(Re)Thinking think tanks in the age of policy labs: The rise of knowledge‐based policy influence organisations
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 The idea of ‘think tanks’ is one of the oldest in the policy sciences. Although the topic has been studied for decades, recent works dealing with advocacy groups, policy and behavioural insight labs and into the activities of think tanks themselves have led to discontent with the definitions used in the field, and especially with the way the term may obfuscate rather than clarify important distinctions between the different kinds of knowledge‐based policy influence organisations (KBPIO) operating in the contemporary policy landscape. In this paper, we examine the traditional and current definitions of think tanks utilised in the discipline and point out their weaknesses. We then develop a new framework to better capture the variation in the kinds of knowledge‐based organisations which operate in many sectors.
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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 | 0.002 | 0.002 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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