Exporting Good Governance: Temptations and Challenges in Canada's Aid Program
Bibliographic record
Abstract
Can good governance be exported? International development assistance is more frequently being applied to strengthening governance in developing countries, and in Exporting Good Governance: Temptations and Challenges in Canada's Aid Program, the editors bring together diverse perspectives to investigate whether aid for good governance works. The first section of the book outlines the changing face of international development assistance and ideas of good governance. The second section analyzes six nations: three are countries to which Canada has devoted a significant portion of its aid efforts over the past five to ten years: Ghana, Vietnam, and Bangladesh. Two are newer and more complex fragile states, where Canada has engaged: Haiti and Afghanistan. These five are then compared with Mauritius, which has enjoyed relatively good governance. The final section looks at challenges and new directions for Canadas development policy. Co-published with the Centre for International Governance Innovation
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".