Work Motivation and Job Satisfaction of Sport Management Faculty Members
Bibliographic record
Abstract
Informed by self-determination theory, this study builds on previous research to examine the work motivation and job satisfaction levels of sport management faculty members, as well as any relationship between their job satisfaction levels and work motivations. A total of 193 sport management faculty responded to a survey consisting of the Job Satisfaction Survey and the Motivation at Work Scale. Results revealed that regarding job satisfaction, faculty members were more satisfied with work itself, supervision, and coworkers and were less satisfied with pay, operating procedures, and reward. While participating sport management faculty had the highest mean in intrinsic motivation, job satisfaction also was significantly positively correlated with identified regulation. Male faculty showed significantly greater overall job satisfaction than female faculty, but gender did not affect work motivation factors. Finally, results revealed no significant differences among tenured, tenure-track, and non-tenure-track faculty in motivation levels, but after controlling for motivation, job satisfaction levels of non-tenure-track faculty were significantly less than those of tenured and tenure-track faculty. Results of this study can assist higher education administrators (i.e., department chairs, deans, provosts) to better understand that this population is highly intrinsically motivated and identifies deeply with their work. Administrators should work diligently to preserve autonomy, a factor that appears to lead to greater levels of motivation and job satisfaction.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".