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The Relationship Between Poverty and HIV/AIDS in Rural Thailand

2007· dissertation· en· W29043613 on OpenAlexfundno aff
Michael P. Cameron

Bibliographic record

Venuenot available
Typedissertation
Languageen
FieldSocial Sciences
TopicPoverty, Education, and Child Welfare
Canadian institutionsnot available
FundersNational Cancer InstituteCanadian Institutes of Health Research
KeywordsPovertySocioeconomic statusPandemicHuman immunodeficiency virus (HIV)Development economicsDeveloping countryCulture of povertyEconomic growthMedicineEnvironmental healthGeographySocioeconomicsPolitical sciencePopulationBasic needsImmunologyEconomicsDiseaseCoronavirus disease 2019 (COVID-19)

Abstract

fetched live from OpenAlex

HIV/AIDS is a global pandemic with critical demographic, economic, and social implications. The pandemic is widespread in poor regions of the world, including Southeast Asia where its long-term effects are potentially catastrophic. Despite the major impacts of the epidemic being already felt at the household level in many countries, a lack of recognition of the socioeconomic determinants of HIV infection and the economic and social impacts of HIV/AIDS and their relationship with poverty persists. This is due in part to the lack of systematic studies at the household, community, sectoral, and macro levels. \n \nThe thesis describes a 'vicious circle' between HIV/AIDS, poverty and high-risk behaviour at the individual level. In the poverty-HIV/AIDS cycle, HIV-infected individuals are especially vulnerable to poverty, the poor are more likely to engage in high-risk behaviour such as commercial sex work, and high-risk behaviour in turn makes people susceptible to HIV infection. The thesis examines whether rural Northeast Thailand exhibits characteristics that support the existence of such a cycle. Four key relationships are considered and tested: (i) the relationship between previous HIV infection and current wealth or poverty; (ii) the relationship betweem wealth or poverty and HIV/AIDS knowledge; (iii) the relationship between previous wealth or poverty and current HIV infection; and (iv) the relationship between previous migration and current HIV infection. \n \nAll four relationships are shown to hold using survey data from Khon Kaen province in Northeast Thailand. Poverty is shown to increase susceptibility to HIV infection, and HIV/AIDS is shown to reduce wealth and hence increase poverty. Under the circumstances, the hypothesis that rural Northeast Thailand exhibits characteristics that would suggest the existence of a poverty-HIV/AIDS cycle cannot be rejected. \n \nThis thesis also provides several key contributions to the literature on HIV/AIDS and poverty. First, it provides quantitative and qualitative empirical analysis of the impacts of HIV/AIDS on households in a moderately affected region of Thailand. Second, it provides empirical analysis both on whether wealth and poverty affect the risk of HIV infection, and whether HIV infection affects wealth and poverty. The results from this thesis also provide significant empirical evidence of the importance of rural-urban migration in the spread of HIV in Asia. Finally, the thesis investigates the potential effects on the poverty-HIV/AIDS cycle of an ongoing socio-economic intervention, namely breaking the poverty-HIV/AIDS cycle via intensive rural development.

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)0.000
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.027
Threshold uncertainty score0.053

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.021
GPT teacher head0.327
Teacher spread0.305 · 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 designObservational
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

Citations1
Published2007
Admission routes1
Has abstractyes

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