Recent Mental Health Surveys at Statistics Canada [2015]
Bibliographic record
Abstract
The webinar we explore the following surveys: • 2012 Canadian Community Health Survey – Mental Health (CCHS - MH), which provides a comprehensive look at mental health with respect to who is affected by selected mental disorders, as well as positive mental health of Canadians. It also examines access to and utilization of formal and informal mental health care services and supports, and how people are functioning regardless of whether they have a mental health problem. • 2013 Canadian Forces Mental Health Survey (CFMHS), which collected information about the mental health status and the need for mental health services in the Canadian Forces. It also examines the mental health impact of the Canadian Forces work environment and deployment in support of the mission in Afghanistan. • 2014 Survey of Living with Chronic Diseases in Canada (SLCDC), which provides information related to the experiences of Canadians with mood and anxiety disorders, including care received from health professionals, medication use and self-management of their condition.
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 | 0.002 | 0.015 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.008 | 0.028 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.004 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.026 | 0.014 |
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".