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Record W2991910547 · doi:10.15353/joci.v12i1.3241

Community Mediation through ICTs: Seeking to Bridge Digital and Community Divides

2016· article· en· W2991910547 on OpenAlexaffvenue
Arlene Bailey, Ojelanki Ngwenyama

Bibliographic record

VenueThe Journal of Community Informatics · 2016
Typearticle
Languageen
FieldComputer Science
TopicICT in Developing Communities
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsMediationPublic relationsICTSSocial capitalInformation and Communications TechnologyImplementationEmpirical researchNewspaperPolitical scienceField (mathematics)Bridge (graph theory)Inclusion (mineral)Digital divideSociologyEconomic growthBusinessSocial scienceComputer scienceAdvertisingEconomics

Abstract

fetched live from OpenAlex

Information and communication technologies are being utilized to support social and economic development in marginalized communities in developing countries. In this paper, we explore an emerging role for telecentres - that of community mediation. Our research is based on empirical observations through a field study, and an analysis of local newspaper articles. We investigate ways in which these community mediation strategies through telecentres may support social inclusion and development of social capital. The evolving role of telecentres in the area of peace-making suggests that the factors explored in this study will be of interest to researchers and practitioners in telecentre implementations.

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)0.007
metaresearch head score (Gemma)0.018
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.011
Threshold uncertainty score0.036

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.018
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0040.003
Science and technology studies0.0100.014
Scholarly communication0.0110.016
Open science0.0020.021
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0110.001

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 head0.062
GPT teacher head0.286
Teacher spread0.224 · 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 designQualitative
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

Citations12
Published2016
Admission routes2
Has abstractyes

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