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Record W2172905539 · doi:10.1521/aeap.2015.27.4.333

Becoming “Undetectable”: Longitudinal Narratives of Gay Men's Sex Lives After a Recent HIV Diagnosis

2015· article· en· W2172905539 on OpenAlexafffund
Daniel Grace, Sarah Chown, Michael Kwag, Malcolm Steinberg, Elgin Lim, Mark Gilbert

Bibliographic record

VenueAIDS Education and Prevention · 2015
Typearticle
Languageen
FieldMedicine
TopicHIV/AIDS Research and Interventions
Canadian institutionsOntario HIV Treatment NetworkPositive Living Society of British ColumbiaSimon Fraser UniversityBC Centre for Disease ControlPublic Health OntarioUniversity of Toronto
FundersCanadian Institutes of Health Research
KeywordsNarrativeMen who have sex with menHuman immunodeficiency virus (HIV)Qualitative researchViral loadHomosexualityMedicineSexual identityPsychologyIdentity (music)GerontologyHuman sexualityFamily medicineGender studiesSociologySyphilis

Abstract

fetched live from OpenAlex

We explore gay men's sex life narratives following their diagnosis with an acute or recent HIV infection. All participants received an acute (n = 13) or recent (n = 12) HIV diagnosis and completed a series of self-administered questionnaires and in-depth qualitative interviews over a one-year period or longer. Over the course of four qualitative interviews, participants frequently spoke of the role of medications (e.g., decisions to start treatment) and changing viral loads (e.g., discourses of becoming "undetectable") in relation to their sex lives since being diagnosed with HIV. Many men talked about milestones relating to initiating medication and viral load as informing their shifting sexual behaviors and identities as HIV-positive--or "undetectable"--gay men. The narratives of our participants provide insight regarding complex negotiations and processes of decision-making over time related to sex, counseling needs, treatment initiation, viral load, and the significance of undetectability as an emergent identity.

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)0.009
metaresearch head score (Gemma)0.023
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.010
Threshold uncertainty score0.046

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0090.023
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.001
Science and technology studies0.0090.008
Scholarly communication0.0070.008
Open science0.0020.010
Research integrity0.0020.005
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 head0.061
GPT teacher head0.387
Teacher spread0.326 · 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 designQualitative
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

Citations69
Published2015
Admission routes2
Has abstractyes

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