Bibliographic record
Abstract
Purpose. The aim of the article is to analyze the legal basis for preventing media violence against children. Method. The methodology includes a comprehensive analysis and generalization of existing scientific and theoretical material and the formulation of relevant conclusions. During the research the methods of scientific cognition were used: comparative-legal, logical-semantic, functional, system-structural, logical-normative. Results. The study recognized that it is appropriate to provide in the Law of Ukraine "On Child Protection" a ban on disclosing or publishing in the media confidential information about children in difficult life situations, if the dissemination of such information could harm the child, regardless of parental consent or other legal representatives of the child. Media violence is a form of psychological violence that involves propaganda of violence through the media if it causes emotional insecurity, inability to protect oneself, or mental health damage. The main feature of the modern information society is the recognition of the priority of information as one of the results of human activity. Most of the time behind a computer, modern man can no longer imagine his existence without it, which often leads to the formation of computer addiction. In addition, one of the urgent problems that arose in the era of information technology is the problem of cyberbullying - harassment of the Internet, through messages containing insults, intimidation. Such harassment can be applied to both adults and children. Currently, the phenomenon of cyberbullying is actively manifested in many developed foreign countries, such as the United States, Canada, the European Union and other countries, where public authorities are forced to pay more and more attention to this issue. It is almost impossible to eliminate violence in the media, as they shape their agenda based on the interest of the viewer. And, unfortunately, violence is one that attracts the attention of broad sections of the population. Therefore, educational institutions should help children to form the idea that the agenda, the methods of activity imposed by the media, have value only in the symbolic and not in the practical world. Scientific novelty. In the course of the research it was established that an important measure to prevent and counteract violence in the media may be the introduction of a special course "Violence and Media Space" in the curricula for the specialty 061 "Journalism". Practical significance. The applied value of the study is determined by the fact that the scientific results provide a basis for improving legislation in the field of prevention of media violence against children.
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How this classification was reachedexpand
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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 teacher head, 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".