Accessing Health Care Utilization Databases for Health Research: A Canadian Longitudinal Study on Aging Feasibility Study
Bibliographic record
Abstract
RÉSUMÉ Une des clés au succès de l’Étude longitudinale canadienne sur le vieillissement (ÉLCV) sera de tirer profit des sources de données secondaires, en particulier données relatives à l’utilisation des soins de santé (USS). Pour examiner les aspects pratiques, méthodologiques et éthiques d’accéder à des données sur l’USS, des entrevues qualitatives individuelles ont été réalisés auprès de 53 administrateurs de données et commissaires/ombudsman à la protection de la vie privée à travers le Canada. Les participants de l’étude ont indiqué que d’obtenir la permission d’accéder à des données sur l’USS est généralement possible; cependant, ils ont noté que ce processus sera complexe et long, exigeant des travaux préparatoires considérables et méticuleux afin de s’assurer que la documentation soit appropriée et que le tout soit conforme aux variations juridiques ainsi qu’aux lignes, législatives et politiques.
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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 | 0.033 | 0.065 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.018 |
| Science and technology studies | 0.005 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".