THE PREPARATION OF POLISH SOCIAL WORKERS TO WORK WITH PERSON EXPERIENCING DOMESTIC VIOLENCE. EDUCATIONAL EXPERIENCES AND CHALLENGES
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Today’s social worker has to face many new challenges that arise due to socio-economic and cultural changes. One of the extremely important and difficult areas of social workers' job is to work with people who are experiencing domestic violence. The aim of the following article is to show previous experience in the field of theoretical and practical social worker's training in work with people experiencing domestic violence and the difficulties arising because of the imperfections of the system (i.e. due to lack of appropriate diagnostic tools, intervention strategies and supporting institutions). To show the weaknesses of education, a secondary analysis of the data (including programs, study plans) was made and expert interviews with employees who undertake work with a person experiencing violence were conducted. The analysis allowed to propose a concept of social workers’ training in working with a person experiencing domestic violence (child, woman, elderly person), based on best practices, i.e. from Israel and Canada.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it