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Record W2941494828

Psychometric properties of the Spanish version of the Referee Self-Efficacy Scale (REFS)

2019· article· en· W2941494828 on OpenAlexaff
Félix Guillén García, Deborah L. Feltz, Todd A. Gilson, Lori Dithurbide

Bibliographic record

VenueAcceda (Universidad de Las Palmas de Gran Canaria) · 2019
Typearticle
Languageen
FieldPsychology
TopicMotivation and Self-Concept in Sports
Canadian institutionsDalhousie University
Fundersnot available
KeywordsCronbach's alphaPsychologyReliability (semiconductor)PsychometricsScale (ratio)Structural equation modelingSample (material)Social psychologyStatisticsClinical psychologyMathematicsPhysicsThermodynamics
DOInot available

Abstract

fetched live from OpenAlex

The purpose of the present study was to translate into Spanish and analyze the reliability and validity of the Referee Self-Efficacy Scale (REFS). The English version of the 13-item REFS, which was created by Myers, Feltz, Guillen and Dithurbide (2012), was analyzed with data obtained from a sample of 490 Spanish referees representing three different team sports. The reliability was evaluated using Cronbach's alpha and test-retest. The validity was assessed through Confirmatory Factor Analyses and the correlations between the REFS subscales. The reliability estimated with Cronbach's alpha was (alpha =.85) which was acceptable for the 13-item REFS as well as its subscales ranged .72 to .80. The Confirmatory Factor Analyses were performed which supported a 13-item REFS, assessing the four hypothesized dimensions of self-efficacy: game knowledge, decision-making, pressure, and communication. The overall fit of the model was good showing value of .95 for AGFI, .97 for GFI and NNFI, .98 for CFI, and .04 for RMSEA. In conclusion, this version shows good properties in terms of its dimensionality and internal consistency. Guidelines are also provided for future research on its validity as a measure of self-efficacy in a sample of Spanish officials.

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 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 score0.045
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
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 head0.022
GPT teacher head0.255
Teacher spread0.233 · 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 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

Citations4
Published2019
Admission routes1
Has abstractyes

Explore more

Same venueAcceda (Universidad de Las Palmas de Gran Canaria)Same topicMotivation and Self-Concept in SportsFrench-language works237,207