Realising the Africa mining vision: the role of government-initiated international development think-tanks
Bibliographic record
Abstract
This paper focuses on the role of international development think tanks in the realisation of the Africa Mining Vision (AMV), launched in February 2009 by the Economic Commission for Africa and the African Union to articulate a new vision for the exploitation of Africa’s mineral resources. By government-initiated international development think-tanks is meant those think-tanks working in the field of international development that do not merely receive government support, but that were established by governments in partnership with the private sector with the overarching goal of furthering the governments’ economic diplomacy and foreign policy objectives. Australia and Canada established, respectively, the International Mining for Development Centre and the Canadian International Resources and Development Institute with the goal not only of contributing to public welfare improvements in developing countries through promoting sustainable mineral resource development but also of furthering their foreign policy objectives. This paper critically reviews the policies and approaches these two think tanks have adopted with a view to analyzing how they can contribute to the realization of the AMV. It also discusses how African countries can collaborate with these think tanks to realize the goals of the Vision, taking into account their local contexts and development trajectories. The choice of Australia and Canada is informed by the huge presence of their mining corporations in Africa and by the fact that Africa constitutes not less than one-third of the geographical focus of the two think tanks mentioned here. The article’s central argument is that despite the shortcomings of the think tanks, the programmes and strategies they have developed have the potential to contribute to the realisation of the AMV through the capacity building opportunities they create. It behoves African governments to leverage the opportunities to maximize the gains of foreign direct investment in the continent. One tool that would help Africa to leverage the opportunities is the adoption and strategic implementation of local content requirements in the mining sector.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".