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Employers and anti-Discrimination Measures in Europe: Good Practice and Bad Faith

  • John Wrench
Part of the Migration, Minorities and Citizenship book series

Abstract

The evidence presented in many of the chapters in this book is that discrimination and exclusion affect the employment opportunities of migrant workers and their descendants in various European countries in ways still not acknowledged by politicians, employers’ organisations, trade unions and others. For many observers, this points to the necessity of strengthening legislation against employment discrimination at a national level in each member state (although some believe that this is not going to happen without the encouragement which comes from an EU Directive against racial and ethnic discrimination, along the lines of that on sex discrimination). In recent years there has been a number of comparisons of national anti-discrimination legislation in European countries (Zegers de Beijl 1991; Forbes and Mead 1992; MacEwen 1995; Wrench 1996). However, this concluding chapter looks not at national measures against discrimination, but at measures at an organisational level. It first presents some examples of ‘good practice’ in various European countries. Then, given that such examples are still relatively rare in a European context, it sets out evidence which reveals the hostility, misunderstandings and conceptual confusions that frequently underlie resistance to the introduction of anti-discrimination measures in organisations by European employers.1 Next it explains some of the key differences in national context which help us to understand the contrasting ways that ‘anti-discrimination’ is perceived and effected in different countries. Finally, it considers whether the business case for such measures is adequate to stimulate their greater introduction, or whether there is an argument for less ‘vol-untarism’ and more compulsion as a means to getting employers to do more.

Keywords

Ethnic Minority Trade Union Racial Discrimination Equal Opportunity Equal Treatment 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© John Wrench 1999

Authors and Affiliations

  • John Wrench

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