Verification of Crime Due to Violence against Women in Karaj City and Effective Factors to Prevent It
Bibliographic record
Abstract
According to the new developments of criminology and approaches to crime victims. Victim – centered approach based on the conditions governing the development of crime and victim in order to prevent crime and reduce its implications are examined. A criminological finding suggests that some individuals for the reason that some of the special Features of biological and psychological and social victim are more at risk than others. Women often are in this context. The purpose of this research is to identify the types of violence in the city of Karaj.This research field of Karaj questionnaire about 384 women and using cluster and systematically implemented, at 2015-2016. The findings show that, there is violence in the mentioned society in various aspects. Most of the current violence is the psychological and sexual violence and economic violence is lowest. There is a direct and meaning full relationship between the notion authoritative man of his role and violence against women.Also there is an inverse and meaningful relationship between the contribution of the husband at home work and violence against women.There is a meaningful and direct relationship between men and women experience violence in their families and 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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 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) | 0.004 | 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".