Female Masturbatory Practices and Sexual Health: A Qualitative Exploration of Women's Perspectives
Bibliographic record
Abstract
Women’s sexuality has long been repressed, and many studies still find that women experience restraint and negativity regarding masturbation and their right to sexual pleasure (Hogarth & Ingham, 2009; Kaestle & Allen, 2011). Previous work looking at women’s masturbation has failed to understand how it is related to sexual health. This qualitative exploratory research’s aim is to better understand how women’s regular masturbation (defined as once per month or more) modulates their sexual health through the development of their sexual self-concept (Deutsch & al., 2014). Thirteen women between the ages of 18 and 30 who masturbate regularly participated in individual semi-directed interviews. Preliminary analysis, through sexual self-concept and feminist theory, indicate that these women have a better understanding of their sexual selves in that they more easily recognize and acknowledge their sexual needs. For example, they were confidant in naming exactly what brought them pleasure in partner sex. However, women seem to refrain from talking to each other about their masturbatory practices, which only escalates their impression of being the only ones to do it and their feelings of guilt. These last findings suggest that social pressures and norms compromise women’s ability to share freely about their sexual practices. Herein lies the importance and pertinence of openly discussing female masturbation and to include this subject matter in future sexuality education curricula.
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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 | 0.010 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.008 | 0.008 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.003 |
| 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".