The Perceived Equity and Equality of Sexual Practices Scale: Validation of a measure of equity and equality within couples
Bibliographic record
Abstract
The goal of the current study was to validate the Perceived Equity and Equality of Sexual Practices Scale (PEESP). A total of 296 undergraduate students from a French-Canadian university completed the PEESP scale in addition to measures of sexual and couple satisfaction. Exploratory factorial analyses revealed three factors underlying the perception of one's contribution to the couple's sex life: implication, expression of discomfort, and sharing. These subscales were replicated for the perception of the partner's contribution to the couple's sex life which allowed three scores to be computed assessing the perceived equality of the contributions to the couple's sex life. Correlations were found between the nine subscales and the levels of couple and sexual satisfaction, thus indicating convergent validity. Internal consistency and test-retest reliability over a two-week period were satisfactory for all subscales. The perception of sexual equity was also assessed by two global questions inspired by previous measures. MANOVAs showed that individuals who perceived themselves as being in a sexually equitable relationship were more satisfied with their couple and sexual life compared to sexually under-benefitted individuals. Results show that the PEESP is a promising instrument for use in clinical and research settings.
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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 | 0.006 | 0.010 |
| 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 | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".