The evolving role of CSR in international development: Evidence from Canadian extractive companies’ involvement in community health initiatives in low-income countries
Bibliographic record
Abstract
Overseas development agencies and international finance organisations view the exploitation of minerals as a strategy for alleviating poverty in low-income countries. However, for local communities that are directly affected by extractive industry projects, economic and social benefits often fail to materialise. By engaging in Corporate Social Responsibility (CSR), transnational companies operating in the extractive industries ‘space’ verbally commit to preventing environmental impacts and providing health services in low-income countries. However, the actual impacts of CSR initiatives can be difficult to assess. We help to bridge this gap by analysing the reach of health-related CSR activities financed by Canadian mining companies in the low-income countries where they operate. We found that in 2015, only 27 of 102 Canadian companies disclosed information on their websites concerning health-related CSR activities for impacted communities. Furthermore, for these 27 companies, there is very little evidence that alleged CSR activities may substantially contribute to the provision of comprehensive health services or more broadly to the sustainable development of the health sector.
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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 | 0.009 | 0.020 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.007 |
| Science and technology studies | 0.008 | 0.007 |
| Scholarly communication | 0.007 | 0.002 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| 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".