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Record W2343376698 · doi:10.5539/jpl.v9n3p16

Corporal Punishment of Children in Iranian Law and International Instruments

2016· article· en· W2343376698 on OpenAlexvenueno aff
Ahmad Reza Behniafar, Mahmood Poyan

Bibliographic record

VenueJournal of Politics and Law · 2016
Typearticle
Languageen
FieldMedicine
TopicEthics and Legal Issues in Pediatric Healthcare
Canadian institutionsnot available
Fundersnot available
KeywordsCorporal punishmentLawPunishment (psychology)JurisprudencePolitical scienceSanctionsLegislationForgivenessHuman rightsSociologyPsychologySocial psychology

Abstract

fetched live from OpenAlex

Corporal punishment of children in their education are important issues that historically have been accepted and Yankvhsh Unfortunately in today's society has neglected the rights of children and adults of these rights by violated. Islamic jurisprudence is recommended to right what ways? As well as laws have been codified in law what is? In the verses of Quran and Hadith from the infallible Imams come from (PBUH) emphasizes the reverence, love, forgiveness, compassion and Rfq and productive than children. On Islamic law, as is early in the punishment of child esteem and under certain conditions as a measure to maintain the system for training and behavior modification, family and children, voided, and to protect the interests, sanctions such as liability and responsibility, provided is. In this regard, in particular understanding of Islam and Shiite jurisprudence that laws in our country is the source and the directive could be an important step for appropriate legislation B for children. The law tries years of punishment and corporal punishment of children to prevent and eliminate this phenomenon in human society and in recent years a comprehensive international instrument to assert the rights of children and the prohibition of corporal punishment for exercising their raised have. Thus, at the outset, and seemingly contradictory approaches is formed. Therefore, in this study, explain and evaluate the real subject of two approaches have been tried according to the interests, rights, education, interests and protect the interests of children, the ways to close the two approaches together will be offered.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.011
Threshold uncertainty score0.050

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0030.008
Scholarly communication0.0040.002
Open science0.0010.001
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0030.000

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.

Opus teacher head0.027
GPT teacher head0.335
Teacher spread0.308 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreOther

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".

Quick stats

Citations0
Published2016
Admission routes1
Has abstractyes

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