Gender beliefs and legitimization of dating violence in adolescents
Bibliographic record
Abstract
Abstract Background and aim Knowing the gender beliefs (GB) that legitimize dating violence (DV) it is important for the prevention of this phenomenon. The aim is to evaluate the impact of GB interventions that legitimize DV. Methods Single group quasi-experimental study, with a sample of 148 Portuguese adolescents. A questionnaire was used to collect data, with data processing carried out using SPSS, using descriptive and inferential statistics. Results The interventions included an infographic on gender asymmetries, a video about DV, and posters on the topic and Health Education sessions. The largest group fell into the less conservative GB (40.5%) and the categories of non-violent relationship and considerably violent relationship had the same percentage (38.5%). The rank mean of the gender belief inventory scale before and after the interventions was, respectively, 35.24 and 33.06 points, while the same measurements of the violent youth relations inventory scale were 2.74 and 1.63 points. There were statistically significant differences (Wilcoxon: p = 0.01) between the GB score before and after the interventions, as well as in the violent youth relations (VYR) scale score (Wilcoxon: p = 0.000). Conclusion The interventions had a significant impact on reducing the GB legitimizing the DV and VYR, and were effective.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".