Monitoring Racism

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Monitoring Racism and Data Comparability Theoret
ical reflection and practical implementation Pres
entation by Peter Fleissner, Head of Unit
Research and Networks EUMC, Vienna Rotterdam,
29 November 2001
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Overview of the presentation

• the RAXEN approach
• Approaches of data comparability
• approaches for improving comparability

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i. The RAXEN approach
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Approach 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

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The construction of RAXEN
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2000 RAXEN1 - Seven National Focal 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

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RAXEN1 Content of the Mapping Exercise

• 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 countries
• see http//eumc.eu.int

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2001 RAXEN2 data collection mapping 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)

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2001 RAXEN2 - 15 Focal Points

• Austria Austrian Academy of Sciences (AAS)
• Belgium Centre for Equal Opportunities and
  Opposition to Racism
• Denmark The Danish Board for Ethnic Equality
  (NEL)
• Finland Finnish League for Human Rights
• France 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)
• IrelandNational 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 House
• Portugal NUMeNA (Research center on human and
  social sciences) cooperating with the High
  Commission for Migration and Ethnic Minorities
• Spain Movement for Peace and Liberty (MPDL)
• Sweden EXPO Foundation
• United KingdomCommission for Racial Equality
  (CRE)

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2002 RAXEN3data collection analyses updating
Time Meetings Data Collection
Analyses Output/Results
1
1
1
Peer review of RAXEN2
Data collection in 4 areas and 15
countries publicly accessible
2
15 NFPs 15 National Studies in the 4 areas of
RAXEN2
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RAXEN3 Data Collection Data Collection
Update Mapping Exercises Update Rapid Response
Function Case Studies
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5
2002
6
7

• 15 national studies in
• employment
• racial violence
• education
• legislation

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Comparative studies in the four areas of RAXEN2
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10
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4 comparative studies on EU level in the above 4
areas
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Peer review of RAXEN3
Data collection results and in 15 countries
publicly accessible
Meeting Working Group on Methodology
Meeting with National Focal Points
Distribution of Results
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Frameworks for Monitoring

• 1. Natural Science
• Subject -gt Filter -gt 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

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Frameworks for Monitoring

• 2. Social Sciences
• Observer -gt Filter -gt
• Society lt- Reaction lt-
• 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
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Frameworks for Monitoring

• 3. RAXEN approach society is looking at itself
• EUMC (NFPs) Filter
• long term short term
• Observer -gt Filter -gt
• Society lt- Reaction lt-
• Meta-approach used, similarity to scientific
  approach
• Objects are complex systems with variable
  categories
• Political and cultural processes matter
• High sensitivity and relevance

Subjects
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ii. Approaches of data comparability
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Approaches towards Comparison

• Intended goals
• From a variety of indicators towards a harmonised
  approach of measurement
• From formal comparability towards comparability
  of content
• Comparability
• between 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

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Mosaic 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

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Rainbow 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

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Complementary 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

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Cluster 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

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Satellite 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)

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Harmonised approach

• This is the ideal goal of data collection (Max
  Webers 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

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iii. RAXEN approach for improving comparability
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Aggregation 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

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ABCDEFGIHJK
Layer 4 Full Coverage
A
Layer 3 Coarser Topology
ABCDEFG
IHJK
Layer 2 Finer Topology
DEFG
ABC
IH
JK
E
G
B
D
K
I
F
A
C
H
J
Layer 1 Finest Topology atomic level
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Examples Discrimination in the Labour Market

• should include
• informal
• direct (intentional)
• and
• structural (non-individual) forms
• and
• legal forms
• This presentation is strongly inspired by John
  Wrenchs paper Observations from European
  Comparative Research on Discrimination in
  Employment

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

• Racist discrimination
• Personal stereotypes about a social group
• I wont employ Indians because they are lazy
• B. Statistical discrimination
• Negative characteristics of a social group
• I wont employ Indians because they will go off
  and start their own business
• C. Societal discrimination
• Other people have negative attitudes
• I wont employ Indians because my customers
  wont like it

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Example 1 Discrimination in the Labour Market
Structural 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 discrimination
• Discrimination in one sphere produce
  discrimination in an other
• discimination in education can produce
  discrimination in employment

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Example 1 Discrimination in the Labour Market
Full Coverage and Coarser 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

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Example 2 Organizational measures against
discrimination in the Employment Sector

• A. Training the immigrants
• B. Making cultural allowances
• Equal opportunity policies
• Challenging racist attitudes
• Combating discrimination
• Diversity management

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Example 3 Legal discrimination in the
Employment Sector

• Try do give estimates on the percentages of the
  following categories of the working population
• A. Citizens in their own country
• Citizens of an EU country working here
• Non-EU denizens from third country with full
  rights to residency and work here
• Third country nationals with limited work permit
• Undocumented workers

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Thank you for your attention

• For comments please send an e-mail to
• peter.fleissner_at_eumc.eu.int
• See also my homepage
• http//www.arrakis.es/fleissner