Evaluation in Transition: The Promise and Challenge of South-South Cooperation
Bibliographic record
Abstract
Abstract: In order for the evaluation field to ensure its salience over the next decade, high-profile areas of work have to be sought where evaluative practices are underexplored or undervalued yet can help inspire and accelerate urgently needed transformations while also advancing evaluation theory and practice. This article highlights one such opportunity, offered by South-South cooperation (SSC), an increasingly powerful force in international development yet overshadowed by the frameworks, narratives, and approaches of North-South cooperation (NSC), better known as international development cooperation or development aid. The values, principles, achievements, and challenges that define SSC are seldom discussed at evaluation events or in the evaluation literature, and development evaluation continues to be shaped largely by theories from the Global North and by North-South interactions, despite the growing prominence of SSC and the Global South in world affairs. This article is dedicated to creating awareness of the current situation by highlighting how more intensive engagement with the unique aspects and underexplored opportunities of SSC might help shift paradigms and practices in evaluation, especially but not only in the Global South.
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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 | 0.188 | 0.141 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.011 | 0.034 |
| Scholarly communication | 0.024 | 0.018 |
| Open science | 0.002 | 0.024 |
| Research integrity | 0.005 | 0.010 |
| 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".