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Être musulmane et sujet éthique et spirituel : Vivre-ensemble et autres concepts expérientiels mobilisés par des soufies montréalaises

2023· article· fr· W4387122632 on OpenAlexaffvenueabout
Abdelwahed Mekki‐Berrada, Cécile Rousseau, Karim Ben Driss

Bibliographic record

VenueAnthropologica · 2023
Typearticle
Languagefr
FieldSocial Sciences
TopicMulticulturalism, Politics, Migration, Gender
Canadian institutionsMcGill UniversityUniversité Laval
Fundersnot available
KeywordsHumanitiesPhilosophyEthnologySociology

Abstract

fetched live from OpenAlex

Nous visons, par ce texte, une meilleure compréhension de la mise en mots des expériences subjectives, éthiques et esthétiques de femmes soufies installées à Montréal, tout en identifiant les interactions dynamiques entre des concepts clés qu’elles mettent de l’avant. Ces concepts semblent former une constellation conceptuelle qui constitue pour ces femmes une grille d’interprétation du monde et un guide d’action dans et sur ce monde. Une telle herméneutique-action, qui fusionne conceptualisation et expérientiel dans la quotidienneté, participerait-elle à la fois à la construction de soi et d’un vivre- ensemble où la différence et l’altérité relèveraient de la théophanie et de la sacralité ? Telle est la question centrale que nous posons ici. Nous nous basons essentiellement sur des données qualitatives. L’analyse de ces données laissent entrevoir que les impardonnables atrocités, perpétrées dans le monde au nom de l’islam par une petite minorité radicale violente, organisée en milices assassines et rétives à toute forme d’altérité, ne devraient pas occulter l’existence d’un islam du vivre-ensemble où l’Autre serait sujet d’ennoblissement.

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: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.662
Threshold uncertainty score0.681

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0090.021
Scholarly communication0.0050.004
Open science0.0010.003
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0090.000

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 head0.144
GPT teacher head0.457
Teacher spread0.313 · 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 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

Citations0
Published2023
Admission routes3
Has abstractyes

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