Is High Sexual Desire a Risk for Women’s Relationship and Sexual Well-Being?
Bibliographic record
Abstract
Historically, women's sexual desire has been deemed socially problematic. The growing popularity of the concept of hypersexuality-which lists high sexual desire among its core components-poses a risk of re-pathologizing female sexual desire. Data from a 2014 online survey of 2,599 Croatian women aged 18-60 years was used to examine whether high sexual desire is detrimental to women's relationship and sexual well-being. Based on the highest scores on an indicator of sexual desire, 178 women were classified in the high sexual desire (HSD) group; women who scored higher than one standard deviation above the Hypersexual Disorder Screening Inventory mean were categorized in the hypersexuality (HYP) group (n = 239). Fifty-seven women met the classification criteria for both groups (HYP&HSD). Compared to other groups, the HSD was the most sexually active group. Compared to controls, the HYP and HYP&HSD groups-but not the HSD group-reported significantly more negative consequences associated with their sexuality. Compared to the HYP group, women with HSD reported better sexual function, higher sexual satisfaction, and lower odds of negative behavioral consequences. The findings suggest that, at least among women, hypersexuality should not be conflated with high sexual desire and frequent sexual activity.
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 | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".