Advocating for a Home-State Grievance Mechanism: Law Reform Strategies in the Canadian Resource Justice Movement
Bibliographic record
Abstract
The vast majority of mining companies operating globally are Canadian. For nearly two decades, social justice advocates systematically documented the concerns of mine-affected communities in relation to Canadian operations in developing countries, producing a significant body of empirical work that described not only the nature of the social conflicts associated with Canadian companies but also the mechanisms whereby the Canadian government provides companies with political, economic and legal support. Beginning in 2005, activists, policy makers, industry leaders and international human rights bodies participated in a sustained debate over the appropriate Canadian regulatory responses to these issues. This chapter analyses the strategies of law reform advocates between 2000 and 2017 to critique Canadian policy and the overseas conduct of Canadian extractive companies. It gives special attention to the 2016 law reform proposal from Canadian civil society, the draft Business & Human Rights Act. The strategies profiled here are of special interest because they resulted in a significant, if not unexpected, breakthrough in early 2018 when the Canadian government announced a globally unprecedented new grievance mechanism: the Canadian Ombudsperson for Responsible Enterprise. The discussion is of interest to those concerned with law's potential (and limitations) as an instrument of social justice in the global economy, and particularly for communities affected by foreign resource extraction.
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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 | 0.022 | 0.030 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.053 | 0.040 |
| Scholarly communication | 0.022 | 0.007 |
| Open science | 0.005 | 0.009 |
| Research integrity | 0.016 | 0.015 |
| Insufficient payload (model declined to judge) | 0.004 | 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".