The missing piece: Measuring portfolio salience in Western European parliamentary democracies
Bibliographic record
Abstract
Abstract Although much has been discovered concerning the resources and preferences that parties take into the coalition formation game in Western European parliamentary democracies, we know a good deal less about the payoffs they receive. Portfolios constitute an important payoff, not just because they provide access to patronage, but because influence over policy decisions tends to go with control over the key government portfolios. It is easy to discover which and how many portfolios each party holds in any government, but what is missing is accurate measurement of the value or salience of these portfolios. Some attempts have been made to measure portfolio salience, but they have lacked one or more of the following properties: cross‐national scope, country‐specific measurement, coverage of the full set of postwar portfolios, measurement by multiple experts and measurement at the interval level. In this article, we present a new data contribution: a set of portfolio salience scores that possesses all of these properties for 14 Western European countries derived from an expert survey. We demonstrate the comprehensiveness and reliability of the ratings, and undertake some preliminary analyses that show what the ratings reveal about parliamentary government in Western Europe.
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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 | 0.005 | 0.018 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 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) | 0.002 | 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".