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Teamwork and Performance

2012· book-chapter· en· W310935377 on OpenAlexaff
Albert V. Carron, Luc J. Martin, Todd M. Loughead

Bibliographic record

VenueOxford University Press eBooks · 2012
Typebook-chapter
Languageen
FieldPsychology
TopicSport Psychology and Performance
Canadian institutionsUniversity of LethbridgeUniversity of WindsorWestern University
Fundersnot available
KeywordsTeamworkPsychological interventionCohesion (chemistry)Perspective (graphical)PsychologyApplied psychologyKnowledge managementPublic relationsManagement scienceEngineeringPolitical scienceComputer scienceArtificial intelligence

Abstract

fetched live from OpenAlex

Abstract This chapter focuses on the nature of teamwork as perceived from the perspective of sport, industrial, and military psychology. First, commonly held definitions for a team in each of these three areas are introduced. This is followed by a discussion of how teamwork is conceptualized. Important correlates of teamwork and performance have been identified within the three areas, including cooperation, role relationships, leadership, and cohesion. We provide a framework to facilitate our discussion of these correlates. Then, research carried out in sport, industry, and the military pertaining to each correlate is reviewed. Because of the perceived importance of teamwork, numerous team building interventions have been undertaken to enhance it. The types of interventions and their relative effectiveness are outlined. Finally, future directions are proposed.

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 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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.981
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 integrity0.0010.001
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 head0.031
GPT teacher head0.237
Teacher spread0.205 · 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 teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreOther

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

Citations24
Published2012
Admission routes1
Has abstractyes

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