The Role of Feminist Standpoint and Intersectionality Epistemologies in Providing Insights into the Causes of Gender Disparity in Higher Education
Bibliographic record
Abstract
Higher education plays a critical role in society’s development, particularly in the current era of globalization in which knowledge-based innovations are critical for development. However, women’s underrepresentation in higher education remains a persistent issue of concern, particularly, in sub-Saharan Africa. The gender gap in higher education is created by complex interconnected sets of deep-rooted factors. A clear understanding of the underlying causes of gender inequality in higher education is necessary to develop effective interventions to overcome this disparity. Feminist standpoint and feminist intersectionality epistemologies have been used to provide insights into gender disparities in higher education. Drawing on existing published literature, I will discuss the conceptual and theoretical frameworks of these two feminist epistemologies and explore the methodological implications of these epistemologies for critically examining gender disparities in higher education in the context of sub-Saharan Africa.
 Keywords: epistemology, feminism, gender, higher education, intersectionality
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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 | 0.026 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.008 | 0.006 |
| Science and technology studies | 0.011 | 0.093 |
| Scholarly communication | 0.017 | 0.022 |
| Open science | 0.002 | 0.015 |
| Research integrity | 0.005 | 0.008 |
| 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".