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Record W4407635329 · doi:10.5539/ach.v17n1p35

The Relationship between Shanxi Merchants and Spatial Structure in Yuncheng Ancient City, China

2025· article· en· W4407635329 on OpenAlexvenueno aff
Kaixin Xu

Bibliographic record

VenueAsian Culture and History · 2025
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicFinancial Crisis of the 21st Century
Canadian institutionsnot available
FundersUniversity of Tsukuba
KeywordsChinaAncient historyHistory of ChinaChinese cityArchaeologyGeographyEconomic geographyHistoryEconomySocioeconomicsSociologyEconomics

Abstract

fetched live from OpenAlex

Against the backdrop of growing international emphasis on the sustainable development of cultural heritage, case studies of historic cities offer valuable insights for the preservation and utilization of cities with diverse cultural and natural contexts. This study focuses on Yuncheng Ancient City in Shanxi Province, utilizing historical literature review and field investigation data to examine its spatial structure across different periods. The analysis includes an exploration of the city’s locational factors, changes in its buildings, roads, and their interrelationships before and after the emergence of the Shanxi merchants, as well as the underlying causes of these changes. The findings reveal that Yuncheng was constructed primarily for the administration of salt production, with its spatial structure evolving to support this purpose. Although government policies facilitated the entry of the Shanxi merchants into Yuncheng, their influence on the city’s development was minimal. Instead, the establishment of public facilities significantly enhanced the welfare of local residents. These findings clarified that in Yuncheng, the Shanxi merchants represented a temporary socio-economic phenomenon aligned with governmental policies, while the city itself was fundamentally shaped by government-led salt production and administration.

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)0.000
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.237
Threshold uncertainty score0.451

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.028
GPT teacher head0.224
Teacher spread0.196 · 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 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

Citations0
Published2025
Admission routes1
Has abstractyes

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