Development and validation of an inventory to assess conflict in sport teams: the Group Conflict Questionnaire
Bibliographic record
Abstract
Abstract The purpose of the study was to develop and validate a conceptually and psychometrically sound conflict questionnaire for sport. The development process involved 3 phases: (a) a qualitative phase, (b) a content and factorial validity phase and (c) a construct validity phase. A total of 50 items were generated and sent to 6 experts to determine content validity. Through this process, 25 items were retained and administered to a sample of athletes (n = 437) to determine factorial validity. Based on these results, a second sample (n = 305) was administered the 14-item version of the Group Conflict Questionnaire along with the Group Environment Questionnaire, the Athlete Satisfaction Questionnaire and the Passion Scale to test convergent, discriminant and known-group difference validity. Cross-validation from both samples via confirmatory factor analysis yielded moderate-to-acceptable model fit, thus supporting factorial validity for the 14-item version. Additionally, initial support for convergent validity and known-group difference validity and partial support for discriminant validity were found. A sport-specific conflict questionnaire is now available for researchers to utilise. Results and research implications are discussed.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.018 | 0.023 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".