Bibliographic record
Abstract
Historically, men have been more likely to be appointed to governing cabinets, but gendered patterns of appointment vary cross-nationally, and women's inclusion in cabinets has grown significantly over time. This book breaks new theoretical ground by conceiving of cabinet formation as a gendered, iterative process governed by rules that empower and constrain presidents and prime ministers in the criteria they use to make appointments. \n \nPolitical actors use their agency to interpret and exploit ambiguity in rules to deviate from past practices of appointing mostly men. When they do so, they create different opportunities for men and women to be selected, explaining why some democracies have appointed more women to cabinet than others. Importantly, this dynamic produces new rules about women's inclusion and, as this book explains, the emergence of a concrete floor, defined as a minimum number of women who must be appointed to a cabinet to ensure its legitimacy. \n \nDrawing on in-depth analyses of seven countries (Australia, Canada, Chile, Germany, Spain, the United Kingdom, and the United States) and elite interviews, media data, and autobiographies of cabinet members, Cabinets, Ministers, and Gender offers a cross-time, cross-national study of the gendered process of cabinet formation.
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How this classification was reachedexpand
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 teacher head, 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".