Informal Institutions and the Recruitment of Political Executives
Bibliographic record
Abstract
More women than ever before are being appointed cabinet ministers, yet academic scholarship is making slow progress when it comes to understanding and explaining how and why women reach the executive branch of government. Gender and politics scholarship continues to rely on theories developed to explain women’s presence in legislatures while the mainstream executive literature does not subject its categories and approaches to critical gendered analysis. This paper develops an alternative theoretical and methodological approach to account for and evaluate the presence of women in the executive branch. Drawing on institutionalist approaches, our focus is on identifying the rules which shape and determine ministerial opportunities and appointments. Given the relative absence of formal rules concerning cabinets, our primary aim is to capture the informal rules of appointment. Part of a broader project - see genderpower.net - one way we capture these practices and norms is through an analysis of media reports of the period from election day to the announcement of the ministerial line up (speculation) and the two week period following cabinet formation (reaction). The data presented in this paper relates to the speculation phase of the 2013 Australian election. Our analysis identifies a broad repertoire of informal rules which potentially inform decisions about ministerial appointments. These include stability and continuity, expertise and merit, and balancing representational norms such as region, upper and lower house, parties and gender. In this case, it is the norm of stability and continuity from the shadow cabinet to government which trumps all other appointment considerations.
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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 | 0.009 | 0.024 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.006 | 0.009 |
| Scholarly communication | 0.007 | 0.003 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.012 | 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".