‘Calling out’ corporate redwashing: the extractives industry, corporate social responsibility and sport for development in indigenous communities in Canada
Bibliographic record
Abstract
In this paper, we explore the sponsorship of sport for development (SFD) programs in Indigenous communities in Canada by oil, gas, and mining companies (the ‘extractives industry’). While SFD programming has recently proliferated, the majority of these initiatives have been located in ‘developing’ countries of the global South. It is only more recently that SFD programs have gained traction in Canada, particularly in Indigenous communities. In undertaking an analysis of corporate social responsibility reports, we explore the tensions in having private companies — particularly those with poor environmental and social records — fund SFD programs in Indigenous communities. In the vein of ‘green-washing’, we argue that extractives companies are funding SFD programs in Indigenous communities as a form of ‘redwashing’ to portray themselves as good corporate citizens and as members of the communities in which they operate, while obfuscating the harmful impacts of extractive practices and histories of colonialism.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.016 | 0.007 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".