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Record W1970128866 · doi:10.1037/a0034964

Sub-Saharan Africa’s HIV pandemic.

2014· letter· en· W1970128866 on OpenAlexaff
Chris Simms

Bibliographic record

VenueAmerican Psychologist · 2014
Typeletter
Languageen
FieldHealth Professions
TopicAdolescent Sexual and Reproductive Health
Canadian institutionsDalhousie University
Fundersnot available
KeywordsPandemicPovertyHuman immunodeficiency virus (HIV)InequalityDevelopment economicsEconomic growthPolitical scienceDemographySociologyPsychologySocioeconomicsMedicineCoronavirus disease 2019 (COVID-19)VirologyEconomicsDisease

Abstract

fetched live from OpenAlex

Longitudinal studies and household surveys suggest that sub-Saharan Africa's (SSA's) HIV/AIDS crisis is not a pandemic of the poor but rather one of inequalities, where wealthier individuals are more likely to be infected as a result of greater mobility and multiple relationships (Fox, 2012). This is in sharp contrast to the situation in the United States, where HIV infections "are concentrated among the poor with very few people in the middle and upper social strata contracting HIV" (Pellowski, Kalichman, Matthews, & Adler, May-June 2013, p. 199). Yet from a global perspective, wherein SSA is the poorest region in the world, the pandemic is of course one of poverty as well as one with pronounced racial and gender disparities. Both the May-June 2013 special issue of the American Psychologist ("HIV/AIDS: Social Determinants and Health Disparities") and another American Psychologist special issue 25 years earlier ("Psychology and AIDS," November 1988) help shed light on Africa's HIV/AIDS crisis.

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)0.001
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.026
Threshold uncertainty score0.052

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.006
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.000
Science and technology studies0.0050.001
Scholarly communication0.0020.003
Open science0.0010.002
Research integrity0.0200.015
Insufficient payload (model declined to judge)0.0130.006

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 head0.190
GPT teacher head0.469
Teacher spread0.279 · 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 designNot applicable
Domainnot available
GenreCommentary

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

Citations3
Published2014
Admission routes1
Has abstractyes

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