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Record W4297996215 · doi:10.1080/01426397.2022.2121809

Ink wash virtualities in Qing landscape painting

2022· article· en· W4297996215 on OpenAlexafffund
Rob Shields, Ge Zheng

Bibliographic record

VenueLandscape Research · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicChinese history and philosophy
Canadian institutionsUniversity of Alberta
FundersCommonwealth Scholarship CommissionUniversity of Alberta
KeywordsRealmSublimePaintingLiminalityLandscape paintingArtRepresentation (politics)AestheticsMeaning (existential)Visual artsWildnessArt historyHistoryArchaeologyPhilosophyEpistemology

Abstract

fetched live from OpenAlex

This study considers virtuality in Qing ink wash landscape paintings via an album by Pan Gongshou (1741–94). We examine the painterly devices by which a liminal, ‘virtual,’ space is constructed as a ‘realm’ or world in which the viewer is synaesthetically absorbed into a landscape image. Landscape in this tradition is not a pure creation of the human gaze, nor a representation of material elements and topography. We examine the painterly devices through which a sublime loss of critical distance is linked to the represented elements to absorb the viewer into what Wang Guoweii (1877–1927) proposed as a ‘realm without self.’ Virtualities are intangible but real; they supplement material elements that are represented, changing their meaning and affect. These qualities are at the heart of a geometry of gazes and relations that compose the visual experience of a virtual landscape.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.009
Threshold uncertainty score0.018

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0030.005
Scholarly communication0.0020.002
Open science0.0000.001
Research integrity0.0000.000
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 head0.117
GPT teacher head0.399
Teacher spread0.282 · 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
Published2022
Admission routes2
Has abstractyes

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