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Affirmative action, or positive discrimination favouring the members of marginalized populations, is a key policy approach for addressing group-based inequalities along ethnic, religious, and racial lines (e.g. horizontal inequalities). It is adopted in dozens of countries around the world in the areas of, for instance, university enrolment, public employment, and political representation as corrective social justice measures and means to mitigate ethnic conflict. Public debate over affirmative action is heated in many contexts, underscoring both potential benefits- for correcting historical injustices, supporting marginalized groups, and promoting equality-and potential harms, especially in terms of perceptions of fairness and societal conflict. In order to better evaluate such claims and to consider the appropriateness of affirmative action policies across diverse contexts, further information about these policies is needed. Although there is a large research literature on affirmative action, much of it focuses on a limited number of countries. This paper introduces a new Affirmative Action (AA) Dataset which speaks to this research gap. It provides detailed information in a standardized format on the design and modalities of AA policies, as well as on their adoption, implementation, and impact, and on associated controversies. The AA Dataset can thus be used to provide a systematic description of policies and, together with other cross-country datasets, to situate and examine these experiences comparatively, including in regional and global perspectives. Version 1, discussed in this paper, covers 53 countries.
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