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Record W2955418693 · doi:10.3138/cjhs.2019-0011

Sexting outside the primary relationship: Prevalence, relationship influences, physical engagement, and perceptions of “cheating”

2019· article· en· W2955418693 on OpenAlexaffvenue
Tasha Falconer, Terry P. Humphreys

Bibliographic record

VenueThe Canadian Journal of Human Sexuality · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicGender, Feminism, and Media
Canadian institutionsTrent University
Fundersnot available
KeywordsCheatingPsychologySexual relationshipSocial psychologyContext (archaeology)PerceptionSexual behaviorPositive relationshipDevelopmental psychologyHuman sexualitySociologyGender studiesGeography

Abstract

fetched live from OpenAlex

Research has not yet investigated the frequency of sexting outside of a primary relationship. Research consistently shows that most sexting occurs within the context of a relationship, but few studies have taken relationship status into account. Additionally, limited research has investigated if sexting is considered infidelity. This study aims to fill those gaps by examining sexting outside of the primary relationship. University students and community members were asked about their sexting activities outside of their primary relationship using an online questionnaire. Results indicate that 23% of participants have sexted outside of their relationship. Those who cohabitate with their primary partner or are in a non-monogamous relationship are more likely to sext with a secondary partner. The majority of people who sext outside of their relationship do so with five or less partners and do so less than once a month, indicating that sexting outside of the primary relationship is infrequent. Seventy-five percent of those that sexted secondary partners considered this act cheating. Lastly, 36% also engaged in face-to-face sexual activity with the secondary partners they sexted. The importance of considering relationship status variables in understanding sexting and infidelity is discussed.

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)0.005
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.157
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.086
GPT teacher head0.355
Teacher spread0.269 · 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.

Study designObservational
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

Citations6
Published2019
Admission routes2
Has abstractyes

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