Rising Donors and the New Narrative of ‘South–South’ Cooperation: what prospects for changing the landscape of development assistance programmes?
Bibliographic record
Abstract
This article aims to provide a critical analysis of how the ‘emerging donors’ are redefining the structure of development cooperation in the new millennium. It offers an overview of the growing role of Brazil, China, India and South Africa in shaping the conditionally driven framework of official development cooperation. By reviewing the aid coordination mechanisms of the Southern donors, the article also seeks to provide a context for comprehending the challenges for Southern countries to systematically manage, monitor and deliver aid. It argues that the Southern donors’ interest in changing the dominant conditionality driven narrative of aid has opened up the possibility for constructing a new aid paradigm that focuses more on the strategic needs of the partner countries than on advancing the ideological interests of the donor countries. However, without assuming a much greater role in providing overseas aid and without building a unified platform based on a shared development vision, Southern donors will not be able to meaningfully alter the current dac -dominated aid architecture.
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 | 0.018 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.009 | 0.024 |
| Scholarly communication | 0.018 | 0.015 |
| Open science | 0.001 | 0.010 |
| Research integrity | 0.003 | 0.009 |
| Insufficient payload (model declined to judge) | 0.004 | 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 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".