The International Cyanide Management Code: Assessment as an Environmental Voluntary Code Pursuant to the ISED Framework Positioned within a Broader Environmental Governance Ecosystem
Bibliographic record
Abstract
Trends in modern environmental governance indicate an expanded role for self-regulatory approaches in addressing environmental issues. This thesis aims to assess the efficacy of one environmental voluntary code in the mining industry – the International Cyanide Management Code - positioning it within a broader regulatory governance context. The study employed a mixed-methods approach consisting of a literature review, content analysis of Cyanide Code reports, and the use of a qualitative evaluation framework. The findings suggest the Cyanide Code is a robust voluntary instrument; however, some areas for improvement in terms governance, implementation, and enforcement were identified. Recommendations to address these weaknesses draw on characteristics of other successful voluntary codes in the mining industry. Further, this study identified the presence of both collaborative and “check and balance” relationships between the Cyanide Code and other regulatory entities in the cyanide management governance ecosystem which aligns with Webb (2005)’s sustainable governance approach.
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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 | 0.026 | 0.056 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.003 | 0.009 |
| Scholarly communication | 0.009 | 0.007 |
| Open science | 0.001 | 0.006 |
| 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".