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Record W1581196114 · doi:10.15353/joci.v9i1.3186

Telecenter Web Portals in Latin American and Arab Nations: A Comparative Analysis

2012· article· en· W1581196114 on OpenAlexvenueno aff
Paola Prado, Dana Janbek

Bibliographic record

VenueThe Journal of Community Informatics · 2012
Typearticle
Languageen
FieldComputer Science
TopicICT in Developing Communities
Canadian institutionsnot available
Fundersnot available
KeywordsProsperityPremiseDisadvantageDigital divideDigital literacyLatin AmericansPublic relationsLiteracyPolitical scienceSociologyEconomic growthKnowledge managementInformation and Communications TechnologyComputer scienceEconomicsPedagogy

Abstract

fetched live from OpenAlex

As societies become increasingly inter-connected, communities that do not bridge the digital divide find themselves at a disadvantage in the global market economy. Numerous telecenter initiatives in developing nations aim to foster prosperity through the adoption of information communication technologies (ICTs). This study documents how rural communities at varying levels of development in ten developing nations in Latin America and the Arab World create virtual community and reflect their identity through this new medium. Based on the premise that active participation improves the learning process, as suggested by constructionism theory, this study examined telecenter portals for evidence of user participation in digital literacy initiatives. Findings indicate that most telecenter portals offer few interactive applications, therefore limiting the opportunities for users to practice digital literacy skills and create virtual 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)0.004
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 score0.018
Threshold uncertainty score0.036

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.005
Science and technology studies0.0020.001
Scholarly communication0.0020.002
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0050.000

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 head0.053
GPT teacher head0.316
Teacher spread0.263 · 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

Citations5
Published2012
Admission routes1
Has abstractyes

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