The Need for a Deeper Theorisation on Race and Gender Equity in South African STEM:Drawing on Fraser's Participatory Parity, Decolonial, and Decolonial Feminist Insights
Bibliographic record
Abstract
In this chapter, key theories and concepts related to social justice and inequality in South African higher education are critically analysed and merged to find a new and unique perspective in assigning meaning to experiences of inequality and oppression amongst Black South African women in STEM. This is particularly important, given the pervasiveness of ongoing violence and oppression against Black women and other minority groups in developing contexts, as a result of the nuanced complexities associated with intersectional dynamics. Therefore, this chapter presents a novel conceptual framework to study marginalised women’s experiences in the sciences, as a means of refraining from simplistic perspectives. In doing so, it finds itself situated at a juncture between critical theory and a decolonial feminist paradigm in drawing on both strands of thought, specifically Fraser's perspectival dualism, as well as aspects of the coloniality of power, knowledge and gender. The framework first aims to distinguish between two similar yet distinct schools of thought, and second to demonstrate how both can be applied to scholarly and activism work in STEM, highlighting issues of equity and social justice.
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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 | 0.004 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.006 | 0.032 |
| Scholarly communication | 0.007 | 0.014 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.005 | 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".