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Record W3198177228 · doi:10.1353/jeu.2021.0005

Le rire : formes et fonctions du comique dans la fiction africaine pour la jeunesse

2021· article· fr· W3198177228 on OpenAlexvenueno aff
Kodjo Attikpoé

Bibliographic record

VenueJeunesse Young People Texts Cultures · 2021
Typearticle
Languagefr
FieldArts and Humanities
TopicCaribbean and African Literature and Culture
Canadian institutionsnot available
Fundersnot available
KeywordsArtHumanities

Abstract

fetched live from OpenAlex

Cet article étudie les différentes manifestations du comique ainsi que leurs fonctions dans quatre œuvres fictionnelles pour la jeunesse en Afrique : l'album Tout Rond de Fatou Keïta et les romans Les confidences de Médor de Micheline Coulibaly, Pain sucré de Mary Lee Martin-Koné et Awa la petite marchande de Nafissatou Niang Diallo. Il part de l'idée que l'inscription du rire dans la littérature d'enfance et de jeunesse participe de sa dimension didactique, mais produit également une expérience esthétique. À travers l'analyse des rires moqueurs des personnages, il met particulièrement en évidence des conditions dans lesquelles la dérision apparaît légitime, inévitable, excluant l'Autre ou révélatrice de la profondeur du psychisme humain. Abstract: This article examines the different manifestations of the comic and their functions in four African fictional works of children's literature: the picture book Tout Rond by Fatou Keïta and the novels Les confidences de Médor by Micheline Coulibaly, Pain sucré by Mary Lee Martin-Koné, and Awa la petite marchande by Nafissatou Niang Diallo. It stems from the notion that laughter is inscribed into children's and young adult literature for didactic purposes, but that it also produces an aesthetic experience. By analyzing characters' mocking laughter, it highlights the conditions under which derision appears legitimate, inevitable, exclusionary, or revealing of the depths of the human psyche.

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)0.001
metaresearch head score (Gemma)0.002
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: Empirical
Teacher disagreement score0.013
Threshold uncertainty score0.025

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0080.014
Scholarly communication0.0050.003
Open science0.0000.002
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 head0.008
GPT teacher head0.222
Teacher spread0.214 · 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

Citations0
Published2021
Admission routes1
Has abstractyes

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