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Record W1597562258 · doi:10.1108/13527590810898491

Do teams grow up one stage at a time?

2008· article· en· W1597562258 on OpenAlexaff
Jack K. Ito, Céleste M. Brotheridge

Bibliographic record

VenueTeam Performance Management · 2008
Typearticle
Languageen
FieldPsychology
TopicTeam Dynamics and Performance
Canadian institutionsUniversité du Québec à MontréalUniversity of Regina
Fundersnot available
KeywordsDependency (UML)Stage (stratigraphy)PsychologyConfirmatory factor analysisStructural equation modelingProcess (computing)Test (biology)Path analysis (statistics)Operations managementProcess managementSocial psychologyComputer scienceStatisticsEconomicsMathematicsEngineeringArtificial intelligence

Abstract

fetched live from OpenAlex

Purpose The purpose of this paper is to determine whether the stages of group development are path‐dependent or whether a stage can have a direct influence beyond an adjacent stage; to test a model that distinguishes between task and process characteristics; and to examine the validity of the Group Development Assessment. Design/methodology/approach A total of 204 public servants responded to questionnaires pertaining to their respective teams. Their responses to the Group Development Assessment were analyzed through the use of confirmatory factor analyses and structural equation modeling. Findings This study found that, in general, teams follow a predictable pattern of growth (i.e. they grow up one stage at a time), but their ability to grow is influenced by how well they addressed previous challenges. Path dependency was partly supported since the prior stage was generally the strongest predictor of the subsequent stage. The findings on path dependency are consistent with pendular models since changes in an earlier stage can have significant effects on later stages. Support was found for the separation of tasks and process behaviors. The Group Development Assessment was reasonably reliable, and its items generally classified into their corresponding stages. Research limitations/implications The finding that, at a given moment, a variable such as dependency has a strong independent relationship with interdependence is consistent with a short time lag. However, a longitudinal study is needed to assess such lags. Practical implications As a group meets the challenges of a stage and moves forward, the assumptions or the foundations laid before need to be supported; otherwise the group may regress. Originality/value The study tests a group development model and offers recommendations for group interventions.

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)0.003
metaresearch head score (Gemma)0.019
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 score0.004
Threshold uncertainty score0.018

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.019
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.002
Scholarly communication0.0020.004
Open science0.0010.003
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.001

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 head0.022
GPT teacher head0.264
Teacher spread0.242 · 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

Citations15
Published2008
Admission routes1
Has abstractyes

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