Attachment Style, Early Sexual Intercourse, and Dating Aggression Victimization
Bibliographic record
Abstract
The present study examined relations between attachment style, age at first sexual intercourse, and dating aggression (DA) victimization. In all, 137 heterosexual female undergraduate students 18 to 25 years of age (M = 20.76, SD = 1.87) completed an online questionnaire that included questions regarding sexual history, attachment style (Experiences in Close Relationships Scale), and DA (Conflict in Adolescent Dating Relationships Inventory). Initial bivariate correlations revealed that women reported higher rates of DA victimization if they were more anxiously attached (r = .30, p = .000), had an earlier age at vaginal sexual debut (r = -.19, p = .015), and had an earlier age at oral sexual debut (r = -.15, p = .046); however, when entered into a predictive multivariate model, neither the addition of anxious attachment nor an early age at sexual debut accounted for a significant amount of variance above and beyond control variables. Although we were unable to affirm anxious attachment and an early age at first intercourse as risk factors for DA victimization, posthoc analyses emphasized the need to control for social desirability when gathering information on sensitive topics in clinical and research settings.
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 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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".