The 2014 Ontario Child Health Study—Methodology
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.
Bibliographic record
Abstract
OBJECTIVE: To describe the methodology of the 2014 Ontario Child Health Study (OCHS): a province-wide, cross-sectional, epidemiologic study of child health and mental disorder among 4- to 17-year-olds living in household dwellings. METHOD: Implemented by Statistics Canada, the 2014 OCHS was led by academic researchers at the Offord Centre for Child Studies (McMaster University). Eligible households included families with children aged 4 to 17 years, who were listed on the 2014 Canadian Child Tax Benefit File. The survey design included area and household stratification by income and 3-stage cluster sampling of areas and households to yield a probability sample of families. RESULTS: The 2014 OCHS included 6,537 responding households (50.8%) with 10,802 children aged 4 to 17 years. Lower income families living in low-income neighbourhoods were less likely to participate. In addition to measures of childhood mental disorder assessed by the Mini International Neuropsychiatric Interview for Children and Adolescents (MINI-KID) and OCHS Emotional Behavioural Scales (OCHS-EBS), the survey contains measures of neighbourhoods, schools, families and children, and includes administrative data held by the Ministries of Education and Health and Long-Term Care. CONCLUSIONS: The complex survey design and differential non-response of the 2014 OCHS required the use of sampling weights and adjustment for design effects. The study is available throughout Canada in the Statistics Canada Research Data Centres (RDCs). We urge external investigators to access the study through the RDCs or to contact us directly to collaborate on future secondary analysis studies based on the OCHS.
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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.088 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.003 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 it