Problematic Endorsement of Models Describing Sexual Response of Men and Women with a Sexual Partner
Bibliographic record
Abstract
We were interested to see the recent article entitled, “Endorsement of models describing sexual response of men and women with a sexual partner: An online survey in a population sample of Danish adults ages 20–65 years” authored by Giraldi et al. [1], and we believe that such research can add to our understanding of how people experience sexuality and sexual dysfunction. However, there are several problems with the three models presented in the study and serious problems with the choice of dysfunction measures used. First, we are curious as to the objective of asking people for just one type of sexual experience, given the large body of evidence of variety of satisfactory experience [2–6]. Investigating the possibility that sometimes having and sometimes not having a sense of sexual desire/hunger before being aware of any sexual stimulus are both normal and common was not possible in this study. Second, we are concerned about the validity of the model descriptions. We are unaware of any effort to examine whether the subjects properly understood each of the models, and whether the descriptions clearly captured the important aspects of the model. In Sand's original study, it is noted that “The wording of items assessing the fit of women's own sexual experience with any of these models was independently reviewed by senior clinicians who are extremely familiar with the models in question” [7]. We question if this method is adequate to show whether the descriptions are useful for research purposes.
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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 | 0.018 | 0.076 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.003 |
| 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".