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Record W4410955843 · doi:10.7202/1117906ar

Pourquoi le monde biomédical s’ouvre-t-il à la spiritualité ? Résultats de l’étude SPIPRA

2024· article· fr· W4410955843 on OpenAlexaffabout
Nicolas Pujol, Frédérique Bonenfant, Claire Borrione, Etienne Rochat

Bibliographic record

VenueRELIER Revue interdisciplinaire d’études religieuses · 2024
Typearticle
Languagefr
FieldSocial Sciences
TopicReligion, Spirituality, and Psychology
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsHumanitiesArt

Abstract

fetched live from OpenAlex

Depuis une trentaine d’années, le monde biomédical est marqué par une production presque exponentielle d’articles scientifiques dont le mot clé est « spiritualité » ainsi que par l’émergence de nouvelles pratiques spirituelles. Cet article présente les résultats de la recherche SPIPRA qui vise à comprendre pourquoi et en vue de quoi s’est constitué ce nouveau champ de recherches et de pratiques portant sur la spiritualité dans le monde biomédical. Basée sur un travail d’enquête comparatif France–Québec–Suisse portant sur 9 pratiques spirituelles émergentes, cette étude a permis, à partir de 90 entretiens, de faire émerger 5 catégories conceptuelles pour rendre compte des différences et des similitudes entre ces pratiques : subjectivisation, médicalisation, psychologisation, intégration et théorisation. Un travail théorique a ensuite été réalisé à partir de ces catégories afin d’expliquer cet intérêt croissant pour la spiritualité dans le monde biomédical et de proposer une typologie de pratiques.

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)0.048
metaresearch head score (Gemma)0.119
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.048
Threshold uncertainty score0.251

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0480.119
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.006
Science and technology studies0.0050.006
Scholarly communication0.0070.005
Open science0.0010.006
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0130.002

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 head0.029
GPT teacher head0.357
Teacher spread0.327 · 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 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

Citations0
Published2024
Admission routes2
Has abstractyes

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