Tracking and Resisting Backlash Against Equality Gains in Sexual Offence Law
Bibliographic record
Abstract
The authors document feminist efforts to expose, challenge, and eliminate direct, indirect, and systemic inequality in the substantive, evidentiary, and procedural laws proscribing sexual offences and in the enforcement and application of those laws have not only been consistently resisted by police, lawyers, judges, and juries, but have also consistently generated backlash against those responsible for and/or supportive of such egalitarian change. Actual and imagined social, economic, political and legal equality gains by women as a class-however unevenly distributed- have triggered a variety of types of backlash, including an escalation in actual or threatened violence against women accompanied by new equality-resistant strains of legal doctrine that effectively offset or bypass earlier reforms. The authors illustrate these forms of backlash by examining three decades of feminist reforms to sexual assault laws.
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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 | 0.001 | 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 | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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 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".