Appraising the Epistemic Performance of Social Systems: The Case of Think Tank Evaluations
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 article elaborates a conceptual framework to systematize the epistemic evaluation of social systems. This framework can be used to structure an evaluation or to characterize and assess existing ones. The article then uses the framework to assess four representative evaluations of think tanks. This meta-evaluation exemplifies how the framework can play its structuring role. It also leads us to general conclusions about the existing evaluations of think tanks. Most importantly, by focusing on the organizational level, existing evaluations miss factors that are situated at the network and ecosystemic levels and that significantly determine how well think tanks serve society in producing and disseminating knowledge relevant to public policy. This conclusion suggests the need for epistemic evaluations of think tank ecosystems.
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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 | 0.001 | 0.000 |
| 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 | 0.000 |
| 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