In-group Identification and In-person Activities as Mediators of the Association Between Social Motivation and Psychological Well-being in the Kink Community
Bibliographic record
Abstract
The importance of social interaction on well-being has been investigated in a variety of social psychological domains (e.g., homelessness, addiction, and immigration); however, little research has been conducted on the associations between social motivation, community, and well-being within BDSM/kink practitioners. Previous literature has found that feelings of in-group inclusion and attending events predicted well-being in other sexual minority communities; therefore, the current study examines the association between social motivation, in-group inclusion, attending events, and well-being within the BDSM/kink community. A mediational model was tested, and it was found that social motivation significantly predicted well-being through both in-group inclusion and attending events. Additionally, beyond the serial mediation model, both identification with the kink community and attending events were significant mediators on their own. Participation in a BDSM community constitutes a large part of kink for many individuals, meaning that feelings of in-group inclusion and attending community events are likely vital for increasing and maintaining well-being. Marginalized communities often find solace, comfort, and acceptance through community, highlighting the importance of socialization for health and well-being. The study concludes with a discussion on implications, future directions, and the value of community in BDSM/kink communities.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 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".