Bibliographic record
Abstract
Women, Men, and Elections sheds new light on gendered political behaviour by analysing the relationship between policy supply and gender gaps in vote choice across elections in the United States, Canada, Australia, New Zealand and multiple Western European countries.Rosalind Shorrocks argues that the electoral context, and specifically policy supply, are associated with the ways in which vote choice at election time is gendered. Using data from the Comparative Study of Electoral Systems and the Comparative Manifesto Project, Shorrocks finds that the extent to which men and women differ in their vote choice is contingent on the policy choices that parties off er to voters. Women and men respond to party policy positions in ways that are linked to both their gender and their socioeconomic position, producing variation in gendered political behaviour across elections, across countries, and across subgroups in society. Women, Men, and Elections offers a much- needed fresh perspective on our understanding of political behaviour, representation, and party competition. It serves as an excellent supplementary text for students and scholars of comparative politics, gender and politics, and political behaviour.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.014 | 0.002 |
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".