Global Policy Models, Globalizing Poverty Management: International Convergence or Fast‐Policy Integration?
Bibliographic record
Abstract
Abstract The millennial ‘rediscovery’ of poverty as a global challenge, by the United Nations and other multilateral agencies, was accompanied by the (rather premature) announcement that a ‘global consensus’ had been established on the philosophy and policy of poverty alleviation. The paper presents a critical account of the origins and character of this global consensus on poverty alleviation, which is based on a family of supply‐side, ‘human‐capital’ approaches that incentivize risk‐taking, investment‐oriented behavior on the part of poor households. It concludes that such global models of poverty management represent more than carriers of best practices or conveyors of multilateral policy accords; they epitomize a form of ‘fast policy’ integration in which policy problems themselves are effectively redefined (or ‘reformatted’) through preconstituted strategies, with outcomes that nevertheless remain geographically uneven and deeply contradictory.
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 | 0.020 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.003 | 0.024 |
| Scholarly communication | 0.016 | 0.023 |
| Open science | 0.002 | 0.019 |
| Research integrity | 0.005 | 0.008 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".