Are Delayed Complaints of Sexual Harassment Not Worthy of Human Rights Protection?
Bibliographic record
Abstract
Within the current legislative landscape in Ontario, survivors of sexual harassment are treated differently than survivors of sexual assault and sexual misconduct with respect to when they can advance a legal claim against their perpetrators. Under sections 16(1)(h) and 16(1)(h.1) of the Ontario Limitations Act, survivors of sexual assault and misconduct are able to file a civil claim whenever they choose to do so. Under s 34(1) of the Ontario Human Rights Code, survivors of sexual harassment must file a human rights complaint within one year of the experienced harassment. This paper argues that s 34(1) should not apply to complaints based on sexual harassment. The author provides four reasons to substantiate this argument: (1) this provision fails to align with contemporary understandings of sexual harassment; (2) it is arbitrary to apply drastically different timelines to survivors depending on the type of sexual violence they have experienced; (3) two important objectives of limitation periods will not be seriously threatened by the suggested amendment to the Human Rights Code; and (4) section 34(1) favours the interests of the harassers over those of the survivor, the public, Bill 132 and the Human Rights Code.
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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 | 0.005 | 0.039 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.017 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.004 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".