Partner-Killing by Women in Cohabiting Relationships and Marital Relationships
Bibliographic record
Abstract
Using a national-level U.S. database that includes more than 400,000 homicides committed from 1976 to 1994, the author calculated rates of partner-killing by women by relationship type (cohabiting or marital), by partner ages, and by the age difference between partners. Men in cohabiting relationships are 10 times more likely to be killed by their partners than are married men. Within marriages, the risk of being killed by a partner decreases with a man's age. Within cohabiting relationships, in contrast, middle-aged men are at greatest risk of being killed by their partners. The risk that a man will be killed by his partner generally increases with greater age difference between partners. These findings provide the first national-level replications of risk patterns reported for a national-level Canadian sample. Discussion highlights future research directions, including identifying why men in cohabiting relationships incur greater risk of being killed by their partners than do married men.
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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 | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".