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»I Spy with my Little Eye«: GIS and Archaeological Perspectives on Eleventh Century Song Envoy Routes in the Liao Empire (Kitan-Liao Archaeological Survey and History KLASH)

2015· article· en· W2270665758 on OpenAlexafffund
Gwen Bennet

Bibliographic record

VenueMedieval Worlds · 2015
Typearticle
Languageen
FieldSocial Sciences
TopicChinese history and philosophy
Canadian institutionsMcGill University
FundersArts and Humanities Research CouncilMcGill University
KeywordsViewshed analysisEleventhArchaeologyChinaGeographyAncient historyPopulationEmpirePeriod (music)ExcavationHistoryInner mongoliaCartographyDemographyArt

Abstract

fetched live from OpenAlex

Archaeological data, combined with GIS analysis has given us new perspectives on eleventh century medieval period envoy missions from the Song Dynasty (960-1279 CE) to the Liao Empire (907-1125 CE). Lu Zhen and Wang Zhen were Song envoys sent in 1008 and 1012 by the Song to the Liao’s Middle Capital or Zhongjing, in present day Chifeng Inner Mongolia, the Peoples Republic of China (PRC). Lu Zhen recorded information about the route he traveled that allows us to locate it on administrative maps of the Song-Liao period and present day maps of the PRC. Viewshed analysis of the route combined with information Wang Zhen recorded about it lets us calculate population densities for an area that he passed through that can be used to extrapolate population density estimates from archaeological data for other areas in Chifeng. Viewshed analysis provides insights about the areal extent of the landscape and what man-made structures the envoys might have been able to see along the route during their travels. Combined, these analyses give us better insights into some of the concerns that the Liao had about these foreign missions crossing their territory and the steps they took to address them.

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)0.003
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.474
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.003
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.058
GPT teacher head0.301
Teacher spread0.243 · 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.

Study designObservational
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
Published2015
Admission routes2
Has abstractyes

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