An Exploratory Analysis of Factors Associated With Repeat Homicide in Canada
Bibliographic record
Abstract
The current study presents the results of the first Canadian national study on the characteristics of repeat homicide offenders and the factors associated with homicide recidivism. The research involves an analysis of National Parole Board (NPB) files for all homicide offenders in Canada who committed more than one homicide ( n = 86) between 1975 and 2005 and a matched sample of homicide offenders who only committed one homicide ( n = 84). Descriptive and bivariate analyses are used to examine and compare characteristics of single-time homicide offenders (SHOs) and repeat homicide offenders (RHOs). Logistic regression analysis reveals that RHOs lacked employment prior to their first homicide and became involved in alcohol and drug-influenced lifestyles. Furthermore, RHOs experience reductions in family and community support after release from custody for the first homicide. This reduction of support will likely reflect at-risk behavior and crime lifestyles associated with being unlawfully at large and alcohol and drug involvement.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".