Beyond the Myths: Equality, Impartiality, and Justice
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Violence against women is as much a matter of equality as it is an offence against human dignity and a violation of human rights. As the Supreme Court of Canada has repeatedly recognized, eliminating myths and stereotypes from the law constitutes an important part of remedying the law’s historically inadequate response to violence against women. The author explores how the concepts of impartiality, equality, and justice shed light on the ways in which myths and stereotypes distort the truth-finding process and perpetuate discrimination. Looking toward the future, further equality-informed legislative amendments, judicial education, and international norms, such as those set out in the Convention on the Elimination of All Forms of Discrimination against Women (1979), will provide key means of ensuring that myths and stereotypes are fully and permanently eradicatedfrom the law. The goals of equality and justice for all require nothing less.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 it