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Record W2031569182 · doi:10.1177/154193120605001710

Team Response to Workload Transition: The Role of Team Structure

2006· article· en· W2031569182 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

VenueProceedings of the Human Factors and Ergonomics Society Annual Meeting · 2006
Typearticle
Languageen
FieldEngineering
TopicMilitary Strategy and Technology
Canadian institutionsUniversité LavalDefence Research and Development Canada
Fundersnot available
KeywordsWorkloadContext (archaeology)Task (project management)Transition (genetics)Event (particle physics)Function (biology)Computer scienceSimulationOperations managementAeronauticsEngineeringGeographyBiologySystems engineeringPhysicsOperating system

Abstract

fetched live from OpenAlex

The present study aims to investigate how teams respond to workload transition due to a sudden and unexpected event in a complex and dynamic command and control (C2) environment. The C 3 Fire microworld (Granlund, 1998), a forest fire-fighting simulation, is used to compare divisional (territory-specific) and functional (role-specific) teams. Workload transition is induced by the sudden appearance of a second fire. Results show that functional teams' performance decreases while their communication frequency increases following the workload transition. However, they are faster to detect the second fire. This pattern of results suggests that in the context of C2 environments, the impact of a workload escalation varies as a function of team structure (functional vs. divisional) and the type of task (fire detection vs. fire fighting).

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)0.000
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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.222
Threshold uncertainty score0.425

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 head0.004
GPT teacher head0.178
Teacher spread0.174 · 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