Occluded Topics: The hidden half of Brazilian research

Large-scale bibliometric databases generally provide a selective and geographically-biased representation of scientific production. Taking Brazil as a case study, this paper quantifies the extent of research output excluded from the Dimensions’ database, using the national curriculum database, the Lattes Platform. Our findings identify the specific research areas underrepresented in Dimensions and assess the relation between publication language and indexing Additionally, we examine gender-based differences in topic coverage, language, and indexation rates. Our results suggest that indexing biases disproportionately affect researchers focusing on locally relevant topics through articles that are written in Portuguese. Given women's overrepresentation in this group, our findings illustrate how indexing biases contribute to gender inequalities in science.