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Record W2046742742 · doi:10.1518/155534307x232848

Using GOMS for Modeling Routine Tasks Within Complex Sociotechnical Systems: Connecting Macrocognitive Models to Microcognition

2007· article· en· W2046742742 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

VenueJournal of Cognitive Engineering and Decision Making · 2007
Typearticle
Languageen
FieldComputer Science
TopicCognitive Science and Mapping
Canadian institutionsCarleton University
Fundersnot available
KeywordsSociotechnical systemComputer scienceTask (project management)Cognitive ergonomicsCognitionCognitive modelSocio-cognitiveWork (physics)Systems modelingHuman–computer interactionComplex systemManagement scienceSystems engineeringArtificial intelligenceEngineeringSoftware engineeringPoison controlPsychologyHuman factors and ergonomics

Abstract

fetched live from OpenAlex

Cognitive modeling has not yet played much of a role in the study of sociotechnical systems. Arguably, this is because most cognitive modeling systems were originally created to model microcognitive results, not the types of macrocognitive behaviors that drive sociotechnical systems (Klein et al., 2003). However, this does not mean that cognitive modeling systems cannot be adapted to deal with macrocognitive activities in ways that are relevant to cognitive engineering. Previous research using GOMS in sociotechnical systems indicated that GOMS is problematic to use when interruptions and task switching are common; therefore, we added new theoretical structures to GOMS to deal with these issues. We tested the system by constructing a model of routine network maintenance and installation at a large telecommunications company. We then compared the model predictions with observations of the work. The results showed that the model results were useful in guiding the research and organizing the findings.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.417
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.104
GPT teacher head0.354
Teacher spread0.250 · 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