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Record W4391876895 · doi:10.1111/1468-0009.12695

Keeping It Political and Powerful: Defining the Structural Determinants of Health

2024· article· en· W4391876895 on OpenAlex
Jonathan Heller, Marjory L. Givens, Sheri P. Johnson, David A. Kindig

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueMilbank Quarterly · 2024
Typearticle
Languageen
FieldHealth Professions
TopicPublic Health Policies and Education
Canadian institutionsSt. Francis Xavier University
FundersW.K. Kellogg FoundationRobert Wood Johnson Foundation
KeywordsPower (physics)Social determinants of healthPublic healthPoliticsWork (physics)Affect (linguistics)Balance (ability)Psychological interventionSocial structureRoot (linguistics)Health policySocial psychologySociologyPolitical sciencePublic economicsPublic relationsPsychologyEconomicsEngineeringMedicineCommunication

Abstract

fetched live from OpenAlex

Policy Points The structural determinants of health are 1) the written and unwritten rules that create, maintain, or eliminate durable and hierarchical patterns of advantage among socially constructed groups in the conditions that affect health, and 2) the manifestation of power relations in that people and groups with more power based on current social structures work-implicitly and explicitly-to maintain their advantage by reinforcing or modifying these rules. This theoretically grounded definition of structural determinants can support a shared analysis of the root causes of health inequities and an embrace of public health's role in shifting power relations and engaging politically, especially in its policy work. Shifting the balance of power relations between socially constructed groups differentiates interventions in the structural determinants of health from those in the social determinants of health.

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.

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)0.001
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 score0.469
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.058
GPT teacher head0.472
Teacher spread0.414 · 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