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Record W2192017657 · doi:10.1051/shsconf/20152101003

Apprendre, un moment de vie ? Savoir, expérience et rapport au vivant

2015· article· fr· W2192017657 on OpenAlexaff
Julie Noack

Bibliographic record

VenueSHS Web of Conferences · 2015
Typearticle
Languagefr
FieldHealth Professions
TopicHealth, Medicine and Society
Canadian institutionsUniversité de Montréal
Fundersnot available
KeywordsHumanitiesPhilosophy

Abstract

fetched live from OpenAlex

L’objectif de cette communication est de comparer sur le plan pédagogique deux conceptions du rapport entre science et vivant, diamétralement opposées sur le plan épistémologique. En se basant sur un livre [1], une conférence [2] et un entretien [3], on analysera l’expérience de pensée par laquelle le biologiste et épistémologue Jean-Jacques Kupiec fait se sentir vivants les apprenants afin de mieux les conscientiser aux réquisits de la démarche scientifique. On comparera ensuite les motivations de Kupiec avec les idées pédagogiques du philosophe-médecin Georges Canguilhem (1904–1995) afin d’essayer de comprendre pourquoi l’un et l’autre jugent pertinent de faire remarquer à l’apprenant qu’il est actuellement en vie. Car, malgré des conceptions du vivant diamétralement opposées, Canguilhem et Kupiec se rejoignent sur l’idée que l’expérience vitale joue un rôle crucial – que ce soit en positif ou en négatif, comme un obstacle épistémologique ou comme un levier heuristique – dans l’apprentissage et la pratique de la biologie ou de la médecine. Prendre en charge cette expérience constitue peut-être une ressource face au double défi (scientifique et éthico-politique) qui échoit à l’éducation aux sciences du vivant.

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)0.003
metaresearch head score (Gemma)0.005
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.011
Threshold uncertainty score0.026

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0080.026
Scholarly communication0.0110.013
Open science0.0010.007
Research integrity0.0040.006
Insufficient payload (model declined to judge)0.0080.001

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 head0.139
GPT teacher head0.401
Teacher spread0.263 · 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

Citations1
Published2015
Admission routes1
Has abstractyes

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