Sex guilt or sanctification? The indirect role of religiosity on sexual satisfaction.
Bibliographic record
Abstract
With a Mechanical Turk sample of 1,614 sexually active individuals (62.6% women, 85% heterosexual, mean age of 34.47 years) who had been in a committed sexual relationship for a least two years, we used structural equation modeling to better understand how global religiosity may indirectly influence sexual satisfaction. Because religiosity has been linked to the way people make sense of sexuality, we assessed positive (sexual sanctification) and negative (sexual guilt) meaning making variables as mediators between religiosity and sexual satisfaction. Consistent with prior research, greater sanctification of sexuality was directly tied to greater sexual satisfaction, whereas greater sexual guilt was directly tied to less sexual satisfaction. Greater general religiosity was indirectly related to greater sexual satisfaction for men and women through greater sexual sanctification. Contrary to expectations, no significant pathways emerged between greater religiosity and less sexual satisfaction via sexual guilt, possibly due to reliance on a one item indicator for the latter variable. Also, in structural equation models, when sanctification of sexuality was taken into account, greater religiosity was directly tied to less sexual satisfaction for women, but not for men. This suggests that sanctification of sexuality represents a facet of religiousness that facilitates women's and men's sexual satisfaction, whereas other religious beliefs may inhibit women's sexual satisfaction.
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 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 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".