Exploring Male Multiple Orgasm in a Large Online Sample: Refining Our Understanding
Bibliographic record
Abstract
BACKGROUND: The scientific literature on multiple orgasm in males is small. There is little consensus on a definition, and significant controversy about whether multiple orgasm is a unitary experience. AIMS: This study has 2 goals: (i) describing the experience of male multiple orgasm; (ii) investigating whether there are different profiles of multiple orgasm in men. METHODS: Data from a culturally diverse online convenience sample of 122 men reporting multiple orgasm were collected. Data reduction analyses were conducted using principal components analysis (PCA) on 13 variables of interest derived from theory and the existing literature. A K-means cluster analysis followed, from which a 4-cluster solution was retained. RESULTS: While the range of reported orgasms varied from 2 to 30, the majority (79.5%, N = 97) of participants experienced between 2 and 4 orgasms separated by a specific time interval during which further stimulation was required to achieve another orgasm. Most participants reported maintaining their erections throughout and ejaculating with every orgasm. Age was not a significant correlate of the multiple orgasm experience which occurred more frequently in a dyadic context. Four different profiles of multiorgasmic men were described. STRENGTHS & LIMITATIONS: This study constitutes a rare attempt to collect systematic self-report data concerning the experience of multiple orgasm in a relatively large sample. Limitations include the lack of validated measures, memory bias associated with self-reported data and retrospective designs, the lack of a control group and of physiological measurement. CONCLUSION: Our study suggests that multiple orgasm in men is not a unitary phenomenon and sets the stage for future self-report and laboratory study. Griffin-Mathieu G, Berry M, Shtarkshall RA, Amsel R, Binik YM, Gérard M. Exploring Male Multiple Orgasm in a Large Online Sample: Refining Our Understanding. J Sex Med 2021;XX:XXX-XXX.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".