Science for whom? The influence of the regional academic circuit on gender inequalities in Latin America is a research paper published in Journal of the Association for Information Science and Technology (2024). On theSindex it has a DataRank of 0.351. It has been cited 8 times, with 4 citing works in its 1-hop citation network.
AbstractThe Latin‐American scientific community has achieved significant progress towards gender parity, with nearly equal representation of women and men scientists. Nevertheless, women continue to be underrepresented in scholarly communication. Throughout the 20th century, Latin America established its academic circuit, focusing on research topics of regional significance. Through an analysis of scientific publications, this article explores the relationship between gender inequalities in science and the integration of Latin‐American researchers into the regional and global academic circuits between 1993 and 2022. We find that women are more likely to engage in the regional circuit, while men are more active within the global circuit. This trend is attributed to a thematic alignment between women's research interests and issues specific to Latin America. Furthermore, our results reveal that the mechanisms contributing to gender differences in symbolic capital accumulation vary between circuits. Women's work achieves equal or greater recognition compared to men's within the regional circuit, but generally garners less attention in the global circuit. Our findings suggest that policies aimed at strengthening the regional academic circuit would encourage scientists to address locally relevant topics while simultaneously fostering gender equality in science.
FAIR checklist signals are shown for context only and do not affect DataRank scoring.
Base Score Contribution
0.330
From this paper's citation signal
Citation Network Contribution
0.0210
From 2 citing papers with measurable signal
Ranked by citation count — the same ordering the engine uses when summing log1p(Cq) over citers.
DataRank blends this paper's own citation count with the influence of the papers that cite it. Here, roughly 94% comes from its base citations and 6% from the citation network (2 citing papers contributed measurable signal).
Citers are pulled from OpenAlex sorted by cited_by_count:descand capped per paper, so when the cap binds we keep the highest-signal references and the score is reproducible across reruns.
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