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Record W2555621660 · doi:10.1177/1046496416676892

Role Variability in Self-Organizing Teams Working in Crisis Management

2016· article· en· W2555621660 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 · 2016
Typearticle
Languageen
FieldPsychology
TopicTeam Dynamics and Performance
Canadian institutionsHEC MontréalUniversité LavalDefence Research and Development Canada
Fundersnot available
KeywordsFlexibility (engineering)AmbiguityPsychologySelf-managementAffect (linguistics)Knowledge managementSocial psychologyApplied psychologyProcess managementComputer scienceBusinessArtificial intelligenceManagement

Abstract

fetched live from OpenAlex

Crisis management teams face situations characterized by high risk, time pressure, and uncertainty and must adapt to a wide range of circumstances. Self-organizing teams have been proposed as an alternative to more traditional functional teams as they are described as adaptive and promptly reconfigurable. This study investigated whether self-organizing teams display more role flexibility than functional teams and the impact on performance and coordination. Teams were assigned to either a functional or a self-organizing structure and completed scenarios in a functional simulation. Results revealed that self-organizing teams performed and coordinated better than functional teams. As expected, self-organizing teams showed more role variability across and within teams. However, greater variability in role allocation within teams was associated with poorer performance and coordination. We conclude that flexibility in roles can be beneficial but that too much variability can be associated with role ambiguity and negatively affect a team’s ability to achieve its goals.

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)0.007
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.177
Threshold uncertainty score0.625

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0070.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.046
GPT teacher head0.350
Teacher spread0.304 · 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