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 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 | 0.012 | 0.034 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.007 | 0.024 |
| Scholarly communication | 0.009 | 0.009 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.004 | 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".