Who are The Political Parties’ Ideas Factories? On Policy Analysis by Political Party Think Tanks
Bibliographic record
Abstract
This chapter explores the available literature on party study centres in an effort to develop a heuristic typology that classifies different types of party think tanks worldwide. Although political party think tanks do sometimes take different shapes within countries, these differences are usually less outspoken than those differences across countries. The chapter particularly focuses on these cross-country trends. Our empirical input comes from secondary literature about a wide variety of countries including Australia, Flanders, Wallonia, Brazil, Canada, Germany, Japan, the Netherlands, Taiwan, the United States and the European Union. Without claiming exhaustiveness, the cases under study are sufficiently representative of the variety in political systems of modern democracies that exist worldwide. The chapter addresses the autonomy of political party think tanks vis-à-vis their mother party, and considers the various functions fulfilled by these organizations. It combines the two typologies and critically reflects on the meaning of political parties' ideas factories.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
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; both teacher heads agree on what is shown here.
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".