Bibliographic record
Abstract
Purpose The purpose of this study was to determine the attitudes of university students towards domestic violence against women. Methods This cross-sectional study was conducted on students attending the School of Nursing and School of Physical Therapy and Rehabilitation at a university in Turkey. The study was conducted between February 2015 and May 2015. The study was conducted on 415 volunteer students without resorting to the sampling selection method. Data were collected using a Personal Information Form and The Scale of Attitude Toward Domestic Violence. The data were analysed using frequencies, means, standard deviations, independent t-tests and ANOVA. Results The mean of attitude scores of university students toward domestic violence were 23.13 ± 6.66 and were affected by variables such as gender, and whether the questions should be asked to women who experienced domestic violence such as: “Does your partner have justified reasons for applying domestic violence against women?” and “Should domestic violence against women be shared by others?” and “Does domestic violence against women bother you?” (p<0.05). Conclusion In this study, the mean of attitude scores of university students toward domestic violence were found to be low and their attitudes toward domestic violence were found to be unfavorable. It was suggested that education programs (seminars and conferences) consisting of information, guidance, stimulation and prevention be organized to reach out to university students who are interested in domestic violence against women.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".