Development and psychometric validation of the Sexual Fantasies and Behaviors Inventory.
Bibliographic record
Abstract
To date, no measures of sexual fantasies and behaviors have been tested using modern structural equation modeling techniques. A total of 4,280 adults from the U.S., U.K., Canada, and Ireland completed a measure of diverse (paraphilic and normophilic) sexual fantasies and behaviors. Data were randomly split in half for a two-part analysis. First, an exploratory factor analysis (EFA) was performed to reduce the item pool and determine general factor structure. Second, we tested several models using confirmatory factor analysis (CFA) and exploratory structural equation modeling (ESEM). These were followed by tests of measurement invariance (based on sex and sexual orientation) and criterion validity. For both the fantasies and behaviors, bifactor ESEMs were the most appropriate models. Similar specific factors emerged: (a) normophilia, (b) rough sex, (c) interest of intrusion, (d) assuming power, and (e) relinquishing power. Findings suggest that sexual interests show a hierarchical measurement structure. Males and nonheterosexuals had higher general fantasy scores; nonheterosexuals had higher general behavior scores. Heterosexuals generally scored lower than nonheterosexuals. Fantasy and behavior scores were positively related to Dark Triad traits and sociosexuality, and there were weak or no relationships with depression and anxiety. Results support the psychometric validation of the Sexual Fantasies and Behaviors Inventory. Strengths of this study include a large nonclinical sample with relevant psychological correlates and the use of modern psychometric methods. However, the use of an internet sample with self-report measures may be unrepresentative, although the internet has the advantage of being able to recruit from stigmatized groups. (PsycInfo Database Record (c) 2022 APA, all rights reserved).
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".