Parliamentary Debate and Job Market Signaling in Westminster Systems
Bibliographic record
Abstract
ABSTRACT This article examines parliamentary speech as a job‐market signal in Westminster systems, where ministers are selected from the legislature under conditions of informational asymmetry. Building on signaling theory, it argues that party leaders use visible, effortful parliamentary activities—such as frequent speechmaking—as proxies for latent qualities like political aptitude and commitment. Using data from Australia, Canada, Ireland, and the UK, it finds that a one standard deviation increase in first‐term speech rate is associated with a 27% [95% CI: 19, 36] increase in the risk of ministerial promotion. The relationship is role‐specific (predicting ministerial but not whip appointments) and robust to confounds such as elite education, gender, and prior experience. These findings contribute to the literatures on ministerial selection and parliamentary debate by reframing parliamentary speech as a strategic investment. They also challenge critical conceptions of the Westminster model by showing how fused executive–legislative dynamics shape ministers' career incentives and understanding of institutional design.
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 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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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".