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ICT Infrastructure Expansion in Sub‐Saharan Africa: An Analysis of Six West African Countries from 1995 to 2002

2006· article· en· W4234558460 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueThe Electronic Journal of Information Systems in Developing Countries · 2006
Typearticle
Languageen
FieldEngineering
TopicICT Impact and Policies
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsInformation and Communications TechnologyInvestment (military)Economic growthBusinessDeveloping countryDevelopment economicsPolitical scienceEconomics

Abstract

fetched live from OpenAlex

Abstract A decade has passed since many African countries started consistently investing in the new Information and Communication Technology (ICT). Currently, there is need for more research on the impact of these investments on the expansion of productive capacity necessary for economic and social developments in this region on the world. Presently, the African Telecommunication Union (ATU) is advocating higher levels of investment in ICT in African countries, regional integration and new policies for the ICT sector. High‐tech parks are being constructed for the development of the technology and to attract and encourage business initiatives in the sector. However, UNDP agencies for information technology and social development have not yet been able to state firmly whether the adoption of ICT has had a significant impact on less developed countries in general and African countries in particular. In this paper, I demonstrate that the investments in the ICT sector have resulted in technical progress. This study uses a DEA approach and some novel analysis to examine the impacts of investments in the ICT sectors of six West African countries during the period of 1995 and 2002.

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.

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)0.001
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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.891
Threshold uncertainty score0.629

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.005
GPT teacher head0.211
Teacher spread0.207 · 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