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Record W2996003773 · doi:10.1080/09718524.2019.1684022

Grinding against HIV discourse: a critical exploration of social sexual practices in gay cruising apps

2019· article· en· W2996003773 on OpenAlex
Matthew Numer, Dave Holmes, Phillip Joy, Ryan Thompson, Nicole Doria

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

VenueGender Technology and Development · 2019
Typearticle
Languageen
FieldPsychology
TopicSexuality, Behavior, and Technology
Canadian institutionsDalhousie University
Fundersnot available
KeywordsHuman immunodeficiency virus (HIV)Men who have sex with menQueerQualitative researchPsychologyGender studiesSociologySocial psychologyDevelopmental psychologyMedicineVirology

Abstract

fetched live from OpenAlex

Social networking applications (SNAs), such as Grindr, are shaping the identities and sexual practices of gay, bisexual and other men who have sex with men (GBM). This qualitative study aimed to gain a deeper understanding of the role of such technologies in social sexual practices, particularly in relation to risk management and prevention of HIV and other sexually transmitted blood-borne infections (STBBIs). Poststructuralism and queer theory were used to critically examine the relationship between GBM and SNAs in a sample of people who use Grindr. Sixteen people, identifying as men who used Grindr, were interviewed. Discourse analysis was employed to critically examine the relationship between GBM and SNAs, and three threads of discourse emerged: Language and images, Filtering, and Trust. These threads of discourse provide insight into how the sexual beliefs, values, and practices of GBM are shaped on SNAs.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.477
Threshold uncertainty score0.796

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.139
GPT teacher head0.417
Teacher spread0.278 · 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