Lessons From Canadian Judgments: The Consideration of Culture in Intimate Partner Violence Legal Cases Involving Asian Canadians
Bibliographic record
Abstract
Despite the pervasiveness of intimate partner violence (IPV) in Canada, research examining IPV in the context of Asian Canadians is scarce. Our study examined whether and how Canadian judges consider culture when determining a sentence in IPV cases involving an Asian offender and/or an Asian victim. We systematically searched for publicly published cases through CanLII. A total of 50 cases met the inclusion criteria. Cultural themes were identified using a direct content analysis approach to capture a priori themes in the literature, as well as identify any other factors considered. Our findings indicated culture was most often considered in only a superficial way (n = 31, 62.0%), where judges only made statements that simply identified the ethnicity of the offender and not how culture may have impacted the case. When examining cases where culture was meaningfully considered there were no prominent culture themes identified (all themes present in <14% of cases). We suggest this may not only reflect the heterogeneity of Asian Canadians, but could also reflect the lack of cultural consideration by the judges. Cultural factors were also rarely considered explicitly as an aggravating or mitigating factor in a case (n = 2; 4.0% and n = 7; 14.0% of the total sample, respectively). The findings reveal the current lack of meaningful consideration of culture in IPV legal cases involving Asian Canadians. We outline how this contrasts the increased attention to the meaningful consideration of culture in the Canadian legal arena and prompt all professionals involved in assessing and managing IPV risk to consider racial, ethnic, and cultural factors in these cases.
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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 | 0.038 | 0.087 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.009 |
| Science and technology studies | 0.039 | 0.021 |
| Scholarly communication | 0.013 | 0.005 |
| Open science | 0.005 | 0.008 |
| Research integrity | 0.003 | 0.006 |
| Insufficient payload (model declined to judge) | 0.003 | 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".