Disability Payments for Persons With Severe Mental Illness in Alberta, Canada
Bibliographic record
Abstract
OBJECTIVE: The authors measured the total expenditures for two key sources of social support in Alberta in 2005 for persons with severe and persistent mental illness and compared these expenditures with the total mental health expenditures. METHODS: Social services and assistance benefit data were from the federal government's Canada Pension Plan-Disability Benefits and from Alberta Services' Assured Income for the Severely Handicapped for beneficiaries with psychiatric diagnoses. These benefits were compared with the total public mental health expenditures in Alberta for budget year 2005-2006. RESULTS: A total of 7,456 adults with certified mental illness conditions received federal disability benefits, and 17,138 received provincial disability and medical benefits. The total for social support (income) benefits was $207 million Canadian compared with $405 million Canadian spent by the provincial government for mental health services for adults under age 65. CONCLUSIONS: Social assistance forms a substantial portion of Canadian federal and provincial government support for persons with mental illness. Whenever a government-payer perspective is taken, these costs should be factored into the analysis.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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) | 0.002 | 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".