Public Inquiries, Policy Learning, and the Threat of Future Crises
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 book is animated by a simple but very important question. Can post-crisis inquiries deliver effective lesson-learning which will reduce our vulnerability to future threats? Conventional wisdom suggests that the answer to this question should be an emphatic no. Inquiries are regularly vilified as costly wastes of time that illuminate very little and change even less. This book, however, draws upon evidence from an international comparison of post-crisis inquiries in Australia, Canada, New Zealand, and the United Kingdom to show that, contrary to conventional wisdom, the post-crisis inquiry is an effective means of learning from disaster and that they consistently encourage policy reforms that enhance our resilience to future threats. This evidence is accompanied by a re-booted conceptualization of the public inquiry, which better recognizes the complexity of the modern state, the challenges of policy learning within it, and contemporary forms of public policy scholarship.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.007 |
| 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