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Record W2561391145 · doi:10.1177/0020731416681891

Introduction to the “Evaluating the Impact of Structural Policies on Health Inequalities and Their Social Determinants and Fostering Change” (SOPHIE) Project

2016· article· en· W2561391145 on OpenAlexaff
Carme Borrell, Davide Malmusi, Carles Muntaner

Bibliographic record

VenueInternational Journal of Health Services · 2016
Typearticle
Languageen
FieldHealth Professions
TopicEmployment and Welfare Studies
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsInequalityHealth equitySocial determinants of healthHealth policyAcronymEquity (law)Social inequalityPublic economicsPolitical scienceHealth careEconomic growthEconomics

Abstract

fetched live from OpenAlex

The SOPHIE Project (acronym for Structural Policies for Health Inequalities Evaluation) has focused on evaluating the impact of structural policies on health equity, considering as such all those policies that exert a powerful influence on the structural determinants of health (e.g., patterns of social stratification, living and working conditions) and thus on health-related exposures through intermediary determinants. In these sections of the International Journal of Health Services, we present some of the main findings of the SOPHIE Project. We include both articles that summarize all the evidence already published in the project on a thematic area (such as labor market, gender, or housing) and articles that present new, unpublished evidence on a specific health inequality or policy.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.753
Threshold uncertainty score0.880

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 studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.226
GPT teacher head0.544
Teacher spread0.318 · 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

Citations17
Published2016
Admission routes1
Has abstractyes

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