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Record W2068334264 · doi:10.1002/pmj.20268

Teamwork in Integrated Design Projects: Understanding the Effects of Trust, Conflict, and Collaboration on Performance

2011· article· en· W2068334264 on OpenAlexafffund
François Chiocchio, Daniel Forgues, David Paradis, Ivanka Iordanova

Bibliographic record

VenueProject Management Journal · 2011
Typearticle
Languageen
FieldPsychology
TopicTeam Dynamics and Performance
Canadian institutionsÉcole de Technologie SupérieureUniversité de Montréal
FundersAgência Regional para o Desenvolvimento da Investigação, Tecnologia e InovaçãoUniversity of Salford ManchesterMcGill University
KeywordsTeamworkCompetition (biology)Multidisciplinary approachKnowledge managementOutcome (game theory)Conflict managementAffect (linguistics)PsychologyProcess managementBusinessComputer scienceManagementSociology

Abstract

fetched live from OpenAlex

Teamwork during integrated design projects is complex. We address this by investigating how trust, collaboration, and conflict evolve over time to affect performance. Our results stem from data gathered using validated self-report questionnaires with 38 participants in 5 multidisciplinary teams at three points in time during a 6-week integrated design competition. Results show that without collaboration, trust and conflict have no bearing on performance. In addition to an unambiguous practical outcome—fostering collaboration helps build trust and manage conflict—our study points to theoretical developments: as trust- and conflict-performance relations grow over time, so does collaboration's mediating effect.

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)0.011
metaresearch head score (Gemma)0.049
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 score0.011
Threshold uncertainty score0.059

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0110.049
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.002
Scholarly communication0.0030.002
Open science0.0010.003
Research integrity0.0010.001
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 head0.072
GPT teacher head0.302
Teacher spread0.229 · 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

Citations161
Published2011
Admission routes2
Has abstractyes

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