Struggles over Resource Decentralisation: Legislative Reform, Corporate Resistance and Canadian Aid Partnerships in Burkina Faso
Bibliographic record
Abstract
In attempting to counter the various negative correlations associated with the mining–development nexus in the global South (for example, the ‘resource curse’ or ‘enclave economies’), the global mining sector experienced a mushrooming of ethical norms, practices and policies during the past three decades, many of them intended to strengthen local communities. In addition to the launch of various initiatives from the corporate world (ranging from multi-stakeholder partnerships on the global level to corporate social responsibility programmes in mining concessions), a number of West African countries have reformed their liberal mining legislation in recent years, thereby introducing new mechanisms for a more just local redistribution of mining revenues. In this spirit, the mining code of Burkina Faso, reformed in 2015, provides the implementation of a Mining Fund for Local Development (FMDL) to which multinational corporations are legally required to contribute 1 per cent of their national turnover (before tax). This chapter investigates multi-scalar policies for decentralised mining revenue allocation in and around Burkina Faso’s gold mining sector by engaging with and contributing to debates in post-structural geography and political ecology. It explores how ‘resource decentralisation’ became a priority of both the national government and of Canadian aid projects in Burkina Faso, while facing political resistance from mining companies. I argue that struggles for local profits from mining transcend specific scales (‘the global’, ‘the national’, or ‘the local’) in resource governance and focus either on promoting the various voluntary engagements of the corporate world or on calling for the state-centred enforcement of legal requirements. In Burkina Faso’s mining areas this has ambivalent outcomes: It leads to a reshuffling of responsibility for the (re-)distribution of mining revenues from corporate agents to municipal decision makers, on the one hand. On the other, it serves to engineer (potential) community unrest, and thus to eventually make large-scale mining feasible in the first place.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".