SUSTAINABILITY REPORTING IN FINANCIAL INSTITUTIONS: A STUDY OF THE NIGERIAN BANKING SECTOR
Bibliographic record
Abstract
Transparency and disclosure practices of business organizations are key aspects of corporate governance. Business organizations are faced with the need to report on sustainability performance in economic, environmental and social terms. Financial institutions constitute providers of capital to other sectors of an economy. Thus, their sustainability performance is an important aspect of transparency and disclosures that should not be ignored. This study investigated sustainability reporting of Nigerian companies in the banking sector for the five-year period ended December 2014. A disclosure index was used to score the information content of corporate reports pertaining to sustainability indicators. There was an increase in the mean sustainability reporting scores of the banks across the five years. The economic indicators was skewed in favor of direct economic value generated, economic value distributed, estimated value of defined benefit plan obligations (liabilities). On the other hand, disclosures on climate change were few. Banks should focus on improving their environmental disclosures in areas of renewable materials used, greenhouse gas emissions and assessment of suppliers based on environmental risks.
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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 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".