An Archival Descriptive Study: Risk and Protective Factors of Recidivism for Youth with Fetal Alcohol Spectrum Disorder
Bibliographic record
Abstract
A majority (60%) of youth with Fetal Alcohol Spectrum Disorder (FASD) will come into contact with law at some point in their lives (Institute for Health Economics, 2013). The reasons for this troubling statistic are hypothesized to be a result of the varying cognitive, social, and behavioural problems that are present in individuals who experienced pre-natal alcohol exposure (Chartrand & Forbes-Chilibeck, 2003). The Youth Criminal Justice Act (YCJA) in Canada proposes that a balance must be struck between maintaining public safety while strongly emphasizing rehabilitative interventions as opposed to imprisonment (Justice Department of Canada, 2000). In order to implement effective rehabilitative interventions, it is critical to identify what the relevant needs/risks and circumstances of FASD youth are. The current archival descriptive study examined the relevant risk factors for 37 youth with FASD who received a Section 34 assessment in the Edmonton and surrounding area between 2010 and 2015. The Structured Assessment of Violence Risk in Youth (SAVRY) was utilized in order identify relevant risk and protective factors. It was found that the majority of youth not only rated high on several of the risk factors but were also found to have almost no protective factors. Implications of this finding and future research directions 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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.006 | 0.004 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| 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".