The Canadian Community Health Survey as a Potential Recruitment Vehicle for the Canadian Longitudinal Study on Aging
Bibliographic record
Abstract
ABSTRACTThe goal of the Canadian Longitudinal Study on Aging (CLSA) is to recruit 50,000 participants aged 45 to 85 years of age and follow them for at least 20 years. The sampling and recruitment processes for a study of this scope and magnitude present important challenges. Statistics Canada was approached to collaborate with the CLSA with the goal of determining whether the Canadian Community Health Survey (CCHS) could be used as a recruitment vehicle for the CLSA. In this pilot study conducted in 2004, it was determined that 63.8 per cent and 75.8 per cent of the respondents agreed to share their contact information and their survey responses with the CLSA, respectively. The most commonly reported concerns were confidentiality/privacy issues, lack of interest, and commitment issues. This pilot study identified some challenges to the use of the CCHS as a recruitment vehicle for the CLSA.
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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 | 0.082 | 0.067 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.011 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.010 | 0.002 |
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".