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Record W1796154260 · doi:10.7352/ijsp.2014.45.121

Collective efficacy or team outcome confidence? Development and validation of the Observational Collective Efficacy Scale for Sports (OCESS)

2014· article· en· W1796154260 on OpenAlexaff
Katrien Fransen, Jens Kleinert, Lori Dithurbide, Norbert Vanbeselaere, Filip Boen

Bibliographic record

VenueLirias (KU Leuven) · 2014
Typearticle
Languageen
FieldPsychology
TopicMotivation and Self-Concept in Sports
Canadian institutionsDalhousie University
FundersVlaamse regeringFonds Wetenschappelijk Onderzoek
KeywordsPsychologyObservational studyOutcome (game theory)Scale (ratio)Collective efficacyApplied psychologySocial psychologyStatistics

Abstract

fetched live from OpenAlex

Although collective efficacy has been demonstrated to be an important precursor of team performance, there remains some ambiguity concerning its assessment. Therefore, the main aim of the present study was to test the validity of previous collective efficacy measures. An online survey was completed by 4,451 Flemish players and coaches from nine different team sports. The results revealed two distinct and reliable scales; process-oriented collective efficacy (i.e., the confidence in the team’s skills to accomplish processes that could lead to successes) and outcome-oriented team confidence (i.e., the confidence in the team’s ability to obtain a goal or win a game). Furthermore, we established the validity of a 5-item Observational Collective Efficacy Scale for Sports (OCESS) as short measure of process-oriented collective efficacy. Because the OCESS only includes observable behaviors, this scale has the potential to be a starting point for the development of a continuous in-game measure of collective efficacy.

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)0.001
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 score0.091
Threshold uncertainty score0.792

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
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 head0.080
GPT teacher head0.337
Teacher spread0.256 · 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

Citations24
Published2014
Admission routes1
Has abstractyes

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