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Study on Religious Education in the United States and Its Inspiration

2011· article· en· W1740816425 on OpenAlexvenueno aff
Xianxia Meng

Bibliographic record

VenueCross-cultural communication · 2011
Typearticle
Languageen
FieldSocial Sciences
TopicReligious Education and Schools
Canadian institutionsnot available
Fundersnot available
KeywordsIdeologyHumanitiesEthnologyReligious educationSociologyPoliticsChinaPolitical scienceArtLawPedagogy

Abstract

fetched live from OpenAlex

The United States is one of the nations with most fantastic religious background, and in reality religion and religious education permeates all aspects of American life. Religion lies in American family education, school education, political activities and social life, playing a role that can not be ignored. An important inspiration can be drawn from the study of religious education of the United States to the ideological education in China. Key words : Religion; Religious Education; The United States; Inspiration Resume: Les Etats-Unis est l'une des nations qui ont des fonds religieux les plus fantastique, et en realite, la religion et l'enseignement religieux impregnent dans tous les aspects de la vie americaine. La religion reside dans l'education familale americaine, l'enseignement scolaire, les activites politiques et la vie sociale, en jouant un role qui ne peut pas etre ignore. Une source d'inspiration importante peut etre tiree de l'etude sur l'education religieuse des Etats-Unis a l'education ideologique en Chine. Mots-cles: Religion; EDucation Religieuse; Etats-Unis; Inspiration

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)0.001
metaresearch head score (Gemma)0.003
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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.015
Threshold uncertainty score0.030

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0040.002
Scholarly communication0.0020.001
Open science0.0000.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.000

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 head0.085
GPT teacher head0.418
Teacher spread0.334 · 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
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
Published2011
Admission routes1
Has abstractyes

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