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Record W2127848723 · doi:10.1109/enabl.2000.883711

The mechanics of collaboration: developing low cost usability evaluation methods for shared workspaces

2002· article· en· W2127848723 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicUsability and User Interface Design
Canadian institutionsUniversity of CalgaryUniversity of Saskatchewan
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsUsabilityWorkspaceCollaborative softwareComputer scienceHuman–computer interactionContext (archaeology)Heuristic evaluationTask (project management)Knowledge managementConceptual frameworkEngineeringSystems engineeringArtificial intelligence

Abstract

fetched live from OpenAlex

We introduce a conceptual framework that articulates the mechanics of collaboration for shared-workspace groupware: the low level actions and interactions that must be carried out to complete a task in a shared manner. These include communication, coordination, planning, monitoring, assistance, and protection. The framework also includes three general measures of these mechanics: effectiveness, efficiency, and satisfaction. The underlying idea of the framework is that some usability problems in groupware systems are not inherently tied to the social context in which the system is used but rather are a result of poor support for the basic activities of collaborative work in shared spaces. We believe that existing low-cost evaluation methods-heuristic evaluation, walkthroughs, user observations and questionnaires-can be modified to include this framework in a way that helps a groupware evaluator uncover these usability problems.

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)0.004
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.926
Threshold uncertainty score0.279

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
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 head0.139
GPT teacher head0.398
Teacher spread0.260 · 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

Quick stats

Citations225
Published2002
Admission routes2
Has abstractyes

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