Health, Social, Education, and Justice Outcomes of Manitoba First Nations Children Diagnosed with Fetal Alcohol Spectrum Disorder: A Population-Based Cohort Study of Linked Administrative Data
Bibliographic record
Abstract
Objective: To examine health services, social services, education, and justice system outcomes among First Nations children and youth with fetal alcohol spectrum disorder (FASD). Methods: In this retrospective cohort study, health and social services, education, and justice data were linked with clinical records on First Nations (FN) individuals aged 1 to 25 and diagnosed with FASD between 1999 and 2010 ( n = 743). We compared the FN FASD group to non-FN individuals with FASD (non-FN FASD; n = 315) and to First Nations individuals (matched on age, sex, and income) not diagnosed with FASD (FN non-FASD; n = 2229). Rates and relative risks (RRs) were calculated using generalized linear models. Results: FN FASD individuals had similar health services use to non-FN FASD individuals but had greater involvement with child welfare (RR, 1.20; 95% confidence interval [CI], 1.02 to 1.41) and the justice system (RR, 1.37; 95% CI, 1.07 to 1.74) and were more likely to be charged with a crime (RR, 1.40; 95% CI, 1.05 to 1.86). There were no suicides/suicide attempts among the non-FN FASD individuals during the study, but the crude rate/100 person-years of suicides among FN FASD individuals (0.22 for females; 1.06 for males) was substantially higher than for FN non-FASD individuals (0.08 for females; 0.32 for males). There were no significant differences between groups in the education outcomes we measured. Conclusions: Young people with FASD are at risk for poor health, education, and social outcomes, but First Nations young people with FASD face comparably higher risks, particularly with child welfare and justice system involvement. The study emphasizes a critical need for appropriate resources for First Nations children with FASD.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".