Combatting complex inequality: the importance of an intersectional approach to Manitoba's human rights complaint process
Bibliographic record
Abstract
In this paper, I present the need and reasons why the Manitoba Human Rights Commission (MHRC) should begin to create and eventually adopt an intersectional board policy for multiple ground human rights complaints. The policy is necessary because it would unite the Commission’s approach to working on these complex complaints. The policy would guide the staff to consider the effect intersectionality has on the registered complaints during all stages of the process. In Canada, the Ontario Human Rights Commission is the only commission that has utilized an intersectional approach in 2001. I propose that Manitoba follow suit and create an approach that works in its complaint process, and a guiding policy using the OHRC’s work as a baseline. My suggestions are for the MHRC to identify the importance of intersectionality in the human rights complaint process, conduct internal staff research and trainings regarding the subject, before eventually providing this information to the public. I recommend that the staff continue to maintain open dialogue with the parties, while discussing their protected characteristics and the relationships that may occur among them. The staff should consider the possibility that the discrimination the intersectional complainants face occur because their protected characteristics exist and interrelate to each other. Supplementing this idea, an educator role should be created at the MHRC to provide training to the staff and public about intersectionality as well as for other MHRC education sessions. I acknowledge that this is not a perfect nor complete recommendation; however, I hope that it can be used as the foundation in the development of an intersectional policy at the MHRC that will adapt to better address the multiple ground complaints in the years to come.
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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 | 0.037 | 0.043 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.056 | 0.032 |
| Scholarly communication | 0.034 | 0.013 |
| Open science | 0.006 | 0.030 |
| Research integrity | 0.009 | 0.013 |
| Insufficient payload (model declined to judge) | 0.011 | 0.001 |
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".