MétaCan
Menu
Back to cohort
Record W6932059396 · doi:10.5683/sp3/eylz18

Canadian Community Health Survey, 2017-2018: Annual Component

2018· dataset· en· W6932059396 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueBorealis · 2018
Typedataset
Languageen
FieldMedicine
TopicStoma care and complications
Canadian institutionsStatistics Canada
Fundersnot available
KeywordsCommunity healthMicrodata (statistics)Population healthGovernment (linguistics)HRHISHealth careHealth policyPublic health informaticsPublic healthData collection

Abstract

fetched live from OpenAlex

<p>In 1991, the National Task Force on Health Information cited a number of issues and problems with the health information system. To respond to these issues, the Canadian Institute for Health Information (CIHI), Statistics Canada and Health Canada joined forces to create a Health Information Roadmap. From this mandate, the Canadian Community Health Survey (CCHS) was conceived.</p> <p>The CCHS is a cross-sectional survey that collects information related to health status, health care utilization and health determinants for the Canadian population. The survey is offered in both official languages. It relies upon a large sample of respondents and is designed to provide reliable estimates at the health region level every 2 years.</p> <p>The CCHS has the following objectives: <br>- Support health surveillance programs by providing health data at the national, provincial and intra-provincial levels; <br>- Provide a single data source for health research on small populations and rare characteristics; <br>- Timely release of information easily accessible to a diverse community of users; <br>- Create a flexible survey instrument that includes a rapid response option to address emerging issues related to the health of the population.</p> <p>The CCHS produces an annual microdata file and a file combining two years of data. The CCHS collection years can also be combined by users to examine populations or rare characteristics.</p> <p>The primary use of the CCHS data is for health surveillance and population health research. Federal and provincial departments of health and human resources, social service agencies, and other types of government agencies use the information collected from respondents to monitor, plan, implement and evaluate programs to improve the health of Canadians. Researchers from various fields use the information to conduct research to improve health. Non-profit health organizations and the media use the CCHS results to raise awareness about health, an issue of concern to all Canadians.</p> <p>The survey began collecting data in 2001 and was repeated every two years until 2005. Starting in 2007, data for the Canadian Community Health Survey (CCHS) were collected annually instead of every two years. While a sample of approximately 130,000 respondents were interviewed during the reference periods of 2001, 2003 and 2005, the sample size was changed to 65,000 respondents each year starting in 2007.</p> <p>In 2012, CCHS began work on a major redesign project that was completed and implemented for the 2015 cycle. The objectives of the redesign were to review the sampling methodology, adopt a new sample frame, modernize the content and review the target population. Consultations were held with federal, provincial and territorial share partners, health region authorities and academics.</p> <p>As a result of the redesign, the current CCHS has a new collection strategy, is drawing the sample from two different frames and has undergone major content revisions. With all these factors taken together, caution should be taken when comparing data from previous cycles to data released for the 2015 cycle onwards.</p>

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.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Dataset · Consensus signal: Dataset
Teacher disagreement score0.187
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.066
GPT teacher head0.345
Teacher spread0.279 · 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