Sayısal Ortamda Zararlı Televizyon Yayınlarından Çocukların Korunması Üzerine Avrupa Birliği Çalışmaları
Bibliographic record
Abstract
This artide analyses the choice mechanisms used in European Union countries to protect children from harmful television broadcasts. It alsa throws light on the studies of European Union that are carried out to empower parents against harmful content. Finally, it focuses on the system developed for Turkish television broadcasts. The condusions the study have reached can be summarized as follows:• All member states with the exception of Luxemburg have specific systems to protect children from problematic television content.• However; these systems which largely depend on the use of watershed, visual icons and acoustic warning are generally; daimed to be not responsive to the challenges brought about by digital technology.• On the other hand,V-chip technology which is widely used in the United States and Canada is not technically feasible in Europe. Moreover; the overall studies of European Union Commission all asserted that V-chip system is not the appropriate mechanism as it does not fit to the multicultural, multilingual nature of European Union.• European Union's main objective is to harmonize the systems which are currently being used in Member Countries and in the longer run, to apply a new system which depends on parental control, media literacy and broadcaster responsibility.• As for the system developed for the Turkish television broadcasts, it can be stated that it is in line with the systems used in Member Countries. However in order to create a perfect system which copes well with Europe, it is essential to project the recent findings of the European Union's studies onto the new arrargement.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.026 | 0.005 |
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".