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Record W2130953957 · doi:10.1109/icalt.2005.97

CSCL for NGO's cross cultural virtual teams in Africa: an Ethiopian children advocacy case study against exclusion and toward facilitation of expression, innovation and creativity

2005· article· en· W2130953957 on OpenAlexaff
Rody R. Klein, R. Letaïef, S. Carter, Ghislaine Chabert, Johanna Lasonen, Todd Lubart

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldSocial Sciences
TopicKnowledge Management and Sharing
Canadian institutionsEmily Carr University of Art and Design
Fundersnot available
KeywordsCreativityContext (archaeology)The artsKnowledge managementFacilitationAsynchronous communicationThe InternetComputer sciencePublic relationsPsychologySociologyPolitical scienceWorld Wide WebSocial psychology

Abstract

fetched live from OpenAlex

This exploratory pilot study shows that NGO's involved in Children Advocacy through Arts in Africa are willing to use a groupware, meaning a computer supported collaborative learning (CSCL) environment. Innovative ideas and best practices among NGOs would be shared easily worldwide. Little scientific information is available to help them make a sound choice. This study suggests that some NGOs based in Ethiopia/Africa have specific needs which should translate in specific context analysis and interface development: 1) an intercultural approach to creativity, arts and innovation, and 2) emphasis should be placed on tools to facilitate asynchronous systematic conception and sharing of intra and cross-organizations information (log book, systematic case studies forms, best practices, music/sound, picture, short movies, literature,) to facilitate continuity, synergy, creativity and innovation. Under contribution being also a problem for most online communities, human and social sciences could provide mid level design principles to improve motivation.

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 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)0.001
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: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.136
Threshold uncertainty score0.442

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
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 head0.060
GPT teacher head0.378
Teacher spread0.318 · 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 teacher head, 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

Citations7
Published2005
Admission routes1
Has abstractyes

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