Proceedings of the Survey Methods Section A Review of the Weighting Strategy for the Canadian Community Health Survey
Bibliographic record
Abstract
The regional component of the Canadian Community Health Survey (CCHS) is a cross-sectional survey with a complex, multi-stage, multi-frame design. It collects general health-related information from a sample large enough to provide estimates for more than 120 health regions across Canada. To date, there have been three regional component surveys conducted in the years 2001, 2003, and 2005. The year 2007 marks a turning point for the survey, as it has been redesigned to incorporate a continuous collection process. In the past, data was collected over a period of one year biennially. Starting in January of 2007, data is collected continually with no breaks in the collection schedule. As part of the CCHS redesign, the methodology of the weighting process is being reviewed. This revision involves some improvements to the weighting strategy, including the methodology of the nonresponse adjustments and the integration of the different frames. As well, the overall process will be simplified to reduce the number of adjustments required.
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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 | 0.163 | 0.253 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.012 | 0.018 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.006 | 0.003 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.032 | 0.015 |
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".