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Record W2228277975 · doi:10.11575/prism/30519

The Complexities of Computer-Supported Collaboration

2006· article· en· W2228277975 on OpenAlexaff
Mark Hancock, Sheelagh Carpendale

Bibliographic record

VenuePRISM (University of Calgary) · 2006
Typearticle
Languageen
FieldPsychology
TopicTeam Dynamics and Performance
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsComputer-supported cooperative workVariety (cybernetics)Computer scienceProcess (computing)Collaborative softwareHuman–computer interactionData scienceManagement scienceWork (physics)World Wide WebEngineeringArtificial intelligenceProgramming language

Abstract

fetched live from OpenAlex

We introduce the idea of considering computer supported collaborative work as a complex adaptive system (CAS). In other disciplines, such as physics, biology and ecology, the idea of a CAS has proven useful in explaining a wide variety of phenomena. We define a CAS and then describe how CSCW fits that definition. We demonstrate that the concepts in CAS theory can be applied to help understand computer supported collaboration and provide examples of catastrophe and chaos in physics showing how they can be paralleled in CSCW. The implications of the application of CAS theory to CSCW include greater insight into the computer supported collaborative process and inform both evaluation methodology and design of applications.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.733
Threshold uncertainty score0.374

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 studies0.0000.000
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 head0.010
GPT teacher head0.220
Teacher spread0.210 · 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 designObservational
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

Citations3
Published2006
Admission routes1
Has abstractyes

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