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Record W2095904896

Wiring sub-Saharan Africa for development

2005· article· en· W2095904896 on OpenAlexaff
Tokunbo Ojo

Bibliographic record

VenueThe International Journal of Education and Development using Information and Communication Technology (The University of the West Indies) · 2005
Typearticle
Languageen
FieldEngineering
TopicICT Impact and Policies
Canadian institutionsAlgonquin College
Fundersnot available
KeywordsICTSLiteracyEconomic growthDigital divideInformation and Communications TechnologyPolitical scienceDeveloping countryBusinessPublic relationsEconomics
DOInot available

Abstract

fetched live from OpenAlex

This paper discusses the uses of ICTs, the dimensions of access and the digital divide, and the development of telecentres in the Sub-Saharan African region. It illustrates that the development initiatives perceived technical access to computers and other ICTs as the only prerequisite to economic and social development when in actual fact extremely important social access to literacy, content, housing and health is not given much consideration in the development agenda. Finally, it discusses experiences at one of the telecentres, the Nakaseke Multipurpose Telecentre in Uganda, by drawing on data from the evaluative report of the IDRC-sponsored telecentres in Africa.

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)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.028
Threshold uncertainty score0.094

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0020.000
Scholarly communication0.0020.001
Open science0.0000.003
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0280.003

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 head0.015
GPT teacher head0.228
Teacher spread0.213 · 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 designNot applicable
Domainnot available
GenreOther

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

Citations28
Published2005
Admission routes1
Has abstractyes

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