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Record W2319483983 · doi:10.1080/01459740.2016.1173691

Ways of Doing: Restorative Practices, Governmentality, and Provider Conduct in Post-Apartheid Health Care

2016· article· en· W2319483983 on OpenAlexfundno aff
Bronwyn Harris, John Eyles, Jane Goudge

Bibliographic record

VenueMedical Anthropology · 2016
Typearticle
Languageen
FieldSocial Sciences
TopicFoucault, Power, and Ethics
Canadian institutionsnot available
FundersUniversity of Cape TownCoordenação de Aperfeiçoamento de Pessoal de Nível SuperiorCanadian Institutes of Health ResearchNational Research FoundationCarnegie Corporation of New York
KeywordsGovernmentalityPaternalismAccountabilityHealth careContext (archaeology)SociologyCitizenshipAuthoritarianismDemocracyPublic relationsPolitical scienceLawPolitics

Abstract

fetched live from OpenAlex

In this article, we consider the conduct of post-apartheid health care in a policy context directed toward entrenching democracy, ensuring treatment-adherent patients, and creating a healthy populace actively responsible for their own health. We ask how tuberculosis treatment, antiretroviral therapy, and maternal services are delivered within South Africa's health system, an institutional site of colonial and apartheid injustice, and democratic reform. Using Foucauldian and post-Foucauldian notions of governmentality, we explore provider ways of doing to, for, and with patients in three health subdistricts. Although restorative provider engagements are expected in policy, older authoritarian and paternalistic norms persist in practice. These challenge and reshape, even 'undo' democratic assertions of citizenship, while producing compliant, self-responsible patients. Alongside the need to address pervasive structural barriers to health care, a restorative approach requires community participation, provider accountability, and a health system that does with providers as much as providers who do with patients.

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)0.011
metaresearch head score (Gemma)0.010
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.019
Threshold uncertainty score0.061

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0110.010
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0150.073
Scholarly communication0.0050.005
Open science0.0010.007
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0020.000

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 head0.105
GPT teacher head0.448
Teacher spread0.342 · 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 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

Citations11
Published2016
Admission routes1
Has abstractyes

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