What’s God got to do with it? The relationship between religion, sadism, and masochism
Bibliographic record
Abstract
Although “BDSM” (i.e., bondage, discipline, dominance, submission, sadism, and masochism) has become increasingly present in popular media in recent years, much remains unknown about the etiology and correlates of BDSM. Research has demonstrated a relationship between religion and sexual behaviours/attitudes; therefore, religion could also be associated with sadism and masochism. To address gaps in existing knowledge, we conducted an online survey of 515 participants who answered a questionnaire on sexual life and behaviour, including questions on arousal in response to sadism and masochism scenarios, associated negative impacts, and religion. We found a higher prevalence of arousal in response to sadism scenarios amongst non-religious participants (64.6%; n = 228/353) than religious participants (54.7%; n = 88/161) with a small, but potentially meaningful effect size (Φ = -.095, p = .032). Increased impact of religious beliefs on sex life was associated with slightly lower sadism arousal, r(499) = -.080, p = .075. This association was strong enough to be considered a potentially meaningful factor but was not statistically significant. There was also a small negative correlation between masochism arousal and impact of religious beliefs on sex life and behaviour, r(500) = -.129, p = .004. Based on these findings, we conclude that there could be a limited but meaningful relationship between religion and sadism/masochism arousal. Further research should explore specific religious affiliations and beliefs as potentially associated with sadism and masochism arousal.
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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 | 0.001 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 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) | 0.002 | 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".