Mining For Equality: Soft Targets and Hard Floors for Boards of Directors?
Bibliographic record
Abstract
In this chapter, we consider the CBCA amendments in light of broader concerns associated with Canadian-based mining companies operating within and outside of Canada, including violations of rights of women and girls. The industrial mining sector is male dominated, and has faced accusations and lawsuits over gender bias, violence (including sexual violence) against women and children, health and safety problems, and environmental harms. The 2019 report of the National Inquiry into Missing and Murdered Indigenous Women and Girls (MMIWG) explicitly linked resource extraction with violence against Indigenous women and girls. Among the calls to justice in the report are five aimed at “Extractive and Development Industries,” including that industries consider “safety and security of Indigenous women and girls” at “all stages of project planning, assessment, implementation, management, and monitoring.”\nThis chapter aims to contribute to the literature on international law, women and mining from a Canadian perspective, focusing on legal developments related to corporate board diversity. We first examine the importance of women’s equality and empowerment in sources of international human rights and sustainable development law, and then consider Canadian initiatives aimed at the extractive sector. Second, we review the data on female representation on Canadian corporate boards and in senior management, with particular attention to the mining sector. Third, we consider insights and limitations of current literature on corporate board diversity, with attention to the definition of “firm performance,” arguing that it must account for respect for the rights of women and girls. A broader understanding of firm performance is essential in light of Canada’s promotion of business responsibilities to respect international human rights law at home and overseas. We conclude by considering different approaches to board and management diversity in light of the recent amendments to the CBCA, and offering recommendations for law and policy reforms as well as future research.
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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 | 0.009 | 0.023 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.013 | 0.018 |
| Scholarly communication | 0.017 | 0.013 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.018 | 0.002 |
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".