The Role of a Policy in Strengthening Corporate Social Responsibility: An Empirical Study of the Mining Sector in Ghana
Bibliographic record
Abstract
The prohibition imposed on resource-rich nations by the Global North governments to legislate laws to control multi-national enterprises has hit a death nail in any attempt(s) to innovate corporate social responsibility. Consequently, a self-commitment strategy was recommended for adoption to guide business own activities. This strategy undermines business participation in effective social governance yet encourages externalisation of the corporate cost of production, leading to catastrophic ramifications for host communities. The paper, therefore, proposes a policy nuance, which is a novelty in the existing literature, to oversee social responsibility undertakings and brings on board the corporate body in the social development discourse. Meanwhile, an SPSS analysis shows a statistically significant p-value and a negative coefficient which indicates comparability between policy and corporate social responsibility resulting in an endorsement of the paper’s proposition. Conclusively, a policy distinction would ensure appropriate planning, realistic and objective target setting, and compensatory plus effective and efficient implementation of basic social amenities, while systematising and normalising social agenda in corporate management strategies. It would also inspire checks of multi-national enterprises’ commitments since benchmarks are established and visible for references. Expectedly, further study on an appropriate policy enforcement mechanism for social (and environmental) governance is recommended.
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".