Sources of Revenue for Nonprofit Mental Health and Addictions Organizations in Canada
Bibliographic record
Abstract
OBJECTIVE: In Canada charitable or nonprofit organizations provide government-contracted mental health and addictions services, and they augment government funding by raising charitable revenues. This study estimated by source the revenues of nonprofit mental health and addictions organizations in Canada. METHODS: A list of nonprofit, service-providing organizations in Canada was developed, financial returns to the Canada Revenue Agency (CRA) in 2007 were obtained, and data were analyzed in aggregate. RESULTS: Information was obtained from 369 Canadian organizations, which had $915.4 million (Canadian dollars [CAD]) in total revenues: 85% were from the government, 4% were from charitable giving, and 11% were from other sources. CONCLUSIONS: The ratio of charitable giving to government funding of mental health care was about .55% ($35 million to $6.3 billion CAD). This charitable giving level cannot compensate for the relatively low levels of total government mental health spending identified in government reports.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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".