Sex dreams: Gender, erotophilia, and sociosexuality as predictors of content, valence, and frequency
Bibliographic record
Abstract
The continuity hypothesis suggests that dream content is directly related to waking life experiences, personality traits, and gender; however, little is known about sexual dreaming. To address this gap, the current study examined how gender, sociosexuality (one’s willingness to engage in sexual relations outside of committed relationships) and erotophilia (a learned disposition to respond positively to sexual stimuli) related to the content, frequency, and valence of sexual dreams. Participants (n = 482) completed an online survey assessing their sex dream experiences, sociosexuality, and erotophilia and were asked to describe their most recent sexual dream. Men scored higher on sociosexuality and sex dream valence than women, but there were no gender differences in erotophilia or sex dream frequency. Individuals who scored higher on sociosexuality and erotophilia reported experiencing more frequent sex dreams and evaluated them more positively. Hierarchical regression analysis demonstrated that erotophilia and sociosexuality significantly predicted sex dream valence, accounting for 24.3% of the variance. The addition of gender at step 2 was significant, but only accounted for an additional 1.9% of the variance. Participants’ descriptions of their most recent sex dream were analyzed for common themes related to variables such as the partner(s) involved (most common: current partner), location (most common: house/apartment), and types of sexual behaviors involved (most common: kissing). Exploratory analyses, limitations, and future directions are discussed.
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 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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".