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Record W4393252494 · doi:10.1080/01490400.2024.2330946

A Thousand Catcalls: Survivors’ Experiences of Sexual Violence in Online Dating

2024· article· en· W4393252494 on OpenAlexafffund
Eric Filice, Amy Matharu, Diana C. Parry, Corey W. Johnson

Bibliographic record

VenueLeisure Sciences · 2024
Typearticle
Languageen
FieldPsychology
TopicSexuality, Behavior, and Technology
Canadian institutionsUniversity of WaterlooSt. Michael's Hospital
FundersSocial Sciences and Humanities Research Council
KeywordsDating violencePsychologySexual violenceSocial psychologyDevelopmental psychologyCriminologyDomestic violenceSuicide preventionPoison controlMedical emergencyMedicine

Abstract

fetched live from OpenAlex

There is growing academic interest in the leisure spaces of online dating as a specific avenue of technology-facilitated sexual violence (TFSV). Yet, limited attention is paid to survivors’ experiences and understandings of sexual violence intermediated by dating apps. Using feminist standpoint theory and an intersectional lens, in-depth interviews were conducted with 15 current and former dating app (e.g. Tinder, Grindr) users of diverse identities and backgrounds who previously experienced sexual violence. Sexual violence was found to take a multiplicity of forms spanning the “online-offline” continuum that often co-occur and mutually reinforce their effects, including sexual assault threats, image-based harassment, gender/sexuality-based hate speech, and in-person sexual coercion and/or aggression. Depending on the experience frequency and severity, psycho-social outcomes range from indifference/mild annoyance to emotional trauma and social withdrawal. Findings underscore the profound personal and collective impacts of TFSV and the urgent need for coordinated, multisectoral responses.

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 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)0.001
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: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.700
Threshold uncertainty score0.873

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
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 head0.064
GPT teacher head0.401
Teacher spread0.337 · 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 teacher head, 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

Citations8
Published2024
Admission routes2
Has abstractyes

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