Role satisfaction: A proposed conceptualization for sport
Bibliographic record
Abstract
Fostering positive role perceptions is an important process related to individual and team success (Carron, Hausenblas, & Eys, 2005). To date, research concerning role perceptions in sport has focused primarily on cognitive aspects of roles and to a much lesser extent on role-related affect. Role satisfaction is defined as a pleasurable emotional state resulting from the perception of one's role as fulfilling or allowing the fulfillment of one's important role values (Locke, 1976). In sport, preliminary research has demonstrated that role satisfaction is positively linked to other role elements (e.g., role efficacy, role clarity) as well as team cohesion (Bray, 1998). However, researchers have noted the absence of a comprehensive conceptualization of role satisfaction, as well as the lack of a psychometrically sound measurement tool. The purpose of this communication is to propose a multi-dimensional model of role satisfaction in sport, developed through a comprehensive review of role satisfaction literature in both sport and organizational psychology. The proposed model contains seven dimensions: satisfaction with (a) skill utilization, (b) personal role significance, (c) team role significance, (d) autonomy, (e) feedback, (f) recognition, and (g) a general dimension of overall role satisfaction. Each of these dimensions is posited to be an essential component of understanding an athlete's perception of satisfaction with his/her role. Potential implications and future directions will be 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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.006 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".