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Record W2017936643 · doi:10.3917/enf.574.0363

Empathie, contagion émotionnelle et coupure par rapport aux émotions

2005· article· fr· W2017936643 on OpenAlexaff
Daniel Favre, Jacques Joly, Christian Reynaud, Luc Laurent Salvador

Bibliographic record

VenueEnfance · 2005
Typearticle
Languagefr
FieldSocial Sciences
TopicPsychology of Social Influence
Canadian institutionsUniversité de Sherbrooke
Fundersnot available
KeywordsPhilosophyHumanities

Abstract

fetched live from OpenAlex

RÉSUMÉ L’absence de consensus autour d’une définition de l’empathie, sa confusion avec les phénomènes de sympathie ou de compassion n’ont pas manqué de se répercuter sur les recherches entreprises pour étudier et, en particulier, mesurer, ce phénomène. Il en a résulté une confusion qu’il convient de réduire autant que possible. L’objectif de cet article consiste à proposer : 1 / un historique théorique et critique visant à assigner une place plus précise à l’empathie au sein du vaste champ conceptuel qui est le sien, et 2 / une nouvelle échelle de mesure (CEC) valide de l’empathie qui permette d’appréhender celle-ci de manière plus fine, en la distinguant clairement des phénomènes connexes que sont la contagion émotionnelle et de ce que nous appellerons la coupure par rapport aux émotions. La seconde partie de cette étude, qui sera publiée en 2006, fera état de la validation du test CEC et du fait que, grâce à ce dernier et à sa conceptualisation sous-jacente, l’empathie apparaît comme une compétence émotionnelle, cognitive et sociale susceptible de constituer un objectif éducatif pour les enseignants concernés par la régulation des comportements en classe.

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)0.004
metaresearch head score (Gemma)0.008
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.019
Threshold uncertainty score0.064

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.008
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0030.012
Scholarly communication0.0090.007
Open science0.0010.005
Research integrity0.0030.005
Insufficient payload (model declined to judge)0.0190.003

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 head0.055
GPT teacher head0.408
Teacher spread0.353 · 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 designNot applicable
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

Citations40
Published2005
Admission routes1
Has abstractyes

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