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Record W2544502234 · doi:10.5539/ies.v9n11p13

The Effect of Religion on Ethnic Tolerance in Malaysia: The Application of Rational Choice Theory (RCT) and the Theory of Planned Behaviour (TPB)

2016· article· en· W2544502234 on OpenAlexvenueno aff
Fazilah Idris, Mohd Richard Neles Abdullah, Abdul Razak Ahmad, Ahmad Zamri Mansor

Bibliographic record

VenueInternational Education Studies · 2016
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicIslamic Finance and Banking Studies
Canadian institutionsnot available
Fundersnot available
KeywordsEthnic groupSocial psychologyRational choice theory (criminology)Perspective (graphical)Theory of planned behaviorPsychologyPerceptionSociological theorySociologySocial scienceCriminologyControl (management)

Abstract

fetched live from OpenAlex

<p class="apa">There has been little research done on explaining the ethnic tolerance behavior from the perspective of sociological theories. The authors chose rational choice theory and the theory of planned behavior as they are widely used in explaining the human social behaviour. In this article, the theories are used to explain the effects of religion on ethnic tolerance in Malaysia. The authors also reviewed a number of literatures to study how religion is associated with ethnic tolerance. From the rational choice theory perspective, it was found that ethnic tolerance can be influenced by one’s religious belief if those who practice it are reciprocated with the promise of retributions from God. The theory of planned behavior on the other hand suggests that religion can affect behavior, subjective norms and perception on how one deal with ethnic tolerance. It is recommended that the theories are used by future studies in order to further expand knowledge base on the subject of ethnic tolerance. This study provides ways and means to inculcate ethnic integration in Malaysia and helps to diffuse religious and ethnic prejudices.</p>

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.711
Threshold uncertainty score0.183

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.013
GPT teacher head0.298
Teacher spread0.286 · 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 designTheoretical or conceptual
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

Citations11
Published2016
Admission routes1
Has abstractyes

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