Lugar da mulher com deficiência é onde ela quer? : Estudo sobre a relação entre Gênero e Deficiência na Educação Superior
Bibliographic record
Abstract
The aim of the article is to map publications on gender and disability in higher education. Research linking gender and disability in higher education, particularly focusing on the university experiences of women with disabilities, is still in its early stages. The consequence of limited scientific dissemination is the invisibility of the barriers affecting these women, preventing them from entering, staying in, and completing university, which affects their future professional careers. Considering these aspects, this article is a literature review covering the period from 2018 to 2024. This review is an update of a previous mapping carried out from 2013 to 2017, in which the direct relationship between gender and disability in higher education did not appear as a study topic in publications from various countries such as Brazil, Spain, Colombia, Chile, Mexico, and Canada. In the current literature review, it was found that, although the number of identified publications is still incipient, there are already published texts on gender and disability in higher education, focusing on the experiences of women with disabilities. Even in an exploratory manner, these studies indicate that there are barriers associated with both gender and disability within the still ableist and sexist structure of higher education.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.007 | 0.027 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".