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Co-construire un accompagnement somato-réflexif dans la traversée COVID avec des pairs formateurs en enseignement supérieur

2022· article· fr· W4313391008 on OpenAlexaff
Geneviève Emond, Sabine Oppliger, Fabienne Venant, Cécile Nicolas

Bibliographic record

VenueÉduquer · 2022
Typearticle
Languagefr
FieldPsychology
TopicSocial Representations and Identity
Canadian institutionsUniversité du Québec à Montréal
Fundersnot available
KeywordsHumanitiesPolitical sciencePhilosophyArt

Abstract

fetched live from OpenAlex

La COVID-19 et l’enseignement à distance a précipité la plupart des formateurs de l’enseignement supérieur dans une période d’insécurité. L’importance de la présence du corps dans leur métier apparait alors plus évidente que jamais. Dans cette traversée, avec un groupe de pairs formateurs ( = 8) désireux de vivre un accompagnement somato-réflexif (Emond et Rondeau, 2019), nous avons étudié la conscience de la corporéité, relation que nous entretenons avec nos propres corps, les corps d’autres personnes autour de nous et notre environnement (Johnson, 2007) alors que nous tentons de retrouver notre pouvoir d’agir de formateurs. Des ateliers somatiques de groupe, accompagnés de la rédaction d’un journal expérientiel, ont mené à une analyse de données phénoménologiques (van Manen, 2014). Les résultats préliminaires montrent différents chemins de régulation empruntés pour maintenir bien-être et santé dans cette période chahutée. Plusieurs des moyens utilisés passent par une réappropriation de l’espace occupé par les corps, tant individuellement que collectivement, afin de se sentir encore vivant dans son métier.

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)0.006
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 score0.033
Threshold uncertainty score0.067

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0030.004
Scholarly communication0.0040.003
Open science0.0010.003
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0090.001

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 head0.024
GPT teacher head0.328
Teacher spread0.305 · 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".

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Citations1
Published2022
Admission routes1
Has abstractyes

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