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Record W1993743128 · doi:10.3138/07l4-2754-514j-7r38

Art as Maps: Influence of Cartography on Two Chinese Landscape Paintings of the Song Dynasty (960-1279 CE)

2000· article· en· W1993743128 on OpenAlexvenueno aff
Bangbo Hu

Bibliographic record

VenueCartographica The International Journal for Geographic Information and Geovisualization · 2000
Typearticle
Languageen
FieldSocial Sciences
TopicGlobal Maritime and Colonial Histories
Canadian institutionsnot available
FundersSmithsonian Institution
KeywordsPaintingStyle (visual arts)ToponymyTheme (computing)Inscribed figureLandscape paintingGeographyChinaArtCartographyChinese artArchaeologyHistoryVisual arts

Abstract

fetched live from OpenAlex

In this article I examine the influence of cartography on two Chinese Song dynasty (960-1279 CE) landscape paintings: the Changjiang wan li tu (panoramic view of the Changjiang) and the Shu chuan shenggai (beautiful scenery along the Changjiang in Sichuan). Western readers may be more familiar with the Changjiang as the Yangtze River. In addition to discussion of their artists, dates, and nature, the cartographic elements depicted in these two paintings have also been examined in detail. Although there are still some uncertainties about the artists and dates of the two paintings, the evidence provided by the place names inscribed on these two scrolls indicates that the Changjiang wan li tu could not have been created before 1196 and that the Shu chuan shenggai could not have been painted earlier than 1208. The theme, content, and artistic style of these two Chinese landscape paintings and the history of the collections in which they were treasured through the centuries suggest that they would be more appropriately regarded as artistic masterpieces than as maps. However, both paintings include significant cartographic elements, reflecting the influence of traditional Chinese cartography. That influence is evident in the inscription of place names according to their relative locations, the use of geographical texts as sources, the indication of distance between the sites, and the identification of the locations and changes of historical place names.

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)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.775
Threshold uncertainty score0.658

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0000.001
Open science0.0010.000
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 head0.004
GPT teacher head0.274
Teacher spread0.270 · 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
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

Citations2
Published2000
Admission routes1
Has abstractyes

Explore more

Same venueCartographica The International Journal for Geographic Information and GeovisualizationSame topicGlobal Maritime and Colonial HistoriesFrench-language works237,207