Predictors of kink community involvement in those interested in sadism and/or masochism
Bibliographic record
Abstract
Sexual sadism (sexual arousal from controlling or causing physical pain, suffering, or humiliation) and sexual masochism (sexual arousal from being controlled or experiencing physical pain, suffering, or humiliation) are part of a spectrum of relatively common sexual interests labelled BDSM. Many people with sadistic or masochistic interests experience stigmatization related to their interests. Those interested in sadism or masochism may seek out community as a means of learning more about their interests, to engage in behaviours related to their interests with others, or to combat potential distress related to their stigmatized BDSM interests. Currently, little is known about predictors of kink community involvement. Using data from an online convenience survey sample of 743 respondents, the current study examined if interest in sadism or masochism, concomitant behaviour, and distress related to sadism and masochism interest predicted kink community involvement. Among those interested in sadism and masochism, the odds of kink community involvement were significantly greater if they engaged in more frequent sadism (OR = 1.64) or masochism (OR = 1.71). Greater interest in masochism predicted significantly greater odds of kink community involvement (OR = 1.67), but this was not true for interest in sadism. Those interested in sadism had greater odds of kink community involvement if they experienced higher levels of distress related to sadism interest (OR = 1.42); masochism-related distress was not a significant predictor. These findings highlight the importance of interest, behaviour, and distress in understanding kink community involvement and underscore the need for further research into how gender, sexual identity, and psychosocial factors shape engagement within stigmatized sexual minorities.
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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 | 0.000 | 0.003 |
| 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 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".