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Record W7096427792

Proceedings of the Survey Methods Section A Review of the Weighting Strategy for the Canadian Community Health Survey

2015· article· en· W7096427792 on OpenAlexaboutno aff

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldSocial Sciences
TopicSurvey Methodology and Nonresponse
Canadian institutionsnot available
Fundersnot available
KeywordsWeightingSection (typography)Data collectionSurvey methodologySample (material)Process (computing)Community healthSurvey data collection
DOInot available

Abstract

fetched live from OpenAlex

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.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.434
metaresearch head score (Gemma)0.103
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Science and technology studies
Consensus categoriesMetaresearch
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.332
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.4340.103
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0020.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.701
GPT teacher head0.569
Teacher spread0.131 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; both teacher heads agree on what is shown here.

Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2015
Admission routes1
Has abstractyes

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