ReviewPloS one2023
Gender gaps in Mathematics and Language: The bias of competitive achievement tests.
Review in PloS one, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
2 citing papers in PubMed, 16 citations in OpenAlex.
- Convolutional neural network and AI technology for colleges and universities students' achievement performance prediction.Scientific reports · 2026Article
- Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors at 3 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
This research paper examines the extent to which high-stakes competitive tests affect gender gaps in standardized tests of Mathematics and Language. To this end, we estimate models that predict students' results in two national standardized tests: a test that does not affect students' educational trajectory, and a second test that determines access to the most selective universities in Chile. We used data from different gender twins who took these tests. This strategy allows us to control, through household fixed effects, the observed and unobserved household characteristics. Our results show that competitive tests negatively affect women. In Mathematics, according to both tests, there is a gender gap in favor of men, which increases in the university entrance exam, especially for high-performance students. As the literature review shows, women are negatively stereotyped in Mathematics, so this stereotype threat could penalize high-achieving women, that is, those that go against the stereotype. In Language tests, women outperform men in the standardized test taken in high school, but the situation is reversed in the university entrance exam. From our analysis of Chilean national data, we find no evidence that the gender effect observed in the competitive test depends on the students' achievement level. Following the literature, this gender gap may be linked to women's risk aversion, lower self-confidence, lower preference for competition, as well as the effect of answering a test under time pressure.
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What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.