Accounting for the Role of Policy in the Underrepresentation of Women in Computer Science
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Since the 1990s, a great deal of effort has been toward improving female participation in computing. Yet the numbers in North America haven't budged: women continue to make up 18\% of CS majors. Current efforts and research focus on societal, cultural, and psychological reasons for this underrepresentation. I argue that the political dimension also needs to be considered both in terms of why women are underrepresented and how to change it. I have found that admissions policies have a profound effect on how many women study undergraduate CS. I've also observed that diversity is not being considered in mainstream CS department policymaking, and ``women's issues'' are expected to be solved by women's groups. And in the women's spaces, I've observed a focus on individual career advancement (``Lean In'') rather than a push for political, collective action.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it