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Virtual Communities

2009· book-chapter· en· W4253387777 on OpenAlexaff
Ben Kei Daniel

Bibliographic record

VenueIGI Global eBooks · 2009
Typebook-chapter
Languageen
FieldSocial Sciences
TopicKnowledge Management and Sharing
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsTechnological determinismKnowledge managementVirtual communitySocializationSocial capitalSociologyContext (archaeology)Public relationsPolitical scienceEngineering ethicsSocial scienceComputer scienceEngineeringGeographyWorld Wide WebThe Internet

Abstract

fetched live from OpenAlex

The growth of virtual communities and their continuous impact on social, economic and technological structures of societies has attracted a great deal of interest among researchers, systems designers and policy makers to examine the formation, development, sustainability and utility of these communities. Over the last two decades, the growth in research into virtual communities, though fairly diverse, can be broadly categorized into two dominant perspectives—technological determinism and social constructivism. The basic tenet of the technology determinism research is that technology shapes cultural values, social structure, and knowledge. This Chapter provides a general overview of research on virtual communities. It describes two particular types of virtual communities relevant to the analysis of social capital described in the book; virtual learning communities and distributed communities of practice. The goal of the Chapter is to provide an overall context in which social capital is reported in the book. The Chapter also describes other areas in which virtual communities are currently used. These include education, health care, business, socialization and mediating interaction among people in Diaspora.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.611
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.001

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 head0.042
GPT teacher head0.288
Teacher spread0.246 · 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.

Study designTheoretical or conceptual
Domainnot available
GenreOther

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

Citations0
Published2009
Admission routes1
Has abstractyes

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