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Record W2122357416 · doi:10.1257/aer.103.3.298

Fidelity Networks and Long-Run Trends in HIV/AIDS Gender Gaps

2013· article· en· W2122357416 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

VenueAmerican Economic Review · 2013
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicGame Theory and Voting Systems
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsPairwise comparisonMatching (statistics)FidelityHuman immunodeficiency virus (HIV)PopulationDemographic economicsEconomicsPsychologyDemographySocial psychologySociologyMedicineDevelopmental psychologyComputer scienceVirologyTelecommunications

Abstract

fetched live from OpenAlex

More than half of the HIV/AIDS-infected population today are women. We study a dynamic model of (in)fidelity, which explains the HIV/AIDS gender gap by the configuration of sexual networks. Each individual desires sexual relationships with opposite sex individuals. Two Markov matching processes are defined, each corresponding to a different culture of gender relations. The first process leads to egalitarian pairwise stable networks in the long run, and HIV/AIDS is equally prevalent among men and women. The second process leads to anti-egalitarian pairwise stable networks reflecting male domination, and women bear a greater burden. The results are consistent with empirical observations.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.317
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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)0.0020.002

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 head0.030
GPT teacher head0.253
Teacher spread0.223 · 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