MétaCan
Menu
Back to cohort
Record W4392882707 · doi:10.1177/03098168241234304

Promoting social justice in the capitalist academy? Health equity and the Johns Hopkins University Michael Bloomberg School of Public Health

2024· article· en· W4392882707 on OpenAlexaff
Stella Medvedyuk, Dennis Raphael

Bibliographic record

VenueCapital & Class · 2024
Typearticle
Languageen
FieldHealth Professions
TopicPublic Health Policies and Education
Canadian institutionsYork University
Fundersnot available
KeywordsSocial justiceEquity (law)Public healthSociologyEconomic JusticePublic administrationPolitical scienceManagementLawSocial scienceMedicineEconomicsNursing

Abstract

fetched live from OpenAlex

The past two decades have seen increasing mentions of health equity and the importance of addressing the social determinants of health in USA public health statements. Yet, there is little uptake of these concepts into USA public policy. We see this, in part, as being due to the unwillingness of the USA public health community – including its network of Masters of Public Health Programs – to address the fundamental cause of health inequities: the United States’ capitalist economic system which skews the distribution of the social determinants of health in favour of the wealthy and powerful. We illustrate this reluctance by examining how the Bloomberg School of Public Health of Johns Hopkins University conceptualises the promotion of health equity through its International Declaration of Health Rights . Nothing in the Declaration considers how the economic system threatens health yet it is presented as a model for public health education. We review its shortcomings and show how revision to it is unlikely since the School is endowed by its namesake billionaire Michael Bloomberg who has denounced any attempts at redistributing wealth and income in the service of public health. Evidence of how public health messaging is already shaped by powerful economic interests embedded within the United States’ capitalist system substantiates concerns that have been raised about such branding and its effects on public health discourse and action.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.010
metaresearch head score (Gemma)0.009
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.990
Threshold uncertainty score0.109

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0100.009
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0100.038
Scholarly communication0.0150.011
Open science0.0010.007
Research integrity0.0060.011
Insufficient payload (model declined to judge)0.0070.001

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 head0.100
GPT teacher head0.443
Teacher spread0.343 · 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 source (direct Gemma or distilled Codex), not a consensus.

Study designQualitative
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

Citations3
Published2024
Admission routes1
Has abstractyes

Explore more

Same venueCapital & ClassSame topicPublic Health Policies and EducationFrench-language works237,207