Exploring Mentoring Functions Within the Sport Management Academy: Perspectives of Mentors and Protégés
Bibliographic record
Abstract
Mentoring has typically been studied in business environments, with fewer studies focusing on academic contexts and even fewer in the field of sport management. This study examined the mentoring relationships, and specifically the mentoring functions that occurred among sport management doctoral dissertation advisors (mentors) and their doctoral students (protégés). Semistructured telephone interviews were conducted with 13 individuals. Participants collectively described examples of all of Kram’s (1988) mentoring functions, with coaching, counseling, and exposure and visibility cited most frequently. Fewer instances of protection and direct sponsorship were mentioned, although there was evidence of considerable indirect sponsorship. Protégés provided more examples of role modeling as compared with their mentors, and the entire process of completing a doctoral degree can be viewed as a challenging assignment. A discussion of these findings within the context of the relevant previous academic literature and suggestions for future research are also provided.
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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 | 0.017 | 0.019 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.017 | 0.012 |
| Scholarly communication | 0.010 | 0.005 |
| Open science | 0.002 | 0.010 |
| Research integrity | 0.003 | 0.006 |
| 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".