BC Court of Appeal Recognizes the Myth of False Allegations of Intimate Partner Violence
Bibliographic record
Abstract
We have both written previously on myths and stereotypes about intimate partner violence (IPV), one of the most common of which is that women make false or exaggerated claims of violence to gain an advantage in family law disputes (see here and here). In KMN v SZM, 2024 BCCA 70 (CanLII), the British Columbia Court of Appeal (BCCA) recognized the existence of this myth and the need for courts to avoid making assumptions that perpetuate it, holding that it is erroneous to do so unless there is an evidentiary basis for a finding of false allegations. This judgment came just a week before the Supreme Court of Canada released a decision on rape myths and stereotypes, in which it reiterated its recognition of the myth of “false allegations of sexual assault based on ulterior motives” (R v Kruk, 2024 SCC 7 (CanLII) at paras 35-37). The Supreme Court has not yet acknowledged the myth of false allegations of IPV in the family law context, however. This post will describe the underlying parenting dispute between KMN (the mother) and SZM (the father) and the trial court and BCCA’s reasons for decision, followed by our commentary on the significance of the latter decision. In addition to its holding on the myth of false allegations, the BCCA underlined the importance of courts making findings of fact when family violence is raised in parenting disputes, and of considering the impact of children’s direct and indirect exposure to family violence.
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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 | 0.009 | 0.050 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.034 | 0.022 |
| Scholarly communication | 0.017 | 0.005 |
| Open science | 0.006 | 0.005 |
| Research integrity | 0.056 | 0.057 |
| Insufficient payload (model declined to judge) | 0.009 | 0.004 |
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".