Intimate partner homicide in New Zealand, 2004–2019. Risk markers, demographic patterns, and prevalence
Bibliographic record
Abstract
Intimate partner homicide (IPH) is a worldwide scourge and a topic of great interest in New Zealand, but its patterns and prevalence have not been quantified and compared to those in other comparable countries such as Australia, Canada, the United Kingdom, and the United States. Using a data set of the 187 IPH cases known to have occurred in New Zealand over 16 years, 174 of which involved current or former marriage (including de facto marriage) partners, we present analyses demonstrating the following. As in other comparable countries, a large majority of IPH victims are women, and the wife's youth, spousal age disparity, and de facto marriage are all associated with elevated risk. New Zealand is also unexceptional with respect to gross IPH rates, a very high incidence of recent marital separation as a trigger for male violence, a substantial incidence of offender suicide when the perpetrators are men but not when they are women and an overrepresentation of stepfamilies among the spousal cases. Despite frequent claims that New Zealand is exceptional in the magnitude of its intimate partner violence problem, the true picture is strikingly similar to that in other comparable countries.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".