Gender and the Electoral Opportunity Structure in the
Bibliographic record
Abstract
We use multivariate analyses to test hypotheses concerning the electoral opportunity structure for women across a twenty-year period of Canadian provincial elections. We find that party, political context, and social variables affect the likelihood that a woman is elected to a provincial parliament. While similarities between U.S. state legislative elections and Canadian provincial elections are found, there are distinct differences across the two polities, especially concerning where women first made inroads in winning representation. While women first gained a beachhead in small amateur legislatures in rural states in the United States, in Canada they first won significant numbers of seats in metropolitan areas. We find there continues to be great differences across riding types with women doing much worse in rural ridings than either urban or metropolitan ridings. The implications of these differences for redistricting are considered. Canadian courts have generally been sympathetic to plans that insure representation of geographic communities of interest, even when this has meant overrepresentation of rural areas and underrepresentation of urban areas. We argue that a consequence of this policy is that Canadian provinces risk underrepresenting women, a nonterritorial community of interest.
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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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 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".