Women’s shelters as the final step against violence: Cases from Turkey and the world
Bibliographic record
Abstract
Purpose: The primary aim of this study is to analyze the structure, operation, and services of women’s shelters in Turkey by comparing them with models implemented in various countries. Additionally, the research evaluates the role of these institutions in promoting gender equality and combating violence against women, as well as the organizational structure and needs of shelter personnel. Materials and Methods: This study is based on a qualitative research design, incorporating literature review, analysis of national legislation, and comparative evaluation of international shelter models. The shelter systems in Turkey and other selected countries are examined through a comparative framework highlighting their strengths and weaknesses. Findings: Although women’s shelters in Turkey are supported by a legal framework, they face several structural challenges, including insufficient capacity, limited rural accessibility, and a shortage of qualified staff. Compared to European countries (Scandinavian countries, Germany, the United Kingdom), North America (the United States and Canada), and selected Asian and African countries, Turkey’s model diversity remains limited. Nevertheless, the expansion of cooperation between governmental bodies and NGOs, along with the increasing prevalence of Violence Prevention and Monitoring Centers (ŞÖNİM), are considered positive developments. Conclusion: Women’s shelters play a vital role in protecting survivors of violence and advancing gender equality. To enhance the effectiveness of shelters in Turkey, it is recommended to diversify shelter models, strengthen personnel capacity, develop child-specific support programs, and expand inclusive services particularly for vulnerable groups.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.005 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 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".