ARAB DEVELOPMENT AID AND THE NEW DYNAMICS OF MULTILATERALISM: TOWARDS BETTER GOVERNANCE?
Bibliographic record
Abstract
This study attempts to explore the evolution of the Arab Development Aid and contextualizes the Arab model of development aid vis-a-vis the DAC Model and the Southern Model shedding light on its transforming characteristics. The Kingdom of Saudi Arabia (KSA), Kuwait and the United Arab Emirates (UAE) have been among the most active donors in the world, with official development assistance (ODA) averaging 1.5 percent of their combined gross national income (GNI) during the period 1973-2008, more than twice the United Nations target of 0.7 percent and five times the average of the OECD-DAC countries. This paper approaches this model of development aid by focusing on: the changing nature of multilateral development framework and the rising role of emerging economies in the aid system; the basic tenets of the Arab aid development model and its current composition and characteristics; the challenges and future prospects for the Arab development aid and its potential role in engendering better governance mechanisms in the Arab region and globally with a case study on the case of the Qatar Development Fund.
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 | 0.008 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.010 |
| Scholarly communication | 0.014 | 0.014 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.003 |
| 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".