Bibliographic record
Abstract
Women faking orgasm has been identified as a common and widespread practice, particularly in the context of heterosexual sex. While feigning pleasure has been the subject of extensive scholarly inquiry, almost no research attention has been applied to women’s experiences of resisting this normative practice. We adopted a discourse analytic approach to explore the question: If faking orgasm is often compulsory, how do women resist this practice and what does it mean when they do? Participants were 15 undergraduate students who ranged in age from 19 to 28. We identified the mobilization of several discursive patterns in their accounts. First, participants mobilized a “future pleasures” discourse to highlight the importance of resisting faking orgasm in order to increase their chances of experiencing genuine pleasure. Second, they positioned sexual satisfaction as an “equal right” to which they were entitled. In some instances, this was discussed in terms of reciprocity, in which pleasure is given and received. In others, it was positioned as a feminist issue of gender and power. Third, participants highlighted the importance of deflecting blame for absent orgasm in order to avoid hurting one’s partner. Fourth, participants described the role of pain as either a factor that prevented them from faking pleasure or that motivated them to fake orgasm in order to end painful sex. We conclude that an equal rights discourse, framed as a feminist issue, holds the most promise as a means of discursive resistance. At the same time, we highlight the significant risks for women of both faking orgasm and not faking orgasm and the delicate discursive work required when an expected orgasm is not experienced. We suggest that efforts to support women’s sexual health and equality are enhanced by better understanding the emancipatory potential of various discursive constructions as well as their limitations and risks. The merits and challenges of each pattern of accounting are discussed in the context of broader scholarship in the area of discursive resistance.
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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 | 0.006 | 0.021 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.007 | 0.011 |
| Scholarly communication | 0.004 | 0.005 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.007 | 0.002 |
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".