A critical analysis of corporate responsibility in the mining industry
Bibliographic record
Abstract
This thesis analyses the role of corporate social responsibility (CSR) in the silver\nmining industry. The study is based on the case of the Peñasquito mine in Mazapil,\nMexico. Owned by Goldcorp, a Canadian mining company, the Peñasquito mine was\ninvolved in a seven-year conflict between the members of the community and the\nextractive corporation. Surprisingly, Goldcorp shows a strong commitment to the\ncommunity and implementation of sustainable programs, such as UN Global\nCompact and The Global Reporting Initiative (GRI), and yet there were a series of\nprotests and lawsuits against the corporation and its activities in Mazapil. For this\nreason, I have proposed the research question, how has corporate responsibility\nimpacted the conflicts of Goldcorp in Mazapil, Mexico? To answer the question, I use two theoretical frameworks, the pyramid of CSR\n(Carroll, 1991) and the stakeholder theory. Following the pyramid of CSR, I evaluate\nGoldcorp’s initiatives and activities under the economic, legal, ethical and\nphilanthropic responsibilities. The stakeholder theory was used to enable a wider\nperspective of the situation from different points of view. Therefore, the research\nagenda of the thesis contains the following: Goldcorp sustainable programmes and\ninitiatives including its activities in Peñasquito; a timeline with the main events that\noccurred during the conflict; and the opinions of different stakeholders involved in the\nconflict, namely, the communities, the Mexican government, the researchers and\njournalists. The findings reveal that the conflict was generated because of an incomplete\nimplementation of CSR, lacking ethical responsibilities. There is evidence showing\nthat during the negotiations with the communities of Mazapil, there were a variety of\ncircumstances that gave Goldcorp space to act one-sided. According to some of the\nstakeholders Goldcorp acted as an unequal partner with dishonesty and treating the\nlocals without respect.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.013 | 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 teacher head, 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".