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Record W2183701001 · doi:10.18192/analyses.v7i2.352

Les personnages <em>kawaii</em> et <em>moé</em>: figures ou figurines?

2012· article· fr· W2183701001 on OpenAlexaffvenue
Valérie Cools

Bibliographic record

VenueAnalyses Revue de littératures franco-canadiennes et québécoise · 2012
Typearticle
Languagefr
FieldSocial Sciences
TopicJapanese History and Culture
Canadian institutionsConcordia University
Fundersnot available
KeywordsHumanitiesArtPhilosophyArt history

Abstract

fetched live from OpenAlex

Cet article se propose d’explorer la question de l’envoûtement au sein de la culture des mangas et des dessins animés japonais contemporains. L’auteur s’interroge sur la possibilité de l’envoûtement à l’intérieur d’une culture de masse et commence par aborder la question du point de vue des jeux de regards avant d’examiner deux courants spécifiques de la culture otaku : le kawaii et le moé. Ayant constaté les facteurs qui s’opposent à l’envoûtement, tels que la nature collective de ces courants et le détachement qui semble les accompagner, l’auteure suggère alors que la figure envoûtante se situe justement dans sa propre impossibilité, dans la quête perpétuelle qui l’entoure.AbstractThis article aims to explore the question of bewitchment within contemporary manga and anime culture. The author questions the possibility of bewitchment within a mass culture, and starts off by tackling the question from the perspective of gaze exchanges, before examining two specific currents within otaku culture: kawaii and moe. After noting those factors which oppose bewitchment, such as the collective nature of these currents and the detachment which appears to go hand in hand with them, the author then suggests that the bewitching figure lies precisely in its own impossibility, in the perpetual quest which surrounds it.

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)0.001
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 score0.013
Threshold uncertainty score0.044

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0050.008
Scholarly communication0.0030.005
Open science0.0000.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0130.001

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 head0.033
GPT teacher head0.293
Teacher spread0.260 · 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
Published2012
Admission routes2
Has abstractyes

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