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Japan

2021· book-chapter· en· W3207071683 on OpenAlexaff
Stefano Evangelista

Bibliographic record

VenueOxford University Press eBooks · 2021
Typebook-chapter
Languageen
FieldSocial Sciences
TopicJapanese History and Culture
Canadian institutionsTrinity College
Fundersnot available
KeywordsDecadenceAmbivalenceTasteArtOrientalismLiteratureJapanese cultureWestern literatureHistoryArt historyPsychologyPsychoanalysisJapanese studies

Abstract

fetched live from OpenAlex

Abstract In the second half of the nineteenth century, literary decadence developed in parallel with japonisme, the taste for Japanese art and culture that seized Western countries following Japan’s opening to foreign trade. This article starts with an analysis of how the intertwining of japonisme and art for art’s sake pioneered by visual artists influenced writers associated with decadence, such as Walter Pater, Arthur Symons, and Oscar Wilde. The evolving relationship between decadence and japonisme assumed a distinctive character in the work of Lafcadio Hearn, who lived in Japan all through the 1890s and wrote a series of influential books about the country. The article closes with an account of how ideas of decadence traveled back to Japan. Yōshū Chikanobu’s color prints reverse the orientalist gaze of Western artists by documenting a Japanese fascination with European culture that traditionalists viewed as a symptom of decadence. As Japanese literature opened itself to cosmopolitan influences, key writers such as Natsume Sōseki, Tanizaki Junichirō, and Mishima Yukio borrowed from Western literatures to provide ambivalent depictions of Japan’s social and cultural changes.

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)0.000
metaresearch head score (Gemma)0.000
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: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.232
Threshold uncertainty score0.000

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.000
Scholarly communication0.0030.002
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.2320.107

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 head0.029
GPT teacher head0.220
Teacher spread0.191 · 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
Published2021
Admission routes1
Has abstractyes

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