The portfolio allocation paradox: An investigation into the nature of a very strong but puzzling relationship
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract Perhaps the strongest empirical finding in political science is ‘Gamson's Law’: the near‐perfect relationship that exists in parliamentary systems between a coalition party's seat contribution to the government and its quantitative allocation of cabinet portfolios. Nevertheless, doubts remain. What would happen if the salience or importance of the various portfolios was also taken into account? Should it not be the case that payoffs correspond with bargaining power rather than seat contributions? And perhaps most significantly, would addressing these issues produce evidence that the parties designated to form governments extract disproportionately large payoffs for themselves, as predicted by ‘proposer’ models of bargaining? Utilizing the results of a new expert survey of portfolio salience in 14 Western European countries, the authors of this article explore each of these questions. Their basic finding is that salience‐weighted portfolios payoffs overwhelmingly mirror seat contributions, contra proposer models and any other models based on bargaining power. The article concludes with a discussion of the implications for formal models of bargaining.
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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 | 0.014 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 it