MétaCan
Menu
Back to cohort
Record W2085683125 · doi:10.1163/22105956-12341262

From Sufism to Universal Vision: Murat Yagan and the Teaching of Kebzeh

2014· article· en· W2085683125 on OpenAlexaboutno aff
Chen Bram, Meir Hatina

Bibliographic record

VenueJournal of Sufi Studies · 2014
Typearticle
Languageen
FieldSocial Sciences
TopicJewish and Middle Eastern Studies
Canadian institutionsnot available
Fundersnot available
KeywordsEthosCompassionSufismChristianityMulticulturalismEthnic groupContext (archaeology)IdeologySpiritualitySociologyAnthropologyIslamReligious studiesEnvironmental ethicsAestheticsHistoryPolitical scienceArchaeologyPhilosophyPoliticsTheologyLawPedagogy

Abstract

fetched live from OpenAlex

This article examines aspects of cultural exchange between the Middle East and the West in which Sufism, Christianity, the traditions of the Circassians and New Age concepts played a central role. It focuses on the teaching of Murat Yagan, of Abkhaz-Circassian origin who grew up in Turkey and immigrated to Canada in the 1960s, where he developed his philosophy, Ahmsta Kebzeh (“the knowledge of the art of living”). The Kebzeh way of life emphasizes modesty, mutual responsibility and compassion. Yagan linked these values to the ancient ethos of the Caucasus Mountains which he sought to revive as the basis of a universal vision. The nature of Kebzeh was influenced by the cosmopolitan environment in which Yagan was educated in Turkey; by his enrollment with Sufi circles in North America; and by the multicultural Canadian atmosphere. These diverse influences enabled him to devise an ecumenical model of dialogue between cultures. The article provides a first-time survey and analysis of Kebzeh ideological and communal features. It sheds new light on the role of ethnicity and cultural heritage in immigrant societies in the context of the evolution of spirituality in Canada, a relatively unexplored milieu in comparison to the United States and Europe.

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)0.002
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: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.219
Threshold uncertainty score0.371

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
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 head0.026
GPT teacher head0.330
Teacher spread0.304 · 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 designQualitative
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

Citations3
Published2014
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Sufi StudiesSame topicJewish and Middle Eastern StudiesFrench-language works237,207