18. Sexual Self-Schemas and Neural Processing of Sexual Information in Women
Bibliographic record
Abstract
Previous research suggests that humans respond differently to reproductively-relevant information in the environment, including heightened neural responses to sexual versus non-sexual cues. Limited research, however, has examined individual variation in the early neural processing of sexual information. Sexual self-schemas, or one’s views of themselves as a sexual person, provide a stable cognitive framework for processing sexually-relevant information, and may relate to women’s sexual responses. This study seeks to examine how women’s sexual self-schemas relate to the early neural processing of sexual information and their subsequent subjective sexual arousal. Twenty women are being recruited from the Queen’s psychology subject pool and data collection is currently underway. I am assessing women’s neural responses to sexual and non-sexual images (i.e., erect penises versus elbows) using electroencephalography (EEG), and women are reporting their feelings of arousal to the sexual images. Women are also completing a measure of sexual self-schemas. I predict that women who have more positive sexual self-schema scores will have a stronger neural response to sexual stimuli than women with more negative schema scores. In addition, I predict that women with more positive schema scores will self-report higher sexual arousal than women with more negative scores. The findings of this study will improve our understanding of the role of sexual self-schemas and early neural processing in women’s sexual response, thus lending to the development of a comprehensive, empirically-supported model of sexual response that accounts for within-gender variability.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| 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".