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The NetLab Network

2018· book-chapter· en· W4241508185 on OpenAlexaffabout
Dimitrina Dimitrova, Barry Wellman

Bibliographic record

VenueAdvances in multimedia and interactive technologies book series · 2018
Typebook-chapter
Languageen
FieldSocial Sciences
TopicSocial Media and Politics
Canadian institutionsYork University
Fundersnot available
KeywordsSensibilitySocial capitalSocial network (sociolinguistics)Perspective (graphical)Intersection (aeronautics)The InternetSociologyPublic relationsFocus (optics)Social mediaPolitical scienceComputer scienceSocial scienceWorld Wide WebGeographyArtificial intelligence

Abstract

fetched live from OpenAlex

The authors discuss the NetLab Network – an interdisciplinary network studying the intersection of social networks, communication networks, and computer networks. It has developed since 2000 from an informal network of collaborators into a far flung virtual laboratory with members from across Canada and the United States as well as from Chile, Hungary, Israel, Japan, Norway, Portugal, and the United Kingdom. Connecting them is a shared sensibility of interpreting behavior from a social network perspective rather than seeing the world as composed of bounded groups, tree-like hierarchies, or aggregates of disconnected individuals. NetLab's researchers focus on the interplay between social and technological links, social capital in job searches and business settings, new media and community, internet and personal relations, social media, households, networked organizations, and knowledge transfer. NetLab has had two main achievements: first, its researchers make substantive contributions to the issues they study, and second, they demonstrate that this model of scholarly collaboration works.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.762
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.007
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0010.001
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 head0.012
GPT teacher head0.307
Teacher spread0.295 · 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 designNot applicable
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
Published2018
Admission routes2
Has abstractyes

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