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Record W2350612395

Urban Integraion Model in Ethnic Autonomous Regions: A case of Yanji Longjing Tumen Area

2013· article· en· W2350612395 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueShijie dili yanjiu · 2013
Typearticle
Languageen
FieldEnvironmental Science
TopicEvaluation Methods in Various Fields
Canadian institutionsScience North
Fundersnot available
KeywordsEthnic groupEconomic geographyChinaUrbanizationPaceGeographyMode (computer interface)NationalityRegional sciencePolitical scienceComputer scienceEconomic growthGeodesyImmigration
DOInot available

Abstract

fetched live from OpenAlex

The rapid development of urbanization promote the pace of development of all levels of regional in China, and emerge the Phenomenon of urban integration in ethnic autonomous regions. Compared to the general and developed areas,there are several distinctive characteristics of the nationality, the ethnic autonomous and immaturity in ethnic autonomous regions.The paper discuss the specificity of autonomous regions, at the same time elaborated the China's ethnic autonomous regional urban and its particularity in detail. And select the YanLongTu which have the typical characteristics as a case region. In quantitative research, by using AHP method measure the integrating force of the YanLongTu region, and divided the integraing space in three levels by field intensity model. It can be obtained the conclution that YanLongTu integration area is at low level and there is a low field strength between Yanji and Tumen through quantitative analysis. In conclution,the paper proposed three types of control measures about space integrated model, administrative division adjustment mode and regional development mode to promote the development of urban interation in YanLongTu area.

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.

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.653
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
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)0.0020.000

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 head0.076
GPT teacher head0.341
Teacher spread0.265 · 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