Sexual Fantasies, Sexual Trauma and the Weight of Shame: A Latent Profile Analysis
Bibliographic record
Abstract
Childhood sexual abuse (CSA) and adulthood sexual assault (ASA) have been associated with the emergence of violent and shame-filled sexual fantasies in adulthood. Shame related to sexual fantasies may be linked to psychological distress and erotophobia, yet the interplay between fantasy themes, shame, and CSA/ASA remains underexplored. This study used a three-step latent profile analysis on a sample of 1,414 Canadian adults (309 CSA and 423 ASA survivors) to examine profiles of fantasies with associated shame, to compare these according to sociodemographics, victimization experiences, psychological distress and erotophobia. Three profiles emerged: (1) Fantasy-Lite, characterized by few fantasies and low shame; (2) Submission-linked Shame, marked by numerous submissive and victimization fantasies with high shame; (3) Perpetration-linked Shame, defined by dominant and perpetration fantasies coupled with high shame. Gender and sexual orientation were associated with profile membership: women and non-heterosexual participants were more frequent in Submission-linked Shame, while men were predominant in Perpetration-linked Shame. CSA survivors were predominantly in the Perpetration-linked Shame profile, while ASA survivors were more likely to belong to the Submission-linked Shame profile. These two profiles presented significantly higher levels of psychological distress and erotophobia than Fantasy-Lite. Findings highlight distinct fantasy-shame patterns and their relevance for trauma-informed clinical interventions.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.002 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| 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".