Bibliographic record
Abstract
STEM education research has repeatedly demonstrated how the STEM field is gendered masculine. But what does this mean? Is there anything about STEM subjects as such, that warrants labelling them masculine? This paper explores these questions through a meta-narrative, theoretical-critical review of previous review studies. The aim is to investigate how STEM subjects have been conceptualized as gendered in STEM education research, and what this means for feminist STEM educators who want to pluralize STEM education. Three ways of conceptualizing STEM subjects as gendered are identified: 1) The non-substantial association thesis; 2) The masculine epistemology of STEM; 3) STEM as difficult, asocial, and unhelpful. An over-arching finding is that most studies do not explore how STEM subjects emerge as gendered in the educational settings explored. Instead, gender is “imputed” into the analysis in ways that are not always productive for educators who want to pluralize STEM education through educational measures. Updated with minor typographical corrections: June 30, 2025.
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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 | 0.005 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.001 | 0.005 |
| Scholarly communication | 0.006 | 0.007 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".