Accounting versus Sustainability Reports in Mining Waste Management: Transparency with Corruption in Latin America
Bibliographic record
Abstract
Accounting and sustainability disclosures provide transparency to mining waste management and yet, negative social and environmental outcomes still occur. Corruption, understood as the devastation of the poor, can be limited through disclosures given to stakeholders as a form of transparency. Using mandated sustainability and accounting reports, a longitudinal descriptive case is built on two events from Brazil looking at transparency through the role of accounting and sustainability disclosures to enhance our understanding of fertile grounds for corrupt practices in Latin America. The appearance of transparency, facilitated by corrupt practices and actors, and its links with environmental and social disasters, is explored through performativity theory. We ask if accounting reports resulting from professional practices and artefacts have the potential to deter corruption in publicly traded companies more than mandated environmental and social reports. Saying something can produce a real outcome that changes reality; therefore, this study counts specific words and how they are used in sustainability and accounting reports before and after each event. We conclude that despite accounting reports give the appearance of more transparency than sustainability reports, neither the apparent transparency nor the silence was able to avoid social catastrophes in Brazil affecting poor rural areas. Accounting practices and artefacts provide more disclosures increasing the visibility of suspected corruption, with the difference explained by the extensive accounting regulation that restricts management exclusionary practices in their reports performativity. Mining waste management transparency is enacted when government officers, managers and auditors can engage in corrupt practices by avoiding visibilities of geological audits.
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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 | 0.009 | 0.034 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.003 | 0.008 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.000 | 0.004 |
| 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".