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Record W4380482003 · doi:10.6000/1929-4409.2020.09.258

The Confessional Differences in Perception of the Factors Insulting the Religious Feelings

2022· article· en· W4380482003 on OpenAlexvenueno aff
Svetlana Pavlovna Politova, Zoya V. Silaeva

Bibliographic record

VenueInternational Journal of Criminology and Sociology · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicCultural, Linguistic, Economic Studies
Canadian institutionsnot available
FundersKazan Federal University
KeywordsConfessionalFeelingInsultNoveltyPsychologySocial psychologyDress codePerceptionConfession (law)IslamJurisprudenceLawCriminologySociologyPolitical scienceHistory

Abstract

fetched live from OpenAlex

The current study is concerned with the actual for modern Russia problem of law enforcement practice under Article 148 of the Criminal Code, which provides for liability for actions committed with the purpose of offending religious feelings. At the same time, until now, there is no uniform understanding of what the religious sentiments of believers are and what are the actions that can insult them. The article describes the results from the survey organized to study confessional differences in the perception of factors of offending the feelings of the believers. The study involved 220 representatives of the main confessions of Russia: Christianity, Islam, Judaism and Buddhism. The respondents were asked to choose those actions from the proposed list that could wound their religious feelings or to suggest their own variant (all questions were composed with reference to doctrinal characteristics of confessions, but were of similar nature). The results obtained indicate that insult to the feelings of believers is subjective and has confessional characteristics determined by the content of the religious teachings. The results of the study are of unconditional novelty and significance in view of great social demand and lack of similar studies.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.186
Threshold uncertainty score0.666

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.002
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.088
GPT teacher head0.346
Teacher spread0.258 · 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 teacher head, 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
Published2022
Admission routes1
Has abstractyes

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