Language hierarchies and gender inequalities: the coverage of OpenAlex and the Web of Science

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Abstract
Large-scale bibliometric databases generally provide a selective and geographically-biased representation of scientific output. Given that these indexing biases reduce the likelihood of retrieving certain types of scientific production, it has been historically hard to assess the extent and characteristics of those excluded scholarly communications. Based on the Lattes platform, a unique data source with comprehensive coverage of Brazilian scholarly output, this paper assesses the coverage of two large-scale bibliometric databases: OpenAlex and Web of Science. Our findings identify the specific research areas underrepresented in both databases and assess the relation between publication language and indexing. Additionally, we examine gender-based differences in topic coverage, language, and indexing rates. Our results suggest that indexing biases disproportionately affect researchers focusing on topics of national relevance for Brazil through articles written in Portuguese. Given women’s overrepresentation in this group, our findings illustrate how indexing biases contribute to gender inequalities in science.
Funding Information
  • Social Science and Humanities Research Council of Canada Pan-Canadian Knowledge Access Initiative Grant (1007–23-0001)
  • Fonds de Recherche du Québec—Société et Culture (362184)
  • Fundação de Amparo à Pesquisa do Estado de São Paulo (2021/05823-1)

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