The prime minister's chief of staff: Comparing profiles and trends in Westminster democracies, 1990–2021
Bibliographic record
Abstract
Abstract Chiefs of Staff to heads of government hold a prominent position at the apex of the political executive. However, our knowledge of the personal and professional backgrounds of these unelected actors is surprisingly patchy. Not only is this an empirical gap, but it is also problematic as interactions between actors within political executives shape political decisions and ministerial operations. For this study, we present the most systematic dataset mapping the profiles of 56 chiefs of staff to prime ministers in four Westminster family countries from 1990 to 2021: Australia, Britain, Canada, and New Zealand. Their profiles are examined in relation to four concepts: (1) descriptive representation; (2) career de‐separation; (3) institutional (in)stability; and (4) the revolving door. The demographic results illustrate how prime ministers' offices attract individuals with certain characteristics more than others. In order to bolster these results, more research on the chief of staff role is needed to demonstrate how prime ministers exert power and use these staff to strengthen their capacity to govern.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".