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Record W1928669598 · doi:10.1111/sms.12235

Collective goals and shared tasks: Interdependence structure and perceptions of individual sport team environments

2014· article· en· W1928669598 on OpenAlexafffund
M. Blair Evans, Mark Eys

Bibliographic record

VenueScandinavian Journal of Medicine and Science in Sports · 2014
Typearticle
Languageen
FieldPsychology
TopicBehavioral Health and Interventions
Canadian institutionsWilfrid Laurier University
FundersCanada Research Chairs
KeywordsInterdependencePerceptionPsychologyCohesion (chemistry)Social psychologyTeam sportAthletesCompetition (biology)Group structurePolitical scienceMedicinePhysical therapy

Abstract

fetched live from OpenAlex

Across two studies, we tested the proposition that interdependence structures (i.e., task interaction among teammates during competition, competition against teammates, presence of a collective outcome) influence interdependence perceptions among teammates as well as perceptions of group cohesion, competitiveness, and satisfaction. Study 1 was a paper-and-pencil survey completed by 210 individual sport athletes from 12 university- and college-level teams. Multiple mediation analyses demonstrated that participants who had to work alongside teammates during competition reported increased interdependence perceptions that were, in turn, associated with increased cohesion and satisfaction as well as decreased competitiveness. There were no differences according to whether participants competed in the same event as all of their teammates or not. Study 2 involved a weekly e-mail survey with 17 university-level individual sport athletes who reported interdependence perceptions on a continual basis over the course of their competitive season. Interdependence perceptions were higher during weeks that were close in time to competitions with a collective group outcome. These studies reveal how interdependence structures shape the group environment and support applied efforts that consider ways to structure teammate interdependencies in ways to optimize group functioning and promote member satisfaction.

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)0.001
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 score0.029
Threshold uncertainty score0.707

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.027
GPT teacher head0.360
Teacher spread0.333 · 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.

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

Citations48
Published2014
Admission routes2
Has abstractyes

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