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Record W4298138666 · doi:10.5539/res.v14n4p1

Knowledge as Play: Comics by Japanese Modern Literature

2022· article· en· W4298138666 on OpenAlexvenueno aff
Rodica Frenţiu, Florina Ilis

Bibliographic record

VenueReview of European Studies · 2022
Typearticle
Languageen
FieldArts and Humanities
TopicComics and Graphic Narratives
Canadian institutionsnot available
Fundersnot available
KeywordsComicsPhenomenonPostmodernismContext (archaeology)Cultural phenomenonPoeticsReading (process)PublishingSociologyLiteratureArtAestheticsHistoryPoetrySocial sciencePhilosophyEpistemologyLinguisticsArchaeology

Abstract

fetched live from OpenAlex

In the context of Japanese cultural postmodernism, the phenomenon of resuming literary masterpieces in comic book form appears as a juxtaposition with a specific purpose, resulting in a hybrid form which we would regard as komiXLit. As part of a specific way of knowledge, we interpret komiXLit as an alternative model whose characteristic is that of the combination of two apparently contradicting terms: the “high” literature and the manga pop culture publication, a cultural move placed by the Japanese publishing houses under the credo “understanding literature through manga”. Using the illustrative example provided by the masterpiece authored by Yasunari Kawabata Snow Country (1935-1937/ 1948) and its manga version (2010), with drawings by Sakuko Utsugi, the present endeavour proposes a reading in which the komiXLit version is interpreted as an architectonic structure inspired by the former, in an attempt to identify the dominants of the textual poetics. We propose that the term komiXLit designate the cultural and social phenomenon of resuming the masterpieces of the Japanese literature in manga (comics) versions, as a self-sustainable category within the genre, meant to complete the already existing ones: story manga‚ dramatic pictures, graphic novels, boys’comics, girls’comics, men’s comics, ladies’ comics.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.258
Threshold uncertainty score0.464

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.047
GPT teacher head0.295
Teacher spread0.248 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreReview

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
Published2022
Admission routes1
Has abstractyes

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