Title IX versus Candian Human Rights Legislation: How the United States Should Learn from Canada's Human Rights Act in the Context of Sexual Harassment in Schools
Bibliographic record
Abstract
This Article critically examines the success of Title IX in eradicating sexual harassment in educational settings after the Supreme Court decisions in Gebser v. Lago and Monroe v. Davis. Regrettably, the high bar for recovery established by these cases, in addition to poor administrative enforcement of Title IX have eroded its ability to maintain discrimination-free schools. After an examination of the manner in which the Canadian human rights model operates in the context of sexual harassment in educational settings, recommendations are made that the United States should use the Canadian example to improve its own system. Specifically, the United States should streamline and simplify its administrative enforcement of Title IX and articulate clearer legal standards for injunctive relief as opposed to recovery of compensatory damages.
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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 | 0.010 | 0.023 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.022 | 0.028 |
| Scholarly communication | 0.017 | 0.006 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.011 | 0.013 |
| 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".