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Record W1980834309 · doi:10.1191/0309132506ph611oa

Research on Chinese urban form: retrospect and prospect

2006· article· en· W1980834309 on OpenAlexaff
Jeremy Whitehand, Kai Gu

Bibliographic record

VenueProgress in Human Geography · 2006
Typearticle
Languageen
FieldEngineering
TopicUrban Design and Spatial Analysis
Canadian institutionsUniversity of Waterloo
FundersUniversity of Pennsylvania
KeywordsChinaGeographyUrban planningEconomic geographyEnvironmental planningRegional scienceHistoryArchaeologyCivil engineeringEngineering

Abstract

fetched live from OpenAlex

In the last 10 years, research on Chinese urban form has grown rapidly both in China itself and in other parts of the world. At the same time Chinese cities have undergone unprecedented growth and transformation, presenting great challenges for the comprehension and management of urban landscape change. In planning future urban morphological research during this period of exceptional flux, an important first step is to take stock of past research, especially that of the recent past. Hitherto research on Chinese urban form across a range of disciplines, including architectural history, urban planning, archaeology and urban geography, has tended to be descriptive and has contained scant comparison, either of findings or methods, with that on towns and cities in other parts of the world. Future research on Chinese urban form can benefit from exploring the efficacy of urban morphological concepts and methods that have been developed and applied elsewhere in the world, especially Europe.

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)0.003
metaresearch head score (Gemma)0.003
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: Review · Consensus signal: none
Teacher disagreement score0.075
Threshold uncertainty score0.150

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0060.017
Science and technology studies0.0030.005
Scholarly communication0.0020.004
Open science0.0010.002
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.013
GPT teacher head0.279
Teacher spread0.266 · 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
GenreReview

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

Citations73
Published2006
Admission routes1
Has abstractyes

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