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Record W1499787641 · doi:10.5539/ass.v11n16p1

The Self of Sundanese Ethnic: Interdependent Construal and Religious Self

2015· article· en· W1499787641 on OpenAlexvenueno aff
Retno Hanggarani Ninin

Bibliographic record

VenueAsian Social Science · 2015
Typearticle
Languageen
FieldSocial Sciences
TopicReligion, Spirituality, and Psychology
Canadian institutionsnot available
Fundersnot available
KeywordsEthnic groupInterdependenceSocial psychologySociologyContext (archaeology)IndonesianSelf construalRelation (database)Religious identityEmpirical researchPsychologyGender studiesSocial scienceEpistemologyReligiosityAnthropologyGeographyComputer science

Abstract

fetched live from OpenAlex

This paper aims to introduce the religious self-viewed from the Indonesian context. Indonesia is a large country with diverse ethnic groups and the study seeks to investigate the self in relation to ethnicity. Specifically, the study examines the Sundanese ethnic group that has relatively few sub-groups compared with others found on the archipelago. The study undertakes a conceptual analysis to illustrate the religious self. In this regard, the social and cultural factors are examined to enable a proper account of the religious self, particularly in Indonesia. Relevant empirical evidence is presented to support and explain the religious self-concept. The study further presents a comparative analysis with previous self-concept studies. Finally, the paper concludes with a discussion on the direction of future research on the religious self.

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)0.003
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 score0.003
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.004
Scholarly communication0.0030.001
Open science0.0000.002
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.040
GPT teacher head0.383
Teacher spread0.343 · 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

Citations10
Published2015
Admission routes1
Has abstractyes

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