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Record W2900813066 · doi:10.1515/css-2018-0026

Semiosphere and Solitary World

2018· article· en· W2900813066 on OpenAlexaff
Lian Duan

Bibliographic record

VenueChinese Semiotic Studies · 2018
Typearticle
Languageen
FieldSocial Sciences
TopicChinese history and philosophy
Canadian institutionsConcordia University
Fundersnot available
KeywordsPaintingInterpretation (philosophy)BlueprintStyle (visual arts)MainstreamPeriod (music)LiteratureLandscape paintingArtAestheticsPhilosophyArt historyVisual artsLinguisticsTheology

Abstract

fetched live from OpenAlex

Abstract Literati landscape painting was the mainstream of Chinese art in the Yuan dynasty; its keynote is the idea of yi , literally, escaping for freedom, which is represented by the notion of reclusiveness at the conceptual level and the notion of spontaneity at the formal level. Based on an analytical interpretation of the development of Yuan literati landscape painting at the two levels, this essay intends to make a point that, under the Mongol rule, reclusiveness and spontaneity became the artistic pursuit of Chinese artists in the period from late 13th to late 14th century. Employing Yuri Lotman’s theory of “semiosphere” in this study, I argue that the blueprint for the solitary world is designed by the early Yuan literati artist Zhao Mengfu, and this world is constructed by the later Yuan literati artists Huang Gongwang and Ni Zan, among others. I further describe the structure of this world as having two levels and three concentric circles, with reclusiveness as the signified central idea and spontaneous brushwork as its signifier. I then conclude that the interaction of the reclusive idea and spontaneous style semioticizes the structure, and completes the construction of the unique artistic world of Yuan literati landscape painting.

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: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.005
Threshold uncertainty score0.019

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0040.024
Scholarly communication0.0040.003
Open science0.0000.004
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.000

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 head0.045
GPT teacher head0.364
Teacher spread0.319 · 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 designTheoretical or conceptual
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

Citations1
Published2018
Admission routes1
Has abstractyes

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