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Record W2804474601 · doi:10.5539/res.v10n2p197

Does Road Investment Really Promote the Export? Evidence from Sichuan County-level Data of China

2018· article· en· W2804474601 on OpenAlexvenueno aff
Lihe Xu, Jiaqi Liu, Xiaoshan Yan

Bibliographic record

VenueReview of European Studies · 2018
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicGlobal trade and economics
Canadian institutionsnot available
FundersNational Natural Science Foundation of China
KeywordsInvestment (military)ChinaTertiary sector of the economyPanel dataBusinessService (business)Manufacturing sectorCapital investmentPrivate sectorIndustrial organizationFinanceInternational tradeEconomicsInternational economicsEconomic growthMarketingEconometricsPolitical science

Abstract

fetched live from OpenAlex

Whether road infrastructure promotes export is still a concerned issue debated in the previous studies. In this paper, we conduct a panel data using two data sources from year 2003 to 2013, examining the relationship between road investment and export. The primary results show that road investment significantly restricts local export. A further test indicates that the road infrastructure benefits service sector, 1) abstract more private capital investment on service sector than manufacturing sector, 2) reduce the employee of tradable sector. Then manufacturing sector was constrained. The results are robust when a set test is carried out.

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)0.001
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.105
Threshold uncertainty score0.208

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.003
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.000
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 head0.297
GPT teacher head0.317
Teacher spread0.020 · 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 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
Published2018
Admission routes1
Has abstractyes

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