MétaCan
Menu
Back to cohort
Record W4245704244 · doi:10.2190/hs.40.2.c

A Macro-Level Model of Employment Relations and Health Inequalities

2010· article· en· W4245704244 on OpenAlexaff
Carles Muntañer, Haejoo Chung, Orielle Solar, Vilma Sousa Santana, Antía Castedo, Joan Benach

Bibliographic record

VenueInternational Journal of Health Services · 2010
Typearticle
Languageen
FieldHealth Professions
TopicEmployment and Welfare Studies
Canadian institutionsCentre for Addiction and Mental Health
Fundersnot available
KeywordsMacroInequalitySocial determinants of healthSocial inequalityPerspective (graphical)Government (linguistics)Industrial relationsSocial policySociologyPublic economicsAffect (linguistics)EconomicsHealth careEconomic growthComputer science

Abstract

fetched live from OpenAlex

The authors develop a macro-social theoretical framework to explain how employment and working conditions affect health inequalities. The theoretical framework represents the social origins and health consequences of various forms of employment conditions. The emphasis is thus on determinants and consequences of employment conditions, not on social determinants of health in general. The framework tries to make sense of the complex link between macro-social power relations among employers, government, and workers' organizations, labor market and social policies, employment and working conditions, and the health of workers. It also suggests further testing of hypothetical causal pathways not covered in the literature. This macro-social theoretical framework might help identify the main "entry points" through which to implement policies and interventions to reduce employment-related health inequalities. The theoretical framework should be approached from a historical perspective.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.101
Threshold uncertainty score0.576

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.136
GPT teacher head0.470
Teacher spread0.333 · 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 teacher head, 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

Citations100
Published2010
Admission routes1
Has abstractyes

Explore more

Same venueInternational Journal of Health ServicesSame topicEmployment and Welfare StudiesFrench-language works237,207