Understanding Information About Mortality Among People with Intellectual and Developmental Disabilities in Canada
Bibliographic record
Abstract
BACKGROUND: This paper reviews what is currently known about mortality among Canadians with intellectual and developmental disabilities and describes opportunities for ongoing monitoring. METHODS: In-hospital mortality among adults with intellectual and developmental disabilities in Ontario was examined using hospital data. Mortality was compared between age-, sex- and residence area-matched groups of Manitobans with and without intellectual and developmental disabilities using linked administrative data. A retrospective cohort study of mortality among individuals with intellectual and developmental disabilities in a region of Ontario focused on measuring excess mortality and risk factors. FINDINGS: There is evidence of excess mortality in persons with intellectual and developmental disabilities in Canada. Some of the excess is attributable to comorbidities that are more common in this population. Women may have a greater risk of death than men. Excess mortality occurs at all ages but is more pronounced in early life. DISCUSSION: High-quality ongoing monitoring of mortality among individuals with intellectual and developmental disabilities is possible in Canada. Examination of sex differences should be a priority.
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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 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.005 | 0.008 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".