Embedding Anti-Discrimination Policies and Allyship in Mining and Engineering Workplaces: A Pathway to Decent Work
Bibliographic record
Abstract
Despite the existence of human rights legislation in Canada, equitable access to these rights remains elusive in many workplaces—particularly in traditionally male-dominated sectors such as engineering and mining. This paper argues that the proactive application of human rights frameworks can drive meaningful workplace culture transformation by addressing both overt and systemic inequities. While Canadian human rights laws offer legal remedies for discrimination, underrepresented groups continue to face barriers, especially in non-unionized environments where support mechanisms are limited. This paper presents a novel analysis of Canadian workplaces through a human rights lens, emphasizing the need for policies that go beyond reactive measures. It advocates for increased public awareness, targeted allyship training, and leadership accountability to foster inclusive and equitable work environments. The findings have broad implications for advancing decent work across sectors and for building representative and inclusive workforces.
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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 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.030 | 0.024 |
| Scholarly communication | 0.012 | 0.004 |
| Open science | 0.002 | 0.012 |
| Research integrity | 0.002 | 0.005 |
| 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".