Potential Focusing Projects and Policy Change
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
Why do policies change dramatically? Most prominent theories and many empirical studies of policy change address that question with attention to external shocks to policy systems or focusing events. These shocks or events are usually described as unplanned, unpredicted jolts such as global crises or natural disasters. I assert a role for focusing projects. These planned activities continue traditional priorities in an issue but do so to a degree perceived as excessive by enough people to shatter seemingly stable policy systems. I then propose a theoretical framework to explain the varying impacts from such projects. The framework uses two dimensions: one that accounts for the mobilization of pro‐change forces and one that assesses policy learning by members of pro‐ status quo coalitions. I examine this framework in the context of changes to dam‐building policies in four diverse political settings: United States, Australia, Canada, and China. I find intriguing similarities between the focusing projects in these different contexts but also considerable variation in the extent to which they produce policy change.
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 | 0.002 | 0.000 |
| 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