1 Review of Dani Rodrik’s One Economics, Many Recipes (Princeton University Press, 2007)
Bibliographic record
Abstract
“The central economic paradox of our time is that ‘development economics ’ is working while ‘development policy ’ is not. On the one hand, the last quarter century has witnessed a tremendous and historically unprecedented improvement in the material conditions of hundreds of millions of people living in some of the poorest parts of the world. On the other hand, development policy as it is commonly understood and advocated by influential multilateral organizations, aid agencies, Northern academics, and Northern-trained technocrats has largely failed to live up to its promise. ” (p. 85). Thus begins one of the chapters of Dani Rodrik’s new book, One Economics, Many Recipes. In exploring this paradox, Rodrik lays out a broad critique of prevailing approaches to development policy, offers fresh ideas for countries seeking to improve their economic performance, and argues for important reforms in the World Trade Organization (WTO) to make room for those ideas. The book is actually a collection of Rodrik’s recent papers on growth, institutions, and globalization, but they constitute a remarkably coherent view of the development problem. A unifying theme of the book is that “government has a positive role to play in stimulating economic development beyond enabling markets to function well … In the words of public policy, lots of $100 bills are left lying on the sidewalk. The role of
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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.007 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.004 | 0.005 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.003 | 0.006 |
| Insufficient payload (model declined to judge) | 0.012 | 0.009 |
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".