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Record W2099045343 · doi:10.1136/jech.57.10.792

Labour market income inequality and mortality in North American metropolitan areas

2003· article· en· W2099045343 on OpenAlexaffabout
Claudia Sanmartin

Bibliographic record

VenueJournal of Epidemiology & Community Health · 2003
Typearticle
Languageen
FieldSocial Sciences
TopicHealth disparities and outcomes
Canadian institutionsUniversity of CalgaryMcGill UniversityStatistics Canada
Fundersnot available
KeywordsMedicineMetropolitan areaInequalityEconomic inequalityDemographic economicsSocial inequalityLabour economicsEconomics

Abstract

fetched live from OpenAlex

OBJECTIVE: To investigate relations between labour market income inequality and mortality in North American metropolitan areas. METHODS: An ecological cross sectional study of relations between income inequality and working age (25-64 years) mortality in 53 Canadian (1991) and 282 US (1990) metropolitan areas using four measures of income inequality. Two labour market income concepts were used: labour market income for households with non-trivial attachment to the labour market and labour market income for all households, including those with zero and negative incomes. Relations were assessed with weighted and unweighted bivariate and multiple regression analyses. RESULTS: US metropolitan areas were more unequal than their Canadian counterparts, across inequality measures and income concepts. The association between labour market income inequality and working age mortality was robust in the US to both the inequality measure and income concept, but the association was inconsistent in Canada. Three of four inequality measures were significantly related to mortality in Canada when households with zero and negative incomes were included. In North American models, increases in earnings inequality were associated with hypothetical increases in working age mortality rates of between 23 and 33 deaths per 100 000, even after adjustment for median metropolitan incomes. CONCLUSIONS: This analysis of labour market inequality provides more evidence regarding the robust nature of the relation between income inequality and mortality in the US. It also provides a more refined understanding of the nature of the relation in Canada, pointing to the role of unemployment in generating Canadian metropolitan level health inequalities.

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)0.058
metaresearch head score (Gemma)0.035
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesMetaresearch
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.253
Threshold uncertainty score0.974

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0580.035
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.002
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 head0.120
GPT teacher head0.461
Teacher spread0.341 · 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

Citations49
Published2003
Admission routes2
Has abstractyes

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