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Record W3152664133 · doi:10.5539/ijef.v13n5p22

The Relationship Between Information & Communication Technology and Foreign Direct Investment Inflow to Africa

2021· article· en· W3152664133 on OpenAlexvenueno aff
Abdisalan Salad Warsame

Bibliographic record

VenueInternational Journal of Economics and Finance · 2021
Typearticle
Languageen
FieldEngineering
TopicICT Impact and Policies
Canadian institutionsnot available
FundersChina Scholarship Council
KeywordsInflowForeign direct investmentInformation and Communications TechnologyBusinessPanel dataInvestment (military)EconomicsInternational economicsOceanographyPolitical scienceMacroeconomicsPoliticsGeologyEconometrics

Abstract

fetched live from OpenAlex

This paper examined the relationship between the increasing Information & Communication Technology (ICT) infrastructure in Africa and foreign direct investment inflow to Africa using panel data sourced from ITU and WDI over 17 years (1998-2014). The paper applies both the fixed-effect and difference-in-differences models. The results indicate that there is a positive correlation between FDI inflow and ICT level in the host country.  The surge in ICT infrastructure in 2009 has substantially increased the FDI inflow to Africa. This increase in FDI inflow was more in the countries that have access to the sea than the countries that have no access to the sea. In other words, the average scale change in FDI inflow to the countries with no access to the sea is smaller than the countries with the coastline.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.803
Threshold uncertainty score0.138

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.024
GPT teacher head0.240
Teacher spread0.216 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations1
Published2021
Admission routes1
Has abstractyes

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