Bibliographic record
Abstract
Ravi Kanbur is one of the world's top specialists in development economics. Born in India and trained in England, at Cambridge and Oxford, he has taught at a number of universities in the United Kingdom and the United States, and has held various high-ranking positions with the World Bank. In 1998, he was asked to lead the team that would prepare the 2000/2001 issue of the World Development Report , the Bank's flagship annual publication, which would focus on “Attacking Poverty.” In June 2000, before the release of the report, Kanbur resigned over disagreements on the final version. At the time, some said that the divergences were minor. The head of the World Bank, James Wolfensohn, even argued that it was merely a dispute over the order of the chapters! Others suggested that much more was at stake and that the United States Treasury Secretary, Lawrence H. Summers, was himself involved in re-writing parts of the report. Whatever the case, the matter certainly appeared important to Kanbur. At a conference he addressed later the same year, he raised the question indirectly through a discussion of the fundamental disagreements that underlie global debates on poverty and development. Inside as well as outside international organizations, Kanbur explained, there are two broad, contending views on how best to attack poverty. The first view rallies most of the economists working in finance ministries, in international financial institutions, and in universities, and the second is primarily defended by those, not usually economists, who are associated with social ministries, aid agencies, and non-governmental organizations.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.476 | 0.317 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".