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Record W2025084391 · doi:10.1080/09557571.2012.734786

Between caution and controversy: lessons from the Gulf Arab states as (re-)emerging donors

2012· article· en· W2025084391 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueCambridge Review of International Affairs · 2012
Typearticle
Languageen
FieldSocial Sciences
TopicInternational Development and Aid
Canadian institutionsBalsillie School of International Affairs
Fundersnot available
KeywordsMiddle EastPolitical scienceGulf warEconomyGeographyDevelopment economicsEconomic historyHistoryEconomicsLaw

Abstract

fetched live from OpenAlex

Abstract The history of Gulf donorship, its trajectory and underlying motivations, continues to be an understudied aspect of foreign aid. While the Gulf Arab states are not new donors, their manner of regional coordination, branding, and aid management are distinct. Often helping fellow countries of the South, particularly Arab and Muslim countries, these countries have moved towards stronger private sector involvement and into social spending programmes. Owing to their oil wealth, Gulf Arab states' are increasingly generous and yet they are also cautious after 9/11 about how and by whom their aid is channelled. Nevertheless, with oscillations in oil prices, continued controversy over rising Islamism post-Arab-Spring, the future of Gulf aid remains a valuable subject of study. Notes 1 This article specifically looks at the six member states of the GCC: Bahrain, Kuwait, Oman, Qatar, Saudi Arabia and the UAE. We use the terms ‘Gulf Arab’, ‘GCC’ and ‘Gulf’ in reference to this subregion of the greater MENA region. Although we acknowledge that Iran and Iraq are part of the geographic Gulf region, we are specifically examining the Gulf states that currently retain membership in the GCC. 2 The Goldman-Sachs acronym ‘BRICs’, of course, also includes Russia as a re-emerging economy. 3 The lack of data available from the Gulf Arab states is well known among regional researchers, and was discussed at length by Shushan and Marcoux (Citation2011) in relation to aid data. In 2008, the former director of the UN Millennium Campaign, Salil Shetty, was quoted in an article as decrying the lack of ‘clear numbers’ on aid contributions from Gulf Arab states, noting, ‘it's very opaque. There needs to be more transparency’ (Abocar Citation2008). 4 In just the last year, we have also seen funding packages within the GCC. Specifically, the GCC developed a US$20 billion aid package for Bahrain and Oman, prompted by their protest movements in the shadow of the Arab Spring. This was coupled with vast domestic spending in each country, which included (in varying forms and combinations) subsidy increases, salary hikes and the sudden offer of public sector jobs in the thousands (Bladd Citation2011; Ulrichsen Citation2011).

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.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.794
Threshold uncertainty score0.385

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.025
GPT teacher head0.337
Teacher spread0.312 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it