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Record W2338163567 · doi:10.1080/00918369.2016.1172883

“Hedge Your Bets”: Technology’s Role in Young Gay Men’s Relationship Challenges

2016· article· en· W2338163567 on OpenAlexaff
Raymond M. McKie, Robin R. Milhausen, Nathan J. Lachowsky

Bibliographic record

VenueJournal of Homosexuality · 2016
Typearticle
Languageen
FieldPsychology
TopicSexuality, Behavior, and Technology
Canadian institutionsAIDS VancouverUniversity of TorontoUniversity of GuelphUniversity of British ColumbiaWilfrid Laurier University
Fundersnot available
KeywordsRomanceJealousyThematic analysisPsychologyReproductive healthHuman sexualitySocial psychologyDevelopmental psychologyHeteronormativityInterpersonal relationshipSexual relationshipHomosexualityGender studiesQualitative researchSociologyPopulationDemography

Abstract

fetched live from OpenAlex

Technology is playing an increasingly pervasive role among young gay men in the process of meeting potential romantic or sexual partners. We investigated challenges posed by technology related to young gay men's relationships. Focus groups (n = 9) of young gay men aged 18-24 (n = 43) were transcribed verbatim, and thematic analysis was used to identify two major themes regarding challenges to relationship development and maintenance. Subthemes include unrealistic expectations of relationships, inauthentic self-presentation online, sexual primacy over romance, increased opportunities for infidelity, and jealousy. The implications of this study for sexual education and sexual health promotion are discussed.

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)0.003
metaresearch head score (Gemma)0.009
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 score0.005
Threshold uncertainty score0.018

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.009
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0050.004
Scholarly communication0.0050.005
Open science0.0010.003
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0020.000

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 head0.102
GPT teacher head0.385
Teacher spread0.282 · 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

Citations13
Published2016
Admission routes1
Has abstractyes

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Same venueJournal of HomosexualitySame topicSexuality, Behavior, and TechnologyFrench-language works237,207