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Record W2009797735 · doi:10.1080/13645570701550549

Population Surveys of Children’s Health and Wellbeing: Parental Views on Data Collection Content and Methods

2007· article· en· W2009797735 on OpenAlexfundno aff
Elizabeth Waters, Elise Davis, Ozlem Mehmet‐Radji

Bibliographic record

VenueInternational Journal of Social Research Methodology · 2007
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicHealthcare Policy and Management
Canadian institutionsnot available
FundersMcMaster University
KeywordsData collectionPsychologyPopulationContent (measure theory)Content analysisSociologyResearch methodologySocial psychologySocial scienceDemography

Abstract

fetched live from OpenAlex

Pre‐testing is a standard tool to increase appropriateness and to capture the audience, yet rarely is this technique employed for population surveys. This study aimed to examine parental views on the content and methodology of a population child health survey. Forty‐eight Australian families of children aged 0–12 years were interviewed about the content and proposed data collection methods of the draft Victorian Population Survey of Child Health and Wellbeing. Concerns with instructions and items of several commonly used child health measures were identified. Parents preferred face‐to‐face methods rather than telephone interviews due to survey legitimacy; however, 72% of parents indicated that they would participate in a telephone survey. This study provided new findings about respondent views on child health measures and the conditions under which CATI versus face‐to‐face methods for child health data collection methods would be acceptable.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.098
metaresearch head score (Gemma)0.137
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: Methods · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.902
Threshold uncertainty score0.521

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0980.137
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.003
Science and technology studies0.0010.002
Scholarly communication0.0020.002
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.773
GPT teacher head0.610
Teacher spread0.163 · 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; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

Study designQualitative
DomainMethods
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

Citations1
Published2007
Admission routes1
Has abstractyes

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