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Record W2262305043 · doi:10.29379/jedem.v4i2.137

Democratic Process in Online Crowds and Communities

2012· article· en· W2262305043 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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJeDEM - eJournal of eDemocracy and Open Government · 2012
Typearticle
Languageen
FieldComputer Science
TopicOpen Source Software Innovations
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsCrowdsReputationDemocracyCollective actionCitizen journalismPublic relationsPeer productionParticipatory cultureAction (physics)Social mediaSociologyProcess (computing)Crowd psychologyOnline forumAffect (linguistics)Political scienceKnowledge managementInternet privacyPsychologyComputer scienceSocial psychologyMedia studiesWorld Wide WebSocial scienceCommunicationComputer securityPoliticsLaw

Abstract

fetched live from OpenAlex

This paper explores the underlying structures that support participation and reputation in online crowd and community-based peer productions. Building on writings on open source, peer production, participatory culture, and social networks, the paper describes crowd and community structures as two ends of a continuum of collective action - from lightweight to heavyweight - differentiated by the extent of connectivity and engagement between contributions and among contributors. This is followed by an examination of the recognition, reputation and reward systems that support these collectives, and how these affect who controls and who contributes information. The aim of this exploration is to gain insight for understanding motivations and structures for e-participation in these different, potentially democratic, forums.

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)0.001
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.064
Threshold uncertainty score0.565

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 communication0.0000.002
Open science0.0010.001
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 head0.029
GPT teacher head0.311
Teacher spread0.282 · 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