An Evaluation of Management Perspectives of Sustainability Reporting in the Nigerian Oil Industry
Bibliographic record
Abstract
Purpose: This article investigates the perspectives of managers involved in sustainability reporting in the Nigerian oil industry. Design/Methodology: The article adopts a survey methodology in its approach to conduct this investigation. The survey employed a structured interview to investigate five themes built around the motivation for sustainability reporting within these organizations, hierarchical responsibility for sustainability reporting, the organizations objectives relative to the welfare of the people within the communities it operates in, policies in place to rejuvenate the damaged environment resulting from it’s operations and finally how sufficient in monetary terms is the company’s effort to wipe out its operational footprint. Findings: The data gathered was analysed qualitatively under these various themes. The general view emerging amongst the vast majority of the managers interviewed was that oil companies operating within the region have a key social responsibility and disclosure role to play but that it remains the role of the Nigerian Federal Government to provide the institutional framework around which the development of the region is to be hinged. Research Implications: More research is required in the area of CSR and CSD in developing/emerging markets to understand the link between weak institutional frameworks and voluntary CSR and CSD. Originality/Value: This article contributes to CSR and CSD literature in broad terms and in specific terms to the literature on sustainable operations in developing/emerging markets. The originality is based on the fact that it explores manager’s perspectives in a developing/emerging market.
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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 | 0.022 | 0.025 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.006 | 0.006 |
| Scholarly communication | 0.009 | 0.004 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| 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".