Traumatic brain injury and justice-involved men in Canada: strategies and implications
Bibliographic record
Abstract
Recent longitudinal evidence reveals how sustaining a traumatic brain injury (TBI) increases risk for criminal justice involvement, including incarceration for serious or chronic offending (i.e., violent crime). In 2016, researchers from Correctional Service Canada (CSC) found between 01 July 1997 and 31 March 2011, the incidence of incarceration was higher among federally sentenced incarcerated people with prior TBI; in their sample, both men and women with TBI were approximately 2.5 times more likely to be incarcerated than men and women without TBI. More research is needed to understand how TBI may be related to neurodiversity and shape pathways to criminal justice system involvement, particularly among men who do not identify as White; for example, in 2020/2021, Indigenous men made up 32% of male admissions to federal custody in Canada. Engaging 11 reports produced by CSC which examine rates of TBI and other related factors among incarcerated people, as well as select international literature on TBI and the criminal justice system, our rapid report seeks to explicate the potential relationship between TBI, neurodiversity, and men as evidenced among federally incarcerated men in Canada. Policy, training, education, future areas of inquiry and practical implications for correctional services are discussed.
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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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.006 |
| Science and technology studies | 0.017 | 0.004 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.004 | 0.005 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 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".