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Record W2885862374 · doi:10.4236/ti.2018.93012

Inquiry into FDI Pattern of China and the Economies along the Belt & Road

2018· article· en· W2885862374 on OpenAlexvenueno aff
Junrong Liu, Yuan Liu

Bibliographic record

VenueTechnology and Investment · 2018
Typearticle
Languageen
FieldSocial Sciences
TopicGlobal Political and Economic Relations
Canadian institutionsnot available
FundersNational Office for Philosophy and Social Sciences
KeywordsForeign direct investmentChinaProsperityOrder (exchange)Investment (military)International tradeBusinessDistribution (mathematics)International economicsEconomicsEconomic growthPolitical scienceMacroeconomicsFinance

Abstract

fetched live from OpenAlex

This paper empirically analyzes the FDI Pattern of China and the other economies along the Belt & Road Initiative. The analysis results show that 1) the mutual FDI between China and the economies along the Belt & Road regions has continuously increased, and the mutual dependence of FDI continues to deepen, but there still is some imbalance existing in FDI dependence and distribution; 2) the Belt & Road Initiative has its objective material basis and subjective willingness for regional FDI cooperation; 3) China and the other economies along the Belt & Road Initiative, need to further utilize the complementary advantages in their industrial and economic structures for deepening the bilateral and multilateral FDI cooperation; 4) China and the countries along the Belt & Road need to clear the investment barriers and achieve a win-win situation for international investment and cooperation, in order to promote the continuous deepening of the Belt & Road Initiative and realize regional common prosperity.

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)0.000
metaresearch head score (Gemma)0.001
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 score0.041
Threshold uncertainty score0.082

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0000.001
Scholarly communication0.0010.001
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 head0.026
GPT teacher head0.291
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

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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