Toward a Cross-Disciplinary Analysis of Group Development Models: Intersecting Organizational Studies with Applied Sport Psychology
Bibliographic record
Abstract
Group development research conducted within applied sport psychology shares many conceptual similarities with the field of organizational studies. This thesis investigates how the cross-integration of two group development models referenced from separate fields of study can converge to produce a comprehensive analytic model for evaluating group performance. Integrating Tuckman's (1965; Tuckman & Jensen, 1977) successive five stage group development model with Carron's (1982) general conceptual system for cohesiveness in sport teams, this thesis develops an original integrative cross-disciplinary schematic for group development. Guided by a systems approach, the analysis of this model reveals how cross-disciplinary research conducted within these two fields serves to identify mutual benefits, while highlighting the similarities and differences from both group development models. A key contribution of this study is the consideration of opportunities for enhancing current knowledge, and the harmonization of strategic and humanistic approaches to management. The conclusions drawn from this thesis raise significant questions about the potential yielded through the adoption of theoretical applications from applied sport psychology to an organizational context.
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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 | 0.025 | 0.030 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.009 | 0.008 |
| Science and technology studies | 0.003 | 0.015 |
| Scholarly communication | 0.013 | 0.010 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.001 | 0.003 |
| 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".