“When You’re in a Relationship, You Say No, but Your Partner Insists”: Sexual Dating Violence and Ambiguity Among Girls and Young Women
Bibliographic record
Abstract
Sexual dating violence (DV) is highly prevalent and associated with deleterious outcomes. Unfortunately, this form of violence remains poorly understood. Furthermore, the measures used to assess sexual DV may not account for the various manifestations of sexual DV, which limits our understanding of this problem. This study aimed to (a) explore how girls and young women describe their experiences of sexual DV and (b) explore whether the taxonomy on intimate partner sexual violence developed by Bagwell-Gray and colleagues could be applicable to girls and young women's experiences of sexual DV. A total of 71 adolescent girls and young women who identified themselves as heterosexual were recruited. Sexual DV was assessed using an adapted version of the Sexual Experiences Survey, followed by a semistructured interview. Findings revealed that 29.6% of participants reported sexual DV victimization in the past 12 months. A direct content analysis was performed based on the taxonomy of Bagwell-Gray and colleagues. Four manifestations of sexual DV were illustrated from the youth's narratives: (a) sexual coercion, (b) sexual assault, (c) sexual abuse, and (d) forced sexual activities. Our results underscore the ambiguity of sexual consent and definition of sexual DV among adolescent girls and young women. This research further supports the necessity to develop and implement prevention programs that specifically target sexual DV in this population.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.001 | 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 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".