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Record W609745217 · doi:10.25300/misq/2015/39.2.06

Leading Collaboration In Online Communities1

2015· article· en· W609745217 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

VenueMIS Quarterly · 2015
Typearticle
Languageen
FieldSocial Sciences
TopicKnowledge Management and Sharing
Canadian institutionsMcGill University
Fundersnot available
KeywordsKnowledge managementOnline participationData scienceComputer scienceWorld Wide WebPublic relationsPolitical scienceThe Internet

Abstract

fetched live from OpenAlex

Despite the growing importance of online communities in creating knowledge and facilitating collaboration, there has been limited research examining the role of leaders in such settings. In this paper, we propose a framework that integrates behavioral and structural approaches to explore the antecedents of leadership in online communities focused on knowledge work. Specifically, we propose that sociability and knowledge contribution behaviors as well as structural social capital lead to being identified as a leader by members of the online community. We test this framework using social network, survey, and message-level content analysis data collected from three different online communities focused on technical topics. The results from our zero inflated negative binomial models, with 6,709 messages from 976 individuals, provide strong support for the framework that is developed in this study. Our study contributes to both theory and practice by identifying the behavioral and structural antecedents of leadership in online communities.

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: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.296
Threshold uncertainty score0.908

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 communication0.0000.000
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 head0.074
GPT teacher head0.364
Teacher spread0.290 · 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