Sexuality and personality correlates of willingness to participate in sex research
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".