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Record W2169950783 · doi:10.1123/jsep.29.3.395

Item Wording and Internal Consistency of a Measure of Cohesion: The Group Environment Questionnaire

2007· article· en· W2169950783 on OpenAlexaff
Mark Eys, Albert V. Carron, Steven R. Bray, Lawrence R. Brawley

Bibliographic record

VenueJournal of Sport and Exercise Psychology · 2007
Typearticle
Languageen
FieldPsychology
TopicChild and Adolescent Psychosocial and Emotional Development
Canadian institutionsUniversity of SaskatchewanWestern UniversityMcMaster UniversityLaurentian University
Fundersnot available
KeywordsPsychologyAcquiescenceInternal consistencySocial psychologyCronbach's alphaCohesion (chemistry)Reliability (semiconductor)Group cohesivenessApplied psychologyPsychometricsClinical psychology

Abstract

fetched live from OpenAlex

A common practice for counteracting response acquiescence in psychological measures has been to employ both negatively and positively worded items. However, previous research has highlighted that the reliability of measures can be affected by this practice (Spector, 1992). The purpose of the present study was to examine the effect that the presence of negatively worded items has on the internal reliability of the Group Environment Questionnaire (GEQ). Two samples (N = 276) were utilized, and participants were asked to complete the GEQ (original and revised) on separate occasions. Results demonstrated that the revised questionnaire (containing all positively worded items) had significantly higher Cronbach alpha values for three of the four dimensions of the GEQ. Implications, alternatives, and future directions 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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.012
metaresearch head score (Gemma)0.025
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: Methods · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.988
Threshold uncertainty score0.062

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0120.025
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
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 head0.015
GPT teacher head0.273
Teacher spread0.258 · 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 source (direct Gemma or distilled Codex), not a consensus.

Study designObservational
DomainMethods
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

Citations117
Published2007
Admission routes1
Has abstractyes

Explore more

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