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Record W4366975152 · doi:10.1515/zfw-2023-0001

<b>How outward FDIs affect income: experiences from Chinese city-regions</b>

2023· article· en· W4366975152 on OpenAlexaff
Ruilin Yang, Harald Bathelt

Bibliographic record

VenueZFW – Advances in Economic Geography · 2023
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicInternational Business and FDI
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsChinaDestinationsForeign direct investmentAbsorptive capacityBusinessResource (disambiguation)Affect (linguistics)Investment (military)Economic geographyInternational economicsDemographic economicsEconomicsGeographyIndustrial organization

Abstract

fetched live from OpenAlex

Abstract While outward foreign direct investments (OFDIs) shift resources from a home economy to foreign destinations, increased market and resource access as well as technological and knowledge effects in return have positive impacts on the home region. Such effects may be especially important in emerging contexts, such as that of China. Analyzing data of 285 Chinese city-regions, this paper investigates the impact of OFDIs on home-region income. We show that foreign investment activity positively and significantly impacts income levels in the home region, with differentiated effects depending on the knowledge characteristics of investments and regional absorptive capacity.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.206
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.003
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.008
GPT teacher head0.238
Teacher spread0.230 · 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 teacher head, not a consensus.

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

Citations24
Published2023
Admission routes1
Has abstractyes

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