Omission of Triple Bottom Line Reporting: Cause of Corporate Entities’ Environmental Neglect in Nigeria
Bibliographic record
Abstract
The study critically looked into the ways in which social and environmental provisions in Nigeria can be improved upon and the body that should be socially responsible. Is it the government or the corporate entities? This paper selected six companies that are quoted in Nigeria Stock Exchange, taking two from each sector, and examined the content and quality of the concerns demonstrated in their 2013 Annual Report and Accounts for Social and environmental issues in Nigeria. Special attention was placed on the similarities or differences among the companies in their social and environmental care. This paper discovered that social and environmental issues in Nigeria had been grossly neglected by the corporate entities. They hardly reported on it in their annual reports. Even where there was reported on the social and environmental issues, it is always in the Chairman’s speech. The main conclusion of this paper is that corporate social responsibility (CSR) is an integral part of the new business model and that it is increasingly recognized that the role of the business sector is critical. As a part of society, it is in business’ interest to contribute to addressing common problems. Strategically speaking, business can only flourish when the communities and ecosystems in which they operate are healthy.
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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 | 0.006 | 0.022 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".