Population Aging and Intellectual and Developmental Disabilities: Projections for <scp>C</scp>anada
Bibliographic record
Abstract
Abstract Population aging is expected to have a dramatic impact on the need for services and supports among adults with intellectual and developmental disabilities. The expected size of the population of older adults affected remains unknown. The aims of this paper are to present methods to project the age‐structure of the adult population with intellectual and developmental disabilities 10 years into the future, apply those methods to data from Ontario, Canada, and discuss their relative merit. Two methods were used. The first method relies on knowledge of the prevalence of intellectual and developmental disabilities across age groups in a given population and the corresponding census estimates for future years for the same age groups in that population. The second method requires knowledge of the age‐structure of the adult population with intellectual and developmental disabilities as well as age‐specific mortality rates for this population. This second method was applied using two sets of available mortality rates. Projections of the number of adults with intellectual and developmental disabilities 45–84 years of age over a 10‐year period vary depending on the method used. The first method suggests a moderate increase (20.5%) while the second method suggests a small increase (4.1–8.4%) in that age group. It is important to be able to critically examine methods and assumptions used when claims are made about population growth and aging in relation to intellectual and developmental disabilities. Accurate age‐specific prevalence data and detailed population‐level mortality statistics specific to intellectual and developmental disabilities are required to plan for aging‐related services.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.708 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".