Vulnerability and variability: Associations between various early forms of nonconsensual sexual experiences and later sexual experiences of young adults
Bibliographic record
Abstract
Early nonconsensual sexual experiences (NSEs) in childhood or adolescence have been linked to elevated risk for adjustment problems and later victimization in some research, whereas others find little or no associations between NSEs and later sexual experiences. The current study examined how a range of early NSEs are linked to both consensual and nonconsensual sexual experiences among young adults, as well as consideration of the familial versus non-familial nature of the perpetrator—victim relationship, an often-overlooked factor. A sample of 520 young adults (68% female; 18–25 years) completed anonymous surveys that assessed sexual experiences before and after age 16. Our results demonstrated that 6.9% of participants reported at least one episode of NSEs under the age of 16 with family members, 3.5% with non-familial adults, but far more (39.2%) with same-age peers. Early NSEs with family members and non-family adults were linked to experiences of sexual assaults after age 16 for both male and female participants. Early NSEs with peers were linked to later sexual assaults for female participants only. Careful consideration must be given to identifying types of early sexual experiences in efforts to understand their differential links to young adults’ experiences. Implications for improving scientific communication and operationalizing NSEs more precisely to advance research in this area are discussed.
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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 | 0.001 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".