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Making it Politic(al): closing the Gap in a Generation: Health Equity Through Action on the Social Determinants of Health

2009· article· en· W1643809570 on OpenAlexaff
Anne‐Emanuelle Birn

Bibliographic record

VenueSocial medicine · 2009
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicGlobal Public Health Policies and Epidemiology
Canadian institutionsUniversity of Toronto
FundersCollege of Engineering, Michigan State UniversityMichigan State University
KeywordsDeclarationGlobal healthCapitalismSocial determinants of healthPovertyEconomic growthHealth promotionPoliticsPolitical scienceSociologyEconomicsLawHealth care

Abstract

fetched live from OpenAlex

The anniversary of the publication of Closing the Gap in a Generation (CGG) offers a moment to reflect on the report’s contributions and shortcomings, as well as to consider the political waters ahead. The issuance of CGG was not the first time the World Health Organization (WHO) raised the problem of global inequalities in health. Numerous analysts and advocates have compared CGG to the 1978 Declaration of Alma-Ata. Some see CGG as a continuation of Alma-Ata; others malign it for paying insufficient attention to the principles, background documents, and lines of action proposed in the Alma-Ata declaration. We might understand the two reports as bookends to 30 years of brutal global capitalism, punctuated by the “lost decade” of the 1980s, the end of the Cold War, and, more recently, the implosion of global finance. This period saw the publication of two seminal neoliberal health manifestos –the World Bank’s 1993 World Development Report and the WHO’s 2002 Commission on Macroeconomics and Health report. Both feature the term “investing in health” in their title, conveying “a double meaning—investing [through “cost-effective,” narrow, technical interventions] to improve health, economic productivity, and poverty; and investing capital, especially private capital, as a route to private profit in the health sector.”

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)0.004
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Commentary · Consensus signal: none
Teacher disagreement score0.523
Threshold uncertainty score0.985

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.001
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 head0.458
GPT teacher head0.528
Teacher spread0.070 · 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 designNot applicable
Domainnot available
GenreCommentary

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

Citations123
Published2009
Admission routes1
Has abstractyes

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