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Record W2308990339 · doi:10.5539/ass.v12n4p1

A Study on the Interaction of Religious Literature for Children and Adolescents with Illustration in Iran

2016· article· en· W2308990339 on OpenAlexvenueno aff
Adeleh Rafaee, Parisa Shad Qazvini

Bibliographic record

VenueAsian Social Science · 2016
Typearticle
Languageen
FieldSocial Sciences
TopicEducation and Islamic Studies
Canadian institutionsnot available
Fundersnot available
KeywordsIslamPersianPoliticsSociologySocial scienceReligious valuesPsychologyHistoryPolitical scienceLawPhilosophyLinguistics

Abstract

fetched live from OpenAlex

The formation of the Islamic Revolution in the early sixties and its rise in the fifties has caused major changes and developments in the cultural structures of Iran. These changes emerged in the political - economic and social – cultural areas in the framework of Islamic- revolutionary utopian ideas. In the Pahlavi era, religious literature for children was less considered due to the low attention of the governing regime. Although the forties is considered as the decade of children’s book illustrations but the religious literature for children and its illustration were less considered. With the beginning of the revolutionary activities, some Persian writers decided to make children familiar with spiritual and religious atmospheres by creating works with a focus on Islam. The prevailing hypothesis of this paper is that an interaction was established between religious literature for children and children’s book illustration after the emergence of religious thoughts in children’s stories. Here, the claim is proved that the social needs and the interaction of religious literature with children’s book illustrations led to the emergence of a branch called religious illustration. The methodology of this study is descriptive-analytical. Data collection method is collecting documents and library resources.

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)0.002
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.017
Threshold uncertainty score0.033

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.006
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0050.003
Scholarly communication0.0040.002
Open science0.0010.002
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0040.000

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 head0.023
GPT teacher head0.335
Teacher spread0.312 · 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 designObservational
Domainnot available
GenreEmpirical

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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