Enquête sur la violence contre les femmes en Suisse - 2003
Bibliographic record
Abstract
Interest in the topic of violence against women has grown strongly over the last two decades. During the nineties, and following studies on the subject in Canada and the United States, the focus has shifted to violence against women in general, and no longer exclusively on domestic violence against women. Following the preparatory work of two UN institutes (UNICRI in Turin and HEUNI in Helsinki), and once the method had been standardized (identical questionnaire and survey method), national studies on this issue have been planned in approximately 30 countries. The Swiss survey is based on a telephone interview, between April and August 2003, of 1975 women aged 18 to 70 living in the German-speaking and the French-speaking parts of Switzerland. The sample thus obtained is representative of the female population. The method used was the computer-assisted telephone survey, which had already proved adequate in previous victimization surveys. This choice was also motivated by the great complexity of the questionnaire. The latter should indeed allow to apprehend different categories of violence, relating to different types of relationship between the author and his victim (marriage, cohabitation, former partners, colleagues, strangers) since the age of 16 years (experiences lived in childhood are not taken into account). There are several objectives for this study: - to increase the awareness of this problem among the authorities and the public - to promote prevention - to provide reliable information for the development of legislation, policies and means of assistance to victims - to set up an internationally comparable database - to help the police in their work practices concerning violence against women - to formulate and test certain hypotheses On thjs basis, here are the hypotheses and research questions: - What is the extent of this type of violence in Switzerland, compared to other countries? How to explain these differences? - How has the situation of domestic violence evolved since the study by Gillioz et al. (1994)? - How important are various factors, including situational and biographical, in experiences of violence? - What is the influence of the past and current criminal history of men on their tendency to domestic violence? - What particular interaction effects are revealed among the variables studied? - How is the role of the police perceived among the victims? - Does (institutionalized) aid to victims achieve its objectives?
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.011 | 0.001 |
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".