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Record W4281398131 · doi:10.21203/rs.3.rs-1675764/v1

Research on the driving effect of Eco-economic Zones on urban coordinated development and its effect mechanism

2022· preprint· en· W4281398131 on OpenAlexaff
Jiaqi Liu, Bibang Gong, Zongyi Hu, Jianjun Li

Bibliographic record

VenueResearch Square · 2022
Typepreprint
Languageen
FieldEconomics, Econometrics and Finance
TopicEconomic Zones and Regional Development
Canadian institutionsUniversity of Alberta
FundersNatural Science Foundation of Hunan ProvinceNational Natural Science Foundation of China
KeywordsLivelihoodStructural basinDevelopment planMechanism (biology)Plan (archaeology)Driving factorsEnvironmental planningGeographyEnvironmental resource managementAgricultureEnvironmental scienceCivil engineeringEngineeringGeologyChina

Abstract

fetched live from OpenAlex

Abstract The core goal of Eco-economic Zone planning is to enhance the coordinated development of cities in the basin in terms of main function realization and livelihood development and achieve coordinated and high-quality development in the basin. Using a double-difference approach, this paper uses panel data from 2004 to 2019 for 49 prefecture-level cities in Jiangxi, Hunan, Hubei, and Jiangsu provinces to test the proposed theoretical hypotheses and empirically examine the driving effects and mechanisms of the three Eco-economic Zones on the coordinated development of cities along the river basin. The study finds that the three zones significantly enhance the coordinated development of cities along the zones. The dimension of livelihood development is more significant in strengthening cities' coordinated development along the three zones. At the same time, there is substantial regional individual heterogeneity and temporal dynamic heterogeneity in the driving effect of the plan. The Eco-economic Zone Plan is designed to enhance the coordinated development of cities along the Great Lakes Basin through green economic development and ecological environment improvement. The above findings help explore new experiences in the protection, management, and development of the Great Lakes Basin. They have important policy implications for cities in the Eco-economic Zone to develop a “new path” of collaborative ecological and economic development.

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)0.022
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.784
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0220.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.003
Research integrity0.0000.003
Insufficient payload (model declined to judge)0.0010.001

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 head0.091
GPT teacher head0.346
Teacher spread0.255 · 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; both teacher heads agree on what is shown here.

Study designTheoretical or conceptual
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
Published2022
Admission routes1
Has abstractyes

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