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Record W2128338110 · doi:10.1177/1046496413478205

Mental Model Updating and Team Adaptation

2013· article· en· W2128338110 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

VenueSmall Group Research · 2013
Typearticle
Languageen
FieldPsychology
TopicTeam Dynamics and Performance
Canadian institutionsUniversity of ReginaYork University
Fundersnot available
KeywordsMental modelTask (project management)PsychologyAdaptation (eye)Context (archaeology)Similarity (geometry)CognitionCognitive psychologyTeam effectivenessTask analysisMental fatigueTeam compositionApplied psychologySocial psychologyComputer scienceKnowledge managementArtificial intelligenceCognitive scienceEngineering

Abstract

fetched live from OpenAlex

In this article, we build on theories of team adaptation by exploring the role of team members’ cognitive knowledge structures in team adaptation to a changing task context. We introduce the notion of mental model updating as the extent to which team members update their mental models in reaction to a change in the task situation. In a laboratory study we investigate the relations between initial mental model similarity and accuracy, team mental model updating, the development of novel interaction patterns, and postchange team performance. The results indicate that mental model updating is positively related to postchange team performance. Also, team adaptation patterns accounted for the effect of mental model updating on postchange team performance. We did not find evidence for a positive relation between initial mental model similarity and accuracy and mental model updating.

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)0.001
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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.943
Threshold uncertainty score0.618

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.132
GPT teacher head0.390
Teacher spread0.258 · 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