Corporate Social Responsibility (CSR) in Ghana's Mining Industry: Insights from the Cases of Newmont and Kinross
Bibliographic record
Abstract
Since the concept of Corporate Social Responsibility (CSR) became popular in academic circles in the 1950s, there has been a great deal of focus on business-society relations in different sectors of the economy as well as different countries and regions. Yet, the literature on the nature, scope and rationale of CSR within the African context is not well developed, as much of the studies tend to focus more on South Africa and Nigeria. But the specific contexts within which companies operate require that more emphasis be given to several other resource-rich countries on the continent. In the case of Ghana, there is inadequate literature that specifically speaks to why companies embark on certain social responsibility initiatives and what the expected outcomes are. A simple google search for scholarly articles on the work of Newmont and Kinross in Ghana, for instance, yielded sparse results. The objective of the paper is, therefore, to show the dearth of literature on CSR in Ghana with reference to two mining companies. The broader theoretical discussion will be reinforced by insights from fieldwork conducted in January (and between May and August) 2013 where several stakeholders were interviewed on what CSR actually means and seeks to do.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.014 | 0.014 |
| Scholarly communication | 0.004 | 0.005 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".