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Record W2073022447 · doi:10.1177/104649640103200101

Team Cohesion and Individual Productivity

2001· article· en· W2073022447 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueSmall Group Research · 2001
Typearticle
Languageen
FieldPsychology
TopicMotivation and Self-Concept in Sports
Canadian institutionsWestern University
Fundersnot available
KeywordsCohesion (chemistry)IdentifiabilityPsychologyNorm (philosophy)Social psychologyFactorialProductivityEconometricsStatisticsMathematicsEconomicsPolitical scienceChemistry

Abstract

fetched live from OpenAlex

This study investigated the potential moderating effects of productivity norms and identifiability of effort on the cohesion-performance relationship in team sports. The design was a 2 (high cohesion, low cohesion)× 2 (high productivity norm, low productivity norm)× 2 (high identifiability of an individual’s effort, low identifiability of an individual’s effort) factorial. Each participant (n = 324) read one of eight scenarios, with cohesion, norms, and identifiability systematically rotated, and indicated the probability that the individual would train during the off-season. An ANOVA showed a main effect for cohesion, F( 1, 316) = 113.44, p < .0001, and norms, F( 1, 316) = 19.61, p < .0001), and an interaction between cohesion and norms, F( 1, 316) = 7.35, p = .007. The probability of off-season training was significantly higher for the high-cohesion-high-norms scenario than for the high-cohesion-low-norms scenario, with no differences under conditions of low cohesion. Directions for future research are discussed.

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.

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)0.003
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.175
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
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 integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.178
GPT teacher head0.397
Teacher spread0.219 · 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