Investigating the process by which National Hockey League player development coaches 'develop' athletes
Bibliographic record
Abstract
From grassroots participation to elite competition, athletes' personal development is fundamentally shaped by coaches (Bloom, 2016). Interestingly, whereas an extensive body of literature pertaining to coaching effectiveness exists (Cote & Gilbert, 2009), these efforts seldom extend beyond the head coach. However, an emerging trend in professional sport is the designation of Player Development Coaches (PDC). While this signifies recognition of the importance of properly developing athletes, the processes by which PDC's go about enabling athletes' development are largely unknown. Therefore, the purpose of this study was to explore the perceptions, experiences, roles, and responsibilities of current and former National Hockey League (NHL) PDC's. Semi-structured interviews were conducted with eight NHL PDC's (Mage = 50.5, SD = 9.65), with a combined 57 years of experience (M = 7.13, SD = 7.1). Generally, it was discovered that PDC's worked closely with athletes to oversee their development, which involved frequent meetings/discussions, traveling to evaluate performances, and being available to provide support. The PDC's also described the necessity of establishing trust and ensuring complete transparency with their athletes. Finally, the specific strategies or behaviours implemented to facilitate development were contingent on various outcomes ranging from tangible (e.g., performance objectives) to more process-based (e.g., maturity). Interestingly, the findings indicate that PDC's act in ways that bare similarities to the mentoring process. For instance, the pillars of the mentoring relationship are trust and respect (Bloom, 2013), which were reportedly crucial for PDC's to effectively form bonds with their players, thus allowing greater impact on player development.
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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 | 0.012 | 0.017 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.006 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| 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".