Bibliographic record
Abstract
Purpose The purpose of this paper is to provide an explanation for the global influences and dynamics that have led major mining companies to adopt corporate social responsibility (CSR) policies, and frame them in terms of sustainable development. Bad reputations stemming from environmental disasters and social disharmony led mining multinationals to adopt CSR policies and improve their practices. Rationalist expectations about what is driving firm responses to external pressures are a necessary, but insufficient, explanation of how and why mining companies have sought to improve their reputations. Three elements are necessary to explain firm responses, including strategic adaptation to external pressures, learning processes associated with CSR, and internalization of sustainable development norms, understood as standards of appropriate behavior. Design/methodology/approach The paper presents a multidisciplinary theoretical framework for explaining the adoption of CSR policies and practices on the part of mining companies, and applies that framework to case studies of two major mining companies with global operations. Findings An account of learning processes and norms socialization as they relate to CSR provide a more comprehensive explanation of how and why mining companies adopt CSR policies. Incorporation of these elements provides a better explanation of why mining companies began to frame their CSR policies in terms of the global norm of sustainable development. Originality/value The paper contributes to the theoretical understanding of how and why firms adapt to changing societal expectations about appropriate corporate behavior by integrating two sets of literatures; constructivism from international relations theory, and learning from organization theory.
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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 | 0.006 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.016 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".