Are Traumatic Brain Injuries Associated With Criminality After Taking Account of Childhood Family Social Status and Disruptive Behaviors?
Bibliographic record
Abstract
OBJECTIVE: The authors aimed to elucidate the links between traumatic brain injuries (TBIs) and criminal convictions in a sample of 724 Canadian males with and without criminal records followed up to age 24. METHODS: Prospectively collected data were analyzed to determine whether prior TBIs predicted subsequent criminal convictions after taking account of family social status (FSS) and childhood disruptive behaviors. At age 24, diagnoses of TBIs were extracted from health records and convictions from official criminal records. In childhood, teachers rated disruptive behaviors and parents reported FSS. RESULTS: Proportionately more individuals with offender status than nonoffender status sustained a TBI from age 18 to age 24 but not before age 18. Individuals with offender status who had sustained a TBI before and after their first conviction were similar in numbers, were raised in families of low social status, and presented high levels of disruptive behaviors from age 6 to age 12. When FSS and childhood disruptive behaviors were included in multivariable regression models, sustaining a prior TBI was not associated with an increased risk of juvenile convictions for any type of crime, for violent crimes, for convictions for any crime or violent crime from age 18 to age 24, or for a first crime or a first violent crime from age 18 to age 24. CONCLUSIONS: Among males, there was no evidence that prior TBIs were associated with an increased risk of subsequent criminal convictions from age 12 to age 24 when taking account of FSS and childhood disruptive behaviors, although these latter factors may be associated with an increased prevalence of TBIs among adult offenders.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".