MétaCan
Menu
Back to cohort
Record W3038587074 · doi:10.1177/1363460720932379

Party-n-Play and online information and communication technologies: A socio-linguistic perspective

2020· article· en· W3038587074 on OpenAlexafffundabout
Rusty Souleymanov, David J. Brennan, Carmen H. Logie, Dan Allman, Shelley L. Craig, Perry N. Halkitis

Bibliographic record

VenueSexualities · 2020
Typearticle
Languageen
FieldPsychology
TopicSexuality, Behavior, and Technology
Canadian institutionsUniversity of TorontoUniversity of Manitoba
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsBiopowerPerspective (graphical)SociologyGender studiesCritical discourse analysisDiscourse analysisHomosexualityPsychologyPoliticsLinguisticsPolitical science

Abstract

fetched live from OpenAlex

This study examined the discourses of gay and bisexual men who seek Party-n-Play (PNP; sex that occurs under the influence of drugs) on mobile apps and websites. In-depth interviews were conducted with 44 gay and bisexual men who lived in Toronto, and who used drugs before or during sex in the previous month. Data were analysed using critical discourse analysis. The study findings presented evidence for subcultural discourses of gay and bisexual men who seek PNP online, and revealed how these discourses were implicated in recasting the practices of biopolitics, as well as enacting risk subjectivities of these men.

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)0.005
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 score0.014
Threshold uncertainty score0.035

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.005
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.002
Science and technology studies0.0090.027
Scholarly communication0.0130.008
Open science0.0010.006
Research integrity0.0020.002
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 head0.057
GPT teacher head0.359
Teacher spread0.301 · 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

Citations25
Published2020
Admission routes3
Has abstractyes

Explore more

Same venueSexualitiesSame topicSexuality, Behavior, and TechnologyFrench-language works237,207