Left–right party ideology and government policies: A meta–analysis
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. This paper summarizes how the partisan influence literature assesses the relationship between the left–right party composition of government and policy outputs through a meta–analysis of 693 parameter estimates of the party–policy relationship published in 43 empirical studies. Based on a simplified ‘combined tests’ meta–analytic technique, we show that the average correlation between the party composition of government and policy outputs is not significantly different from zero. A mutivariate logistic regression analysis examines how support for partisan theory is affected by a subset of mediating factors that can be applied to all the estimates under review. The analysis demonstrates that there are clearly identifiable conditions under which the probability of support for partisan theory can be substantially increased. We conclude that further research is needed on institutional and socio–economic determinants of public policy.
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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 | 0.009 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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