The Sexual Communication Scale (SeCS)
Bibliographic record
Abstract
Many measures of comfort and frequency of sexual communication between partners are limited in gender/sex and sexual orientation inclusivity, how constructs are measured, and for whom. We conducted two studies to investigate a revised and extended version of the Female Partner’s Communication During Sexual Activity Scale: the Sexual Communication Scale (SeCS). We revised the gender/sex language to improve inclusion and added items to assess frequency and comfort with sexual communication. In Study 1, an exploratory factor analysis (n = 578) supported a three-factor structure (Frequency of bidirectional communication, α = .96; Ease of own communication, α = .90; Ease of partner’s communication, α = .83). In Study 2, a confirmatory factor analysis (n = 1479) further supported the three-factor structure. Specifically, the three-factor model provided a reasonably good fit (χ2 (44) = 511.35, p < .001, CFI = .97, GFI = .95, AGFI = .91, SRMR = .00, RMSEA = .08). In both studies, we found small or no differences in men and women’s comfort and frequency of sexual communication. The results provide initial support that the SeCS is an internally consistent, multidimensional gender/sex inclusive tool for future research on sexual communication.
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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 | 0.002 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.015 | 0.002 |
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".