Child's Privacy Jurisprudence and International Instruments
Bibliographic record
Abstract
In the privacy rights of Shiite jurisprudence Iran directly noted instances of its use of the term is limited including the need to protect the privacy of the place with the explicit text of the Holy Quran. It's important to enter the house without letting others do not the civil rights of the Islamic Republic of Iran, which is Shiite jurisprudence emanating from pointed to some evidences of privacy. But in international documents under human rights law and conventions of privacy have been more effectively different categories of persons referred to in the privacy in Shiite jurisprudence and civil rights and the fundamental rights of the Islamic Republic of Iran. However, also examples of human beings considered independently about the child's privacy is something not stated. Although, due to the arrival of children, especially in social virtual communities appear to need immediate attention to children's privacy by lawyers. The drafters of civil law is necessary and international measures to develop laws in this case was conducted including raising the age to 16 years joined children to social networks can be mentioned which is also protect the privacy of physical and sexual children abuse. All psychologists’ attention and extreme caution is ding to conflicts. According to the children defenseless against this social problem that should be subject to specific and severe punishment for properties compared with adults who are physically punished are more defense capabilities and reason legislators should be.
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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 | 0.010 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.043 |
| Scholarly communication | 0.008 | 0.004 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.008 | 0.012 |
| Insufficient payload (model declined to judge) | 0.003 | 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".