Violence against children in families and role of kindergarden in discovering, suspect
Bibliographic record
Abstract
The purpose of this diploma is to analyse how well teachers in kindergartens and their assistants know the legislation that deals with violence against children within families. The goal is also to discover, how well they are aware of child abuse, how well they are able to recognize signs of violence and if they know how to intervene. \nIn theoretical part of diploma I describe possible forms and symptoms of violence against children within families. I present the role of kindergarten when detecting it and the regulations upon which employees can intervene. \nIn empirical part I present the results of survey that was taken in kindergartens in Slovenia among teachers and their assistants. They had to recognize different types of violence and to asses which types in their opinion appear more commonly. They were also asked to estimate how well they know the “Regulatory book on prevention violence against children within family”. They were asked to tell whether they would stand in court, and to state dilemmas when facing cases of violence against children within family. Most of them (95 %) believed that violence manifests in all forms of physical violence, while almost quarter of them considered yelling not to be a form of violence. Also as most commonly appeared type of violence they chose physical violence (68 %). \nAlmost ¾ of them estimated their knowledge of the “Regulatory book on preventing violence against children within families” as good. Yet, more than a third of them (38 %), when stating dilemmas, doubted that a child would speak the truth. Therefore, I believe that they overestimated their knowledge of the regulations. Further on, participants considered that they are not qualified well enough to intervene: Less than a fifth of them thought that they are well qualified for that, and almost half of them as moderately qualified. \n \n
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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 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 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".