Community expectations versus corporate social responsibility practices in Ghana’s oil and gas sector
Bibliographic record
Abstract
The discovery of oil in Ghana initially raised hopes for development in oil and gas communities, driven by transnational companies’ (TNCs) corporate social responsibility (CSR) initiatives. Although previous research on CSR in the oil and gas sector has examined the community’s expectation of CSR, it has produced inconclusive results. As such, this study intends to contribute to this ongoing debate. In this quest, a multiple case study design was deployed to guide this study using a sample size of 94 participants who were selected using a purposive sampling technique. The study deployed interviews and observation to collect data while the data were analysed using thematic analysis. This study’s findings showed considerable optimism among communities regarding the transformative potential of CSR initiatives, with TNCs actively contributing to infrastructure development and livelihood opportunities. However, the results showed that some beneficiaries were discontent with the CSR interventions as they did not reflect their felt needs because of their limited participation. The policy recommendation is that there is a need for active stakeholders’ engagement in CSR decision-making to ensure that felt needs are met and to promote TNCs acceptance.
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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 | 0.005 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.006 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.000 | 0.003 |
| 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".