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Record W2096032874 · doi:10.1186/1744-8603-10-35

Adverse or acceptable: negotiating access to a post-apartheid health care contract

2014· article· en· W2096032874 on OpenAlexafffund
Bronwyn Harris, John Eyles, Loveday Penn‐Kekana, Liz Thomas, Jane Goudge

Bibliographic record

VenueGlobalization and Health · 2014
Typearticle
Languageen
FieldMedicine
TopicGlobal Maternal and Child Health
Canadian institutionsMcMaster University
FundersCanadian Institutes of Health ResearchHealth CanadaScheme for Promotion of Academic and Research CollaborationPublic Health AgencyNational Research FoundationCarnegie Corporation of New YorkInternational Development Research CentrePublic Health Agency of CanadaDepartment of Science and Technology, Ministry of Science and Technology, India
KeywordsHealth careSocial contractPovertyNegotiationPublic relationsHealth services researchHealth policySocial determinants of healthBusinessEconomic growthPolitical scienceSociologyEconomicsLaw

Abstract

fetched live from OpenAlex

BACKGROUND: As in many fragile and post-conflict countries, South Africa's social contract has formally changed from authoritarianism to democracy, yet access to services, including health care, remains inequitable and contested. We examine access barriers to quality health services and draw on social contract theory to explore ways in which a post-apartheid health care contract is narrated, practiced and negotiated by patients and providers. We consider implications for conceptualizing and promoting more inclusive, equitable health services in a post-conflict setting. METHODS: Using in-depth interviews with 45 patients and 67 providers, and field observations from twelve health facilities in one rural and two urban sub-districts, we explore access narratives of those seeking and delivering - negotiating - maternal health, tuberculosis and antiretroviral services in South Africa. RESULTS: Although South Africa's right to access to health care is constitutionally guaranteed, in practice, a post-apartheid health care contract is not automatically or unconditionally inclusive. Access barriers, including poverty, an under-resourced, hierarchical health system, the nature of illness and treatment, and negative attitudes and actions, create conditions for insecure or adverse incorporation into this contract, or even exclusion (sometimes temporary) from health care services. Such barriers are exacerbated by differences in the expectations that patients and providers have of each other and the contract, leading to differing, potentially conflicting, identities of inclusion and exclusion: defaulting versus suffering patients, uncaring versus overstretched providers. Conversely, caring, respectful communication, individual acts of kindness, and institutional flexibility and leadership may mitigate key access barriers and limit threats to the contract, fostering more positive forms of inclusion and facilitating easier access to health care. CONCLUSIONS: Building health in fragile and post-conflict societies requires the negotiation of a new social contract. Surfacing and engaging with differences in patient and provider expectations of this contract may contribute to more acceptable, accessible health care services. Additionally, the health system is well positioned to highlight and connect the political economy, institutions and social relationships that create and sustain identities of exclusion and inclusion - (re)politicise suffering - and co-ordinate and lead intersectoral action for overcoming affordability and availability barriers to inclusive and equitable health care services.

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)0.019
metaresearch head score (Gemma)0.029
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 score0.101

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0190.029
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0190.042
Scholarly communication0.0080.011
Open science0.0020.014
Research integrity0.0030.007
Insufficient payload (model declined to judge)0.0040.000

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 head0.026
GPT teacher head0.369
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

Citations23
Published2014
Admission routes2
Has abstractyes

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