The Influence of Perception on Student-Athletes’ Motivation and Relationship with Coaches — Student-Athlete’s Perception
Bibliographic record
Abstract
The present study was created to better understand the influence of coaches on student-athlete’s motivation. The goal of this study was to determine how the student-athlete’s motivation level is affected by the type of relationship between the coach and the student-athlete in comparison to non-athletes. The hypothesis is that athelete status (student-athlete or non-athlete) impacts perceived motivation when faced with a particular coach (“supportive” or “non-supportive”). The approach was to conduct a two-group experiment providing participants with two different scenarios. One of two scenarios was presented to manipulate the perception of a coach. Forty participants participated in this study. The recruited participants were either student- athletes or non-athletes. All participants were recruited from a Historically Black Institution; 58% were male, 42% female. The results indicate that the type of coach will differently impact a student-athlete’s motivation than a non-athlete. More specifically, both student-athletes and non-athletes perceive a “supportive” coach to be more supportive; however student-athletes perceive “non-supportive” coaches to be less encouraging than non-athletes. The findings from this study suggest that student-athletes and non- athletes perceive a non-supportive coach differently.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.005 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".