A Confirmatory Factor-Analytic and Psychometric Examination of the Team Climate Inventory
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.
Bibliographic record
Abstract
This study examined the factor structure and psychometric properties of the 38-item Team Climate Inventory and the 14-item short version using a sample of 72 four-person teams of management undergraduates in a Canadian university. The confirmatory factor analyses supported the five-factor correlated model that questions the validity of the original four-factor model. The confirmatory factor analyses also supported the short version. Team Climate Inventory scale and subscale scores showed no significant differences when the Team Climate Inventory was administered at two times, separated by 9 weeks, during the team projects. The Team Climate Inventory shows promise as a multidimensional measure of the team climate construct in both student and employee teams. Finally, the short version provides a useful measure when administration time is limited.
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Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 it