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Record W3097010126 · doi:10.1080/23311886.2020.1844927

The multicollinearity between youth sport environment questionnaire and team assessment diagnostic measurement in sport settings

2020· article· en· W3097010126 on OpenAlex
Yuto Yasuda, David M. Paskevich

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

VenueCogent Social Sciences · 2020
Typearticle
Languageen
FieldPsychology
TopicTeam Dynamics and Performance
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsMulticollinearityPsychologyApplied psychologyTeam sportCohesion (chemistry)Mental modelSocial psychologyIndustrial and organizational psychologyAthletesRegression analysisComputer scienceMedicine

Abstract

fetched live from OpenAlex

With interdisciplinary effort, shared mental model from organizational psychology has been introduced in recent years. Even though the concept of shared mental model is established in sport psychology, it still has an operational problem. That is, different researchers have used different measures. The purpose of this research was to examine the multicollinearity between the Team Assessment Diagnostic Measurement (TADM) questionnaire, which measures shared mental model, and the Youth Sport Environment Questionnaire (YSEQ), which measures group cohesion. The participants were competitive youth soccer players. TADM and YSEQ were measured at the end of the season. Findings showed that the TADM was highly correlated with task cohesion (r = 0.81) even though VIF did not indicate multicollinearity. Therefore, TADM should be used with caution. Also, based on the definition of the shared mental model, Pathfinder or card sorting is recommended rather than using questionnaires.

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)0.002
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 score0.008
Threshold uncertainty score0.521

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.061
GPT teacher head0.330
Teacher spread0.270 · 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