Bibliographic record
Abstract
Commentators on market-oriented policy reform, e.g. John Williamson and Naomi Klein, have observed that radical policy change is often enacted in the wake of a “crisis” which is perceived to necessitate and justify the change. In section 2, I critically examine Williamson’s work and his analysis of the enabling conditions of policy changes based on the “Washington Consensus.” I also consider Klein’s work, and use, as a case study, the economic reforms in Chile in the 1970s. Whilst Williamson and Klein provide insights into the introduction of policy change, they do not offer plausible accounts of its persistence after a crisis has passed. Drawing on insights from behavioral economics, an explanation of persistence is offered (section 3). In section 4, the notion of “politics” contained in the work of proponents of market-oriented policy reform is scrutinized. I conclude with remarks on strategies for resisting market-oriented 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.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.006 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.003 | 0.026 |
| Scholarly communication | 0.010 | 0.015 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.012 | 0.017 |
| Insufficient payload (model declined to judge) | 0.010 | 0.003 |
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; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".