Despite years of strategies and initiatives at both the EU and national levels, the majority of Roma people in Italy continue to face significant socioeconomic exclusion, a situation exacerbated by the coronavirus crisis. In response, Italy recently adopted a new National Roma and Sinti Equality, Inclusion, and Participation Strategy (2021–2030) to address their marginalisation, with a specific focus on their integration into the labour market. Taking this recent development as a starting point, this contribution offers a theoretical reflection on “unmaking” the marginality of Roma at both the research and policy levels, engaging with critical literature on ethnic minorities. It calls for a reflexive turn to prevent the (re)production of exclusionary categories and tackles emerging challenges to Roma inclusion in the labour market, such as the use of artificial intelligence in recruitment processes, which risks perpetuating ethnic stereotypes rather than reducing human bias.

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Unmaking Marginality: Future Directions in Achieving Roma Socioeconomic Inclusion

  • Veronica Riniolo

摘要

Despite years of strategies and initiatives at both the EU and national levels, the majority of Roma people in Italy continue to face significant socioeconomic exclusion, a situation exacerbated by the coronavirus crisis. In response, Italy recently adopted a new National Roma and Sinti Equality, Inclusion, and Participation Strategy (2021–2030) to address their marginalisation, with a specific focus on their integration into the labour market. Taking this recent development as a starting point, this contribution offers a theoretical reflection on “unmaking” the marginality of Roma at both the research and policy levels, engaging with critical literature on ethnic minorities. It calls for a reflexive turn to prevent the (re)production of exclusionary categories and tackles emerging challenges to Roma inclusion in the labour market, such as the use of artificial intelligence in recruitment processes, which risks perpetuating ethnic stereotypes rather than reducing human bias.