MétaCan
Menu
Back to cohort
Record W4413966557 · doi:10.4000/14l9j

Courir pieds nus pour se reconnecter sensoriellement à la nature ? Autoethnographie collective d’une transition minimaliste

2025· article· fr· W4413966557 on OpenAlexaff
Brice Favier-Ambrosini, Yannick Linossier, Matthieu Quidu

Bibliographic record

VenueÉduquer · 2025
Typearticle
Languagefr
FieldSocial Sciences
TopicFrench Urban and Social Studies
Canadian institutionsUniversité du Québec à Chicoutimi
Fundersnot available
KeywordsHumanitiesArt

Abstract

fetched live from OpenAlex

Cet article analyse, par une auto-ethnographie collectivement cadrée, une transition vers la course à pied minimaliste (pratiquée pieds nus, en sandales ou en chaussures minimalistes) du premier auteur, afin d’interroger son potentiel de (re)connexion avec la nature. Inscrite dans une socio-phénoménologie, l’étude documente six mois de pratique (48 séances) grâce à des récits d’auto-explicitation, deux échelles numériques et divers entretiens : entretien de mise en parenthèse, entretien de cours de vie relatif à une pratique et entretiens d’explicitation. Trois phases sont dégagées : la découverte sensorielle, où l’exploration tactile s’accompagne d’une focalisation attentionnelle visuelle limitant le déploiement des autres sens ; l’incorporation progressive de la modalité minimaliste, favorisant une intensification du sentiment de connexion à la nature et parfois une expérience de « cosmose »; et enfin, la quête de performance, qui restreint la dimension contemplative tout en ouvrant à une immersion spécifique par la vitesse. L’étude montre ainsi que la réduction des médiations matérielles ne produit pas mécaniquement la connexion à la nature souvent annoncée par les promoteurs de la course minimaliste, mais révèle des dynamiques ambivalentes et non linéaires.

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 score0.011
Threshold uncertainty score0.021

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0070.010
Scholarly communication0.0040.004
Open science0.0010.004
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0050.000

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 head0.297
Teacher spread0.271 · 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

Citations3
Published2025
Admission routes1
Has abstractyes

Explore more

Same venueÉduquerSame topicFrench Urban and Social StudiesFrench-language works237,207