

Layer 3:

Coarser Topology

Layer 4: Full Coverage

25

            

Examples:Examples: Discrimination in the Labour Discrimination in the Labour MarketMarket

should include • informal

– direct (intentional)and

– structural (non-individual) formsand

• legal formsThis presentation is strongly inspired by John

Wrench’s paper “Observations from European Comparative Research on Discrimination in Employment”

26

            

Example 1: Discrimination in the Labour Market Example 1: Discrimination in the Labour Market Direct (intentional) formsDirect (intentional) forms

A. Racist discrimination Personal stereotypes about a social group“I won’t employ Indians because they are lazy”

B. Statistical discriminationNegative characteristics of a social group“I won’t employ Indians because they will go off and

start their own business”

C. Societal discriminationOther people have negative attitudes“I won’t employ Indians because my customers won’t

like it”

27

            

Example 1: Discrimination in the Labour MarketExample 1: Discrimination in the Labour Market Structural formsStructural forms

D. Indirect discrimination “Neutral” recruitment practices discriminate ethnic group

“Recruiting employees through their family connections”

E. Past-in-present discrimination“Neutral” practices have negative effect because of the past

“Recruitment of an ethnic group to inferior jobs goes on in the present”

F. Side effect discriminationDiscrimination in one sphere produce discrimination in an other

“discimination in education can produce discrimination in employment”

28

            

Example 1: Discrimination in the Labour MarketExample 1: Discrimination in the Labour Market Full Coverage andFull Coverage and Coarser TopologyCoarser Topology

• ABCDEF Discrimination in the Labour Market

• ABC Direct (intentional) forms of discrimination in the labour market

• DEF Structural (non-individual) forms in the labour market

29

            

Example 2: Organizational measures against Example 2: Organizational measures against discrimination in the Employment Sectordiscrimination in the Employment Sector

A. Training the immigrants

B. Making cultural allowances

C. Equal opportunity policies

D. Challenging racist attitudes

E. Combating discrimination

F. Diversity management

30

            

Example 3: Legal discrimination Example 3: Legal discrimination in the Employment Sectorin the Employment Sector

Try do give estimates on the percentages of the following categories of the working population

A. Citizens in their own country

B. Citizens of an EU country working here

C. Non-EU denizens from third country with full rights to residency and work here

D. Third country nationals with limited work permit

E. Undocumented workers

            

Thank you for your attentionThank you for your attention

For comments please send an e-mail topeter.fleissner@eumc.eu.int

See also my homepagehttp://www.arrakis.es/~fleissner