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Anthropology, Inequality, and Disease: A Review

2003· review· en· W2100263254 on OpenAlexaff
Vinh‐Kim Nguyen, Karine Peschard

Bibliographic record

VenueAnnual Review of Anthropology · 2003
Typereview
Languageen
FieldBusiness, Management and Accounting
TopicGlobal Public Health Policies and Epidemiology
Canadian institutionsMcGill University
Fundersnot available
KeywordsBiosocial theorySocial inequalityStructural violenceSociologyScholarshipPovertyHealth equityInequalityCausationDevelopment economicsIndividualismHealth careCriminologyPolitical economyPolitical scienceEconomic growthSocial psychologyPsychologyPoliticsEconomics

Abstract

fetched live from OpenAlex

▪ Abstract Anthropological approaches broaden and deepen our understanding of the finding that high levels of socioeconomic inequality correlate with worsened health outcomes across an entire society. Social scientists have debated whether such societies are unhealthy because of diminished social cohesion, psychobiological pathways, or the material environment. Anthropologists have questioned these mechanisms, emphasizing that fine-grained ethnographic studies reveal that social cohesion is locally and historically produced; psychobiological pathways involve complex, longitudinal biosocial dynamics suggesting causation cannot be viewed in purely biological terms; and material factors in health care need to be firmly situated within a broad geopolitical analysis. As a result, anthropological scholarship argues that this finding should be understood within a theoretical framework that avoids the pitfalls of methodological individualism, assumed universalism, and unidirectional causation. Rather, affliction must be understood as the embodiment of social hierarchy, a form of violence that for modern bodies is increasingly sublimated into differential disease rates and can be measured in terms of variances in morbidity and mortality between social groups. Ethnographies on the terrain of this neoliberal global health economy suggest that the violence of this inequality will continue to spiral as the exclusion of poorer societies from the global economy worsens their health—an illness poverty trap that, with few exceptions, has been greeted by a culture of indifference that is the hallmark of situations of extreme violence and terror. Studies of biocommodities and biomarkets index the processes by which those who are less well off trade in their long-term health for short-term gain, to the benefit of the long-term health of better-off individuals. Paradoxically, new biomedical technologies have served to heighten the commodification of the body, driving this trade in biological futures as well as organs and body parts.

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)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.007
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0070.011
Science and technology studies0.0010.002
Scholarly communication0.0030.003
Open science0.0010.001
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0040.001

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 head0.067
GPT teacher head0.434
Teacher spread0.367 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations250
Published2003
Admission routes1
Has abstractyes

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