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Record W3214138202 · doi:10.1111/1467-9566.13399

Desperately seeking reductions in health inequalities in Canada: Polemics and anger mobilization as the way forward?

2021· review· en· W3214138202 on OpenAlexaffabout
Dennis Raphael, Toba Bryant, Piara Govender, Stella Medvedyuk, Zsofia Mendly‐Zambo

Bibliographic record

VenueSociology of Health & Illness · 2021
Typereview
Languageen
FieldHealth Professions
TopicFood Security and Health in Diverse Populations
Canadian institutionsOntario Tech UniversityYork University
Fundersnot available
KeywordsInequalityPublic healthAngerHealth equityPolitical scienceEquity (law)Social determinants of healthPublic policyHealth policyGovernment (linguistics)Collective actionSocial policyCriminologySociologyHealth carePsychologySocial psychologyMedicinePoliticsLaw

Abstract

fetched live from OpenAlex

Progress in reducing health inequalities through public policy action is difficult in nations identified as liberal welfare states. In Canada, as elsewhere, researchers and advocates provide governing authorities with empirical findings on the sources of health inequalities and document the lived experiences of those encountering these adverse health outcomes with the hope of provoking public policy action. However, critical analysis of the societal structures and processes that make improving the sources of health inequalities difficult-the quality and distribution of living and working conditions, that is the social determinants of health-identifies limitations in these approaches. Within this latter critical tradition, we consider-using household food insecurity in Canada as an illustration-how polemics and anger mobilization, usually absent in health inequalities research and advocacy-could force Canadian governing authorities to reduce health inequalities through public policy action. We explore the potential of using high valence terms such as structural violence, social death and social murder, which make explicit the adverse outcomes of health-threatening public policy to force government action. We conclude by outlining the potential benefits and threats posed by polemics and anger mobilization as means of promoting health equity.

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)0.005
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.735
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0030.000
Bibliometrics0.0000.001
Science and technology studies0.0020.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.002
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 head0.246
GPT teacher head0.489
Teacher spread0.243 · 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.

Study designNot applicable
Domainnot available
GenreReview

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

Citations16
Published2021
Admission routes2
Has abstractyes

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