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Record W2963453359 · doi:10.1177/1461444819864903

Tinder’s lesbian digital imaginary: Investigating (im)permeable boundaries of sexual identity on a popular dating app

2019· article· en· W2963453359 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.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueNew Media & Society · 2019
Typearticle
Languageen
FieldPsychology
TopicSexuality, Behavior, and Technology
Canadian institutionsConcordia University
Fundersnot available
KeywordsLesbianThe ImaginaryQueerIdentity (music)Sexual identityTransgenderSpace (punctuation)PsychologyGender studiesSociologySocial psychologyHuman sexualityComputer sciencePsychoanalysisAestheticsArt

Abstract

fetched live from OpenAlex

Dating apps have received rapid uptake, with Tinder as one of the most popular apps in the heterosexual market. However, little research has investigated the experiences of women seeking women (WSW) on this app. This article combines two interview studies of WSW in Australia, Canada, and the United Kingdom to investigate their self-presentations of sexual identity on Tinder. By configuring settings to “seeking women,” participants perceived they were entering a space conducive to finding WSW. However, men, couples, and heterosexual women permeated this space, heightening the need for participants to signal non-heterosexual identity. Their signals fused references to lesbian and queer culture with Tinder’s infrastructure to evoke a digital imaginary, as a routinized set of practices imagined to resonate with a shared community. Although signals within this digital imaginary were sometimes playful and ambiguous, their default toward a recognizable lesbian identity often rendered other sexual or gender identities invisible.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.468
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.051
GPT teacher head0.336
Teacher spread0.285 · 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