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Record W2911228205 · doi:10.3138/cjhs.2018-0028

Sexuality and personality correlates of willingness to participate in sex research

2019· article· en· W2911228205 on OpenAlexaffvenue
Katrina N. Bouchard, Jeremy G. Stewart, Stéphanie C. Boyer, Ronald R. Holden, Caroline F. Pukall

Bibliographic record

VenueThe Canadian Journal of Human Sexuality · 2019
Typearticle
Languageen
FieldPsychology
TopicEvolutionary Psychology and Human Behavior
Canadian institutionsQueen's University
Fundersnot available
KeywordsPsychologyGeneralizability theoryIntrusivenessPersonalitySocial psychologyClinical psychologyDevelopmental psychology

Abstract

fetched live from OpenAlex

Sex research is viewed as being particularly susceptible to volunteer bias, especially those studies that involve genital response measurement. Willingness to participate in sex research may be affected by study procedures, including the intrusiveness of devices measuring genital response, but this topic is seldom examined empirically. A community sample of 364 women and 117 men completed an online survey assessing willingness to participate in 15 sex research scenarios as well as measures of sexual attitudes, behaviours, and personality. As hypothesized, the presence versus absence of genital exposure, rather than the degree or type, impacted willingness ratings, such that participants were more willing to partake in studies in which they remained clothed versus studies that involved getting undressed. Erotophilic attitudes were associated with willingness to participate in unclothed and clothed research procedures for women and men, and sexual orientation impacted women’s willingness ratings for both types of research. Although some personality factors were correlated with willingness ratings, they generally did not explain additional variance in willingness beyond the associations of other correlates. This study provides a critical update on volunteer bias in sex research and demonstrates that self-selection biases may impact the generalizability of sex research assessing community samples of women and men.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.125
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0090.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.185
GPT teacher head0.453
Teacher spread0.268 · 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

Citations27
Published2019
Admission routes2
Has abstractyes

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