Evidence Based Principles to Accelerate Health Information Flow and Uptake Among Older Adults
Bibliographic record
Abstract
SettingThis article describes the development of evidence based principles for increasing health information flow among older adults and how those principles were implemented in a major knowledge mobilization project in Canada.The Canadian Coalition for Seniors' Mental Health (CCSMH) is a national charitable organization seeking to improve the mental health of older adults by creating clinical practice guidelines, mobilizing knowledge, and advocating for policy change.CCSMH was initiated by the Canadian Academy of Geriatric Psychiatry (CAGP) and continues to operate under its oversight.Thanks to recent financial investments from the Public Health Agency of Canada, CCSMH significantly increased its knowledge mobilization initiatives in 2022-2024, covering a wide range of mental health topics and
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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 | 0.218 | 0.270 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.011 | 0.004 |
| Science and technology studies | 0.006 | 0.007 |
| Scholarly communication | 0.014 | 0.010 |
| Open science | 0.007 | 0.020 |
| Research integrity | 0.010 | 0.012 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".