Organising for donor effectiveness: An analytical framework for improving aid effectiveness policies
Bibliographic record
Abstract
To what extent do donor organisational factors impinge on the search for more effective foreign aid? Donors have lagged behind aid recipients in adhering to the principles of aid effectiveness. Explaining the reasons for this demands greater awareness of organisational attributes within donor entities. Donor organisational features that have a credible positive impact on aid effectiveness are identified as the analytical components of donor effectiveness. To date, there have been limited attempts to relate donor organisational factors to aid effectiveness goals. This article elaborates on a number of such relationships based on an empirical examination of donor dynamics in Norway, the UK and Canada. Organisational features identified as contributors to aid effectiveness include a conducive political environment, a powerfully mandate ministry of development, a high-level policy statement on development and bounded professional discretion. Donor effectiveness provides an important lens through which to build a robust post-Busan global partnership.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".