Practice and Policy: Fetal Alcohol Syndrome/Fetal Alcohol Effect: Impacted Offences and the Correctional Service of Canada
Bibliographic record
Abstract
Until recently, there has been little acknowledgement or understanding of the problems faced by those affected by fetal alcohol syndrome/fetal alcohol effect (FAS/FAE). This is especially the case for offenders. Research indicates that those affected by FAS/FAE are far more likely to have trouble with the law than those who are not. Despite this, diagnosis of FAS/FAE is rare and therefore the disability remains hidden. A review of Corrections Services of Canada (CSC) policy finds that there are avenues within the policy which could be usehl in addressing the issue of FAS/FAE impacted offenders. To date, these avenues do not appear to be utilized, nor is there CSC policy dealing directly with FAS/FAE affected offenders. Seven interviews with corrections stakeholders indicate that the resources to address the needs of FAS/FAE affected offenders are scarce. This lack of resources results in keeping the disability invisible and prevents those affected from obtaining the assistance they need to live a pro-social lifestyle. The features of one program, the Genesis House Program, which is an exception to this lacking, are considered for future Corrections development.
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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 | 0.004 | 0.019 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.022 | 0.005 |
| Scholarly communication | 0.008 | 0.002 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.009 | 0.004 |
| Insufficient payload (model declined to judge) | 0.025 | 0.002 |
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".