Gender, indigeneity and mining
Bibliographic record
Abstract
The mining industry has been found to provide economic opportunities for local Indigenous communities, but these benefits are not always distributed equally. For instance, there is evidence of gendered socio-economic impacts of mining within traditional lands or treaty territories of Indigenous communities that have resulted in instances of violence against women. In Canada, the 2019 National Inquiry report on Missing and Murdered Indigenous Women and Girls (MMIWG) revealed the linkages between mining and extractive activities with spikes in violence against Indigenous women, girls, and gender-diverse people. The report includes five recommendations that are related to extractive and development activities to address the rights and safety of Indigenous women in mining territories. In this chapter, authors build upon the premise that mining companies have a responsibility to uphold Indigenous women’s needs and wants through meaningful engagement that is consistent with the 2019 National Inquiry report. They emphasize that there are well-documented advantages to involving Indigenous women as significant rights-holders in projects. This chapter first examines the literature regarding Indigenous women’s experiences with extractive mining projects in resource-based communities in Canada. The authors identify the context of gender and mining, including violence against Indigenous women. Second, they determine the extent and significance of Indigenous women’s involvement in the mining sector. Third, this chapter explores opportunities and strategies that affect the wants and needs of Indigenous women that aim to counter racism, sexism, and misogynistic patterns observed within the mining sector. Last, highlighted is the relevance of these findings for a range of actors involved in policy, practices, planning, and corporate behaviours. Overall, this chapter finds that Indigenous women are essential actors at the nexus of mining companies and local communities. The authors believe that acknowledging this role can improve Indigenous women’s realities and agency while contributing to the equitable development of mining economies in Indigenous communities.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.014 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".