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Record W2092439036 · doi:10.5539/ass.v9n3p97

Interfaith Dialogue between Ethics and Necessity – A Study from the Qur’anic Guidelines

2013· article· en· W2092439036 on OpenAlexvenueno aff
Sohirin Mohammad Solihin, Layth Suud Jassem, Noor Mohammad Osmani, Eeman Mohammed Abbas, Mohd. Shah Jani

Bibliographic record

VenueAsian Social Science · 2013
Typearticle
Languageen
FieldSocial Sciences
TopicEducation and Islamic Studies
Canadian institutionsnot available
Fundersnot available
KeywordsEconomic JusticeInterfaith dialogueDiversity (politics)Religious diversityPromotion (chess)Common groundEnvironmental ethicsSociologyWork (physics)Social psychologyEpistemologyPublic relationsPolitical scienceLawIslamPsychologyTheologyPhilosophy

Abstract

fetched live from OpenAlex

Muslim theology admits on diversity of faiths followed by mankind. The existence of religious diversity is aimed at, among other things, seeking a common ground in disseminating goodness and eradicating evil practices in the community. The study attempts to reveal the guidelines on religious dialogue from the passages of the Qur’an. The Qur’an emphasizes on the importance of communication and dialogue especially with the People of the Book. The Prophetic tradition also indicates on presence of other religious adherents. They are expected to work together in promoting goodness and establishing justice on the basis of divine precepts. Moreover, it highlights the importance of dialogue with different religious groups, as well as the prospect to wipe off misunderstandings that can lead into communal tension and crisis. The study will also shed light on the obstacles faced by religious leaders in conducting the dialogue and to contributing to the promotion of peace and justice. The most important part is that it attempts to expose the ethical guidelines as stated in the Qur’an which could be adopted as principles of dialogue. It is not aimed at condemning other faiths; rather it is aimed at exposing awareness on the differences and similarities which, in the long run, can give chance to restoring misconceptions.

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)0.003
metaresearch head score (Gemma)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.367
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0050.003
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 head0.139
GPT teacher head0.432
Teacher spread0.293 · 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.

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

Citations1
Published2013
Admission routes1
Has abstractyes

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