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Role of Fiscal Policy in Tackling the HIV/AIDS Epidemic in Southern Africa

2013· article· en· W2111993228 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.

Bibliographic record

VenueAfrican Development Review · 2013
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicHIV/AIDS Impact and Responses
Canadian institutionsHEC Montréal
Fundersnot available
KeywordsWelfareDebtFiscal policyHuman immunodeficiency virus (HIV)EconomicsDeveloping countryDevelopment economicsFiscal sustainabilityEconomic growthMedicineMonetary economicsMacroeconomicsVirology

Abstract

fetched live from OpenAlex

Three countries in southern Africa have the highest adult HIV prevalence in the world: Swaziland (25.9 per cent), Botswana (24.8 per cent), and Lesotho (23.6 per cent). Fiscal policy is crucial for addressing this HIV/AIDS crisis. Utilizing a calibrated model, this paper investigates the impact of fiscal policy on reducing the HIV/AIDS incidence rates in these countries. In particular, we studied the welfare impact of different taxation and debt paths in these countries in reducing the HIV/AIDS prevalence rates. This is particularly important given the current concerns about dwindling foreign aid (especially the global AIDS fund), and the fiscal deterioration and sustainability in these countries. Our results show that, acting optimally has not only a positive societal welfare effect but also positive fiscal effects. For example, it will alleviate the debt burden by 5 per cent, 1 per cent and 13 per cent of the GDP, respectively for Botswana, Lesotho and Swaziland by the year 2020. Thus, at a time of fiscal crisis in developed countries and dwindling international HIV/AIDS resources, the future of effective and efficient HIV/AIDS intervention in Africa is clearly domestic.

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.809
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.002

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 head0.025
GPT teacher head0.245
Teacher spread0.220 · 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