Aiding stakeholder capitalism: donors and the contentious landscape of transparency reform in Ghana
Bibliographic record
Abstract
Despite the growing invocation of transparency norms as the panacea for addressing the challenges associated with natural resource wealth, there is considerable ambiguity about how they shape market regimes in the global south. Drawing from empirical insights on government-donor engagements around the Extractive Industries Transparency Initiative (EITI) that were pieced together from multiple rounds of fieldwork in Ghana between 2012 and 2016, this article recounts the distinctive ways that such ambiguities around transparency reforms work to deepen the logics and mechanics of global capital in the extractive sector, with substantial gaps in labour market protections and domestic ownership. The author argues that the EITI’s successes in this endeavour reflect a more structural dynamic that is tied to donors’ parallel role as intermediaries of extractive governance norms and brokers of a distinctive form of stakeholder capitalism. This observation underlines changes in the global architecture for aiding the expansion of Western capital by forging expanded networks that preclude alternatives to neoliberalism.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".