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Record W4413636946 · doi:10.1093/bjsw/bcaf169

From private to public: Analyzing the dynamics of nonconsensual sexts in the digital age

2025· article· en· W4413636946 on OpenAlexafffundabout
Faye Mishna, Shannon Brown, Lana J. Jeries-Loulou, Mona Khoury‐Kassabri, Kara Brisson-Boivin, Andrea Slane, Wendy Craig, Rachelle Ashcroft, Debra Pepler

Bibliographic record

VenueThe British Journal of Social Work · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicGender, Feminism, and Media
Canadian institutionsOntario Tech UniversityYork UniversityUniversity of Toronto
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsDynamics (music)PsychologyBusinessAdvertising

Abstract

fetched live from OpenAlex

Abstract Previous research has found that gender is central to both consensually sending and receiving sexts and nonconsensual sharing. This research often spotlights girls as being responsible and explains that boys’ roles as perpetrators in these interactions are made invisible. We aimed to investigate the feelings, harms, responses, and dynamics of nonconsensual sexting in a sample of Canadian adolescents. Exploratory surveys were administered to adolescents (eleven to nineteen years) who had experienced (n = 73) or engaged (n = 40) in the nonconsensual dissemination of sexts. In the experienced sample, a majority had negative feelings; males tended to have fewer negative feelings. Most told someone outside of school, which females were more likely to find helpful. There was a statistically significant relationship in the engaged sample, with a higher proportion of males than females reporting positive feelings and/or no harm. Gender dynamics and societal norms influence how adolescents respond to sexting experiences, emphasizing the need for education and prevention strategies.

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)0.002
metaresearch head score (Gemma)0.001
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 score0.509
Threshold uncertainty score0.903

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
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 head0.021
GPT teacher head0.298
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

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

Citations0
Published2025
Admission routes3
Has abstractyes

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