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Record W2202451239 · doi:10.7202/1069240ar

THE INFORMATION SOCIETY, POVERTY ANDDEVELOPMENT: AN AFRICAN PERSPECTIVE

2020· article· en· W2202451239 on OpenAlexvenueno aff
Nsongurua J. Udombana

Bibliographic record

VenueRevue québécoise de droit international · 2020
Typearticle
Languageen
FieldEngineering
TopicICT Impact and Policies
Canadian institutionsnot available
FundersNew Partnership for Africa's Development
KeywordsDigital divideUnderdevelopmentPovertyDeveloping countryTransaction costBusinessInformation societyEconomic growthInformation and Communications TechnologySustainable developmentDevelopment economicsEconomicsPolitical scienceEconomyFinance

Abstract

fetched live from OpenAlex

Our age of the Information Society (IS), as represented by Information and Communications Technologies (ICTs), offers immense opportunities for sustainable economic development and the reduction of poverty. It does so by increasing access to market information and reducing transaction costs for poor farmers and traders; by increasing efficiency, competitiveness and market access of developing country firms; and by enhancing the ability of developing countries to participate in the global economy, thereby exploiting the comparative advantage in factor costs, in particular skilled labour. Yet, these goals are unattainable in the present state of digital divide, since access to ICTs is determined not only by infrastructure but also by people’s ability to afford and use them. Furthermore, the digital divide perpetuates underdevelopment, which is Africa’s current condition. Bridging that gap requires creating a knowledge society and forging new partnerships for development among members of the international community.

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)0.002
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: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.014
Threshold uncertainty score0.042

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0040.005
Science and technology studies0.0050.010
Scholarly communication0.0060.008
Open science0.0000.004
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0060.000

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 head0.222
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 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
Published2020
Admission routes1
Has abstractyes

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