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Record W4399739913 · doi:10.25071/2291-5796.164

Structural Determinants of Health

2024· article· en· W4399739913 on OpenAlex
Elizabeth McGibbon

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.
venuePublished in a venue whose home country is Canada.

Bibliographic record

VenueWitness The Canadian Journal of Critical Nursing Discourse · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicHealth disparities and outcomes
Canadian institutionsSt. Francis Xavier University
Fundersnot available
KeywordsEnvironmental planningEnvironmental science

Abstract

fetched live from OpenAlex

This Invited Commentary focuses on a brief summary of how structural determinants of health (DoH) are framed in nursing and how a focus on the political economy of health can support identifying and addressing the ideological drivers of the structural DoH. Structural determinants focus on the politics and histories of enduring root causes of preventable injustices. There is a nascent literature in nursing regarding the structural DoH, which includes policy and governance processes, interlocking systems of oppression and discrimination, and social and economic structures that contribute to forces of power inherent in financial, legal, and governmental systems and policies. However, it is also crucially important to name and analyze their root ideological foundations because this is the space where structural change must be targeted. Various ideologies, intentionally or unintentionally, drive policy, politics, institutional governance and decision-making, and so on. The political economy of health is a foundational field that supports identifying these ideological drivers of the structural DoH. The invited commentary concludes with reflections and recommendations for nursing.

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.461
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.005
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 head0.050
GPT teacher head0.439
Teacher spread0.389 · 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