Bibliographic record
Abstract
Abstract Cabinets, Ministers, and Gender explores why men have been more likely than women to be appointed to cabinet, why gendered patterns of appointment vary cross-nationally, and why, over time, women’s inclusion in cabinets has grown significantly. The book is innovative in conceiving of cabinet formation as a gendered process governed by rules that empower and constrain presidents and prime ministers as selectors of cabinet ministers, and rules that prescribe, prohibit, and permit a range of criteria (experiential, affiliational, and representational) that qualify individuals for inclusion in cabinet. Focusing on seven country cases (Australia, Canada, Chile, Germany, Spain, the United Kingdom, and the United States) using three data sets—elite interviews, media data, and autobiographies—the book reveals the complex sets of rules governing cabinet formation in each country and demonstrates their gendered effects. The book shows how different types of rules empower and constrain selectors, and how these rules interact to create different opportunities and obstacles for women’s cabinet inclusion. The findings demonstrate how institutional change emerges from a complex iterative process through which political actors interpret and exploit ambiguity in rules to deviate from past practices of appointing mostly male cabinets. These selectors help to develop new rules about women’s inclusion, which constrain future leaders in assembling their cabinet. The authors coin the term “concrete floor” to capture the process by which minimum levels for women’s cabinet inclusion are established and become locked in over time, explaining how competing rules for cabinet appointments, changing norms, and women’s mobilization in political parties shape outcomes.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.007 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.000 | 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".