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Record W7075677346

The Dervishes of the North: Rumi, Whirling, and the Making of Sufism in Canada

2023· article· en· W7075677346 on OpenAlexfundaboutno aff

Bibliographic record

VenueTSpace · 2023
Typearticle
Languageen
FieldComputer Science
TopicGeochemistry and Geologic Mapping
Canadian institutionsnot available
FundersSocial Sciences and Humanities Research Council of CanadaQueen's UniversityFederation for the Humanities and Social Sciences
KeywordsSufismMysticismIslamMeditationPoetryNexus (standard)EthnographySpiritual practice
DOInot available

Abstract

fetched live from OpenAlex

The thirteenth-century Muslim mystic and poet Jalal al-Din Rumi (1207–1273) is a popular spiritual icon. His legacy is sustained within the mystical and religious practice of Sufism, particularly through renditions of his poetry, music, and the meditation practice of whirling. In Canada, practices associated with Rumi have become ubiquitous in public spaces, such as museums, art galleries, and theatre halls, just as they continue to inform sacred ritual among Sufi communities. The Dervishes of the North explores what practices associated with Rumi in public and private spaces tell us about Sufism and spirituality, including sacred, cultural, and artistic expressions in the Canadian context. Using Rumi and contemporary expressions of poetry and whirling associated with him, the book captures the lived reality of Sufism through an ethnographic study of communities in Toronto, Montreal, and Vancouver. Drawing from conversations with Sufi leaders, whirling dervishes, and poets, Merin Shobhana Xavier explores how Sufism is constructed in Canada, particularly at the nexus of Islamic mysticism, Muslim diaspora, spiritual commodity, popular culture, and universal spirituality. Inviting readers with an interest in religion and spirituality, The Dervishes of the North illuminates how non-European Christian traditions, like Islam and Sufism, have informed the religious and spiritual terrain of Canada.

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)0.000
metaresearch head score (Gemma)0.000
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 score0.503
Threshold uncertainty score0.837

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 science0.0010.000
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 head0.016
GPT teacher head0.235
Teacher spread0.219 · 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

Citations2
Published2023
Admission routes2
Has abstractyes

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