Bibliographic record
Abstract
As the previous chapters highlight, law reform is the primary strategy adopted by feminist academics and political lobbyists to redress perceived inequalities facing women who kill their spouses. The central concern is to formalise in law the reality of the circumstances in which many women kill. This has meant challenging the criteria for defences in cases of homicide for women who kill their partners by exposing the exclusion of women’s different experiences and circumstances. The project of law reform has also involved indicating how women’s experiences are not incompatible with the present structure of legal defences to homicide. This argument has been that it is necessary to give con sideration to the events leading up to the homicide event, rather than just the act of homicide itself, in order for justice to be meted out fairly. Feminist writers have supported the goal of legal equality for eradicating the discriminatory treatment of female homicide defendants in the criminal justice system (Schneider 1986; Gillespie 1989; O’Donovan 1991; Radford 1993). Some feminists, however, have also raised questions about how women’s differences are addressed through the commitment to equality and equal treatment in law.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".