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Record W2049839475 · doi:10.1007/s11031-013-9365-2

Flow experience and team performance: The role of team goal commitment and information exchange

2013· article· en· W2049839475 on OpenAlexafffund
Caroline Aubé, Éric Brunelle, Vincent Rousseau

Bibliographic record

VenueMotivation and Emotion · 2013
Typearticle
Languageen
FieldPsychology
TopicFlow Experience in Various Fields
Canadian institutionsUniversité de MontréalHEC Montréal
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsPsychologyApplied psychologyPsychological interventionSocial psychologyTeam compositionInformation exchangeKnowledge managementComputer science

Abstract

fetched live from OpenAlex

While a number of studies show that the flow experience is related to different outcomes at the individual level, the role of flow in work teams remains unclear. This study contributes to the advancement of knowledge on flow by testing the relationships between this psychological state, team goal commitment and team performance. Data were gathered from 85 teams comprised of graduate and undergraduate students who participated in a project management simulation. The results show that the flow experience is positively related to team performance. This relationship is mediated by team goal commitment and moderated by the level of information exchange between team members. In practical terms, the results of this study show that managers should implement interventions fostering the flow experience in their teams, while at the same time encouraging information exchange between members.

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.003
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0030.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.012
GPT teacher head0.243
Teacher spread0.232 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations133
Published2013
Admission routes2
Has abstractno

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