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Mobile Phones and Development: An Analysis of IDRC‐Supported Projects

2009· article· en· W2128393480 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.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueThe Electronic Journal of Information Systems in Developing Countries · 2009
Typearticle
Languageen
FieldComputer Science
TopicICT in Developing Communities
Canadian institutionsnot available
Fundersnot available
KeywordsMobile phoneInternational developmentContext (archaeology)Thematic analysisLivelihoodMillennium Development GoalsDeveloping countryBusinessQualitative researchTelecommunicationsEngineeringPolitical scienceEconomic growthSociologyAgricultureGeographySocial science

Abstract

fetched live from OpenAlex

Abstract In the context of the rapid growth of mobile phone penetration in developing countries, mobile telephony is currently considered to be particularly important for development. Yet, until recently, very little systematic evidence was available that shed light on the developmental impacts of mobile telecommunication. The Information and Communication Technology for Development (ICT4D) program of the International Development Research Centre (IDRC), Canada, has played a critical role in filling some of the research gaps through its partnerships with several key actors in this area. The objective of this paper is to evaluate the case of mobile phones as a tool in solving development problems drawing from the evidence of IDRC supported projects. IDRC has supported around 20 projects that cut across several themes such as livelihoods, poverty reduction, health, education, the environment and disasters. The projects will be analyzed by theme in order to provide a thematic overview as well as a comparative analysis of the development role of mobile phones. In exploring the evidence from completed projects as well as the foci of new projects, the paper summarizes and critically assesses the key findings and suggests possible avenues for future research.

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)0.003
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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.586
Threshold uncertainty score0.493

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0000.003
Open science0.0010.000
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 head0.013
GPT teacher head0.254
Teacher spread0.240 · 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