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Record W2809647478 · doi:10.1080/00224499.2018.1475546

Loving Oneself: The Associations Among Sexually Explicit Media, Body Image, and Perceived Realism

2018· article· en· W2809647478 on OpenAlexaff
Emily A. Vogels

Bibliographic record

VenueThe Journal of Sex Research · 2018
Typearticle
Languageen
FieldPsychology
TopicSexuality, Behavior, and Technology
Canadian institutionsUniversity of New Brunswick
Fundersnot available
KeywordsPsychologyPerceptionAssociation (psychology)RealismSocial psychologyArt

Abstract

fetched live from OpenAlex

Online sexually explicit material (SEM) is a popular media source, but little is known about its association with body image. This study explored whether perceived realism of SEM mediated the direct association of SEM use on body image while accounting for gender differences. Young adults (N = 393; ages 19 to 30; 53.4% women) recruited through a crowdsourcing Web site completed an anonymous online survey that assessed SEM use, perceptions of the realism of SEM, and body image. Body satisfaction, genital self-image, comfort being nude, penis-/breast-size satisfaction, and self-esteem were used to create the variable of body image. SEM use had a positive indirect association with body image through perceived realism for both men and women. Follow-up analyses revealed this association was due to body satisfaction and self-esteem in men and comfort being nude and self-esteem in women. Findings are discussed in terms of implications for clinical applications and understanding young adults’ body image.

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)0.009
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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.653
Threshold uncertainty score0.670

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0090.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.002
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 head0.113
GPT teacher head0.445
Teacher spread0.332 · 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 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

Citations29
Published2018
Admission routes1
Has abstractyes

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