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Record W2094619929 · doi:10.4018/jgim.2010070103

Do Foreign Direct Investment (FDI) and Trade Openness Explain the Disparity in ICT Diffusion between Asia-Pacific and the Islamic Middle Eastern Countries?

2010· article· en· W2094619929 on OpenAlexaff
Farid Shirazi, Roya Gholami, Dolores Añón Higón

Bibliographic record

VenueJournal of Global Information Management · 2010
Typearticle
Languageen
FieldEngineering
TopicICT Impact and Policies
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsOpenness to experienceForeign direct investmentInformation and Communications TechnologyMiddle EastEconomicsDiffusionInvestment (military)International economicsInternational tradeBusinessPoliticsGeographyPolitical scienceMacroeconomics

Abstract

fetched live from OpenAlex

This study investigates the impact of FDI and trade openness on ICT diffusion in the Asia-Pacific and Middle East regions from 1996-2005. The results indicate that while dissimilarities exist between the economies included in this study in terms of their level of socio-economic and political development, education and the growth of GDP have had a positive impact on ICT diffusion in both regions. However, while FDI has generally had a positive and significant impact on ICT diffusion in Asia-Pacific economies, its impact on Middle Eastern economies has been detrimental. The results of this study also show that trade-openness has had, in general, a positive and significant impact on ICT diffusion.

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)0.005
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 score0.014
Threshold uncertainty score0.028

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.002
Open science0.0000.001
Research integrity0.0010.001
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 head0.009
GPT teacher head0.221
Teacher spread0.212 · 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

Citations26
Published2010
Admission routes1
Has abstractyes

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