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Record W4389880580 · doi:10.1522/radm.no7.1667

dimensions de l'envie

2023· article· fr· W4389880580 on OpenAlexaffvenue
Mélanie Foucault, Emmanuel Habimana, Marcos Alencar Abaíde Balbinotti, Daniela Wiethaeuper

Bibliographic record

VenueAd machina l avenir de l humain au travail · 2023
Typearticle
Languagefr
FieldNeuroscience
TopicPsychology of Moral and Emotional Judgment
Canadian institutionsUniversité du Québec à Trois-Rivières
Fundersnot available
KeywordsHumanitiesPhilosophy

Abstract

fetched live from OpenAlex

L’être humain fait face au cours de sa vie à une multitude d’émotions, notamment la joie, la peine et la colère, qui sont ouvertement reconnues comme universelles, mais qu’en est-il de l’envie? Bien que l’envie soit présente dans toutes les cultures depuis le début de l’humanité, elle est stigmatisée, considérée comme moralement indésirable et souvent associée à des comportements socialement inacceptables. L'étude de l'envie en psychologie est encore un domaine relativement jeune avec peu d'études empiriques. Des instruments de mesure ont été construits afin de mesurer cette émotion; cependant, les auteurs ne s’entendent pas sur la structure complexe de l’envie. L’objectif de cet article est de parcourir les différentes conceptions de l’envie étayées dans la littérature et de proposer un cadre conceptuel pour d’éventuelles recherches sur le construit latent de l’envie, notamment en milieu de travail.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.005
Threshold uncertainty score0.013

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 studies0.0010.012
Scholarly communication0.0050.003
Open science0.0010.003
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0040.000

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 head0.067
GPT teacher head0.297
Teacher spread0.230 · 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
GenreOther

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
Published2023
Admission routes2
Has abstractyes

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