Governing Failure - Provisional Expertise and the Transformation of Global Development Finance
Bibliographic record
Abstract
Jacqueline Best argues that the changes in International Monetary Fund, World Bank and donor policies in the 1990s, towards what some have called the 'Post-Washington Consensus,' were driven by an erosion of expert authority and an increasing preoccupation with policy failure. Failures such as the Asian financial crisis and the decades of despair in sub-Saharan Africa led these institutions to develop governance strategies designed to avoid failure: fostering country ownership, developing global standards, managing risk and vulnerability and measuring results. In contrast to the structural adjustment era when policymakers were confident that they had all the answers, the author argues that we are now in an era of provisional governance, in which key actors are aware of the possibility of failure even as they seek to inoculate themselves against it. This book considers the implications of this shift, asking if it is a positive change and whether it is sustainable.This title was made Open Access by libraries from around the world through Knowledge Unlatched.
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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 | 0.005 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.024 |
| Scholarly communication | 0.010 | 0.010 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.004 | 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".