Judicial attributions in sentencing: The battered woman before and after R. v. Lavallee
Bibliographic record
Abstract
Battered Women Syndrome (BWS) has been applauded for contributing to our understanding of the experiences of battered women, such as remaining in abusive relationships and, occasionally, killing their abusers. Nonetheless, BWS has been criticized as a stereotype that promotes dichotomous attributions about genuine victims of domestic abuse. Research on BWS has also been criticized for the use of scenarios that do not attend sufficiently to the details of women's experiences and for the use of mock juries that do not adequately represent the legal context. The present research uses discursive psychology to examine judicial attributions about battered women and judges' use of BWS in 26 Canadian sentencing decisions involving women convicted of killing their abusive intimate partners. The decisions covered the period of 1974-2006 with six decisions from before and 20 from after 'R. v. Lavallee' (1990), a ground-breaking case in which BWS testimony was permitted for the first time in Canada. The analyses suggest that for cases in which the accused received a non-custodial sentence, judicial accounts foster sympathy and leniency for trapped victims of longstanding abuse. The accused in such accounts were typically portrayed as passive, devoted, vulnerable and isolated. Conversely, in cases in which the accused received a custodial sentence, judges' accounts did not include narratives of entrapment. Rather, judges emphasized the mutuality of the violence and minimized the extent, duration, and seriousness of the abuse. Depictions of shared substance abuse and mutual violence underpinned negative attributions about the accused and were commonly associated with custodial sentences. Judges who drew on BWS often used the syndrome to construct the seriousness of abuse. BWS also provided judges with an explanatory framework to justify leniency, and allowed them to negotiate difficult rhetorical problems such as the apparent inconsistency between the passivity of the accused and the violence of the offence. The findings are discussed in terms of their contribution to our understanding of the ways in which versions of violence and versions of women are constructed. Suggestions for future research include an examination of guilty pleas by battered women and of police decision-making in instances of dual arrest.
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.
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 | 0.009 | 0.049 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.020 | 0.010 |
| Scholarly communication | 0.005 | 0.001 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.001 | 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".