The effects of COVID-19 on human rights complaints in Manitoba: a study of the Manitoba Human Rights Commission
Bibliographic record
Abstract
This paper aims to understand the effects of the COVID-19 pandemic on human rights complaints received by the Manitoba Human Rights Commission. It should be noted that there is not currently any published research available studying the effects of the pandemic on provincial territorial, or federal Canadian human rights tribunals and commissions. As each human rights jurisdiction in Canada follows the applicable provincial or territorial acts, this paper first looks as human rights legislation in Manitoba, applicable legal tests and the investigation process used by the Commission. The paper also aims to understand current research barriers and what is being done to resolve these by the MHRC and other actors. There have been multiple strategies implemented to respond to these barriers, with varying success. To understand the effects of the pandemic on human rights complaints, this paper looks at two separate three-year periods from 2017-2019 and 2020-2022 and studies the complaint data registered by the Commission during these pre- and post-COVID periods. This allows for the comparison of important information such as: types of complaints, protected characteristics and areas of discrimination complaints were filed under, as well as the number breakdowns of complaints each year. The importance of this research is also discussed, explaining not only why the research is needed, but also looks at potential uses for said research.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".