Canadian-Colombian Interaction towards Building CSR Institutional Capacity How to Reach a Bottom-Line for Ethical Corporate Performance in the Global Mining Industry?
Bibliographic record
Abstract
This research paper seeks to contribute to the debate on whether a bottom-line to CSR exists in the global mining industry. The research approach focuses on the institutional differences and constraints to meet CSR international guidelines in both developed and developing countries. In doing so, the work of key actors within both the Colombian and Canadian regimes was researched and compared to draw attention to possible spill-over effects through different forms of interaction among the two regimes. The different interaction channels involving Canadian mining companies operating in Colombia, civil society’s activism at each end, trade agreements and regimes’ commitment to CSR guidelines at the national and international levels. Relevance to Development Studies This research raises questions over the potential role of Corporate Social Responsibility in the mining sector for countries such as Colombia, which have adopted similar extraction–led pathways within their national policy. Therefore, this paper shall shed light to countries’ institutional capacity in setting “bottom lines” on CSR standards in developed and developing countries. This paper will seek to identify incentive structures for Canadian mining companies in Colombia to go beyond merely compensating for their adverse social, environmental and economic effect, but instead, partaking social responsibility in strengthening national sustainable development road maps for extractive sectors, and with it, enhancing national economic developmental potential.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.010 | 0.007 |
| Scholarly communication | 0.008 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".