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Record W2138690202 · doi:10.1093/heapol/czq022

Allocating funds for HIV/AIDS: a descriptive study of KwaDukuza, South Africa

2010· article· en· W2138690202 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueHealth Policy and Planning · 2010
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicHIV/AIDS Impact and Responses
Canadian institutionsUniversity of TorontoWestern University
FundersNational Institute on Drug AbuseNatural Sciences and Engineering Research Council of CanadaInyuvesi Yakwazulu-NataliOntario HIV Treatment Network
KeywordsResource allocationResource (disambiguation)Process (computing)Human immunodeficiency virus (HIV)BusinessPsychological interventionEconomic growthPublic economicsEconomicsEnvironmental economicsMedicineComputer scienceNursingFamily medicineManagement

Abstract

fetched live from OpenAlex

OBJECTIVE: through a descriptive study, we determined the factors that influence the decision-making process for allocating funds to HIV/AIDS prevention and treatment programmes, and the extent to which formal decision tools are used in the municipality of KwaDukuza, South Africa. METHODS: we conducted 35 key informant interviews in KwaDukuza. The interview questions addressed specific resource allocation issues while allowing respondents to speak openly about the complexities of the HIV/AIDS resource allocation process. RESULTS: donors have a large influence on the decision-making process for HIV/AIDS resource allocation. However, advocacy groups, governmental bodies and local communities also play an important role. Political power, culture and ethics are among a set of intangible factors that have a strong influence on HIV/AIDS resource allocation. Formal methods, including needs assessment, best practice approaches, epidemiologic modelling and cost-effectiveness analysis are sometimes used to support the HIV/AIDS resource allocation process. Historical spending patterns are an important consideration in future HIV/AIDS allocation strategies. CONCLUSIONS: several factors and groups influence resource allocation in KwaDukuza. Although formal economic and epidemiologic information is sometimes used, in most cases other factors are more important for resource allocation decision-making. These other factors should be considered in any attempts to improve the resource allocation processes.

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.

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)0.001
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: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.393
Threshold uncertainty score0.585

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
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 head0.114
GPT teacher head0.346
Teacher spread0.232 · 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