Women's Legislative Underrepresentation: Enough Come Forward, (Still) Too Few Chosen
Bibliographic record
Abstract
Abstract No established liberal democracy has achieved sex balance in its national legislature. Scholars agree skewed candidate pools put forward by parties during elections cause sex-disproportionate seat distribution, but disagree as to whether disproportionality is caused by too few women aspirant candidates coming forward (supply) or party selectors preferring men (demand). This paper uses a multistage method to explore supply and demand during the British Labour party's candidate selection process. Rare data from three elections and 4622 aspirants allow for an unobstructed look inside the secret garden of politics and reveal the party is not fully feminized insofar that women aspirants are disproportionally filtered out of its selection process and are disproportionally underrepresented in its candidate pool. Testing reveals a lack of selector demand for women aspirants has a greater impact on women's underrepresentation than an undersupply of women aspirants, a finding which supports using sex quotas to level imbalanced candidate slates.
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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 | 0.007 | 0.026 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 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".