MétaCan
Menu
Back to cohort
Record W7095115794

Province-Level Income Inequality and Health Outcomes in Canadian Adolescents

2014· article· en· W7095115794 on OpenAlexaboutno aff

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldSocial Sciences
TopicIrish and British Studies
Canadian institutionsnot available
Fundersnot available
KeywordsSocioeconomic statusMental healthEconomic inequalityInequalityFamily incomeLimitingHousehold incomeIncome distributionSocial inequality
DOInot available

Abstract

fetched live from OpenAlex

Objective To examine the effects of provincial income inequality (disparity between rich and poor), independent of provincial income and family socioeconomic status, on multiple adolescent health outcomes. Methods Participants (aged 12–17 years; N 11,899) were from the Canadian National Longitudinal Survey of Children and Youth. Parental education, household income, province income inequal-ity, and province mean income were measured. Health outcomes were measured across a number of do-mains, including self-rated health, mental health, health behaviors, substance use behaviors, and physical health. Results Income inequality was associated with injuries, general physical symptoms, and limiting conditions, but not associated with most adolescent health outcomes and behaviors. Income inequality had a moderating effect on family socioeconomic status for limiting conditions, hyperactivity/inattention, and con-duct problems, but not for other outcomes. Conclusions Province-level income inequality was associated with some physical and mental health outcomes in adolescents, which has research and policy implications for this age-group. Key words adolescents; disparities; health behavior; mental health; public health. Countries with greater disparity between the rich and the poor—or greater income inequality—have been shown to

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)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.018
Threshold uncertainty score0.133

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.003
Science and technology studies0.0030.001
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.052
GPT teacher head0.344
Teacher spread0.292 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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
Published2014
Admission routes1
Has abstractyes

Explore more

Same topicIrish and British StudiesFrench-language works237,207