Factors Impeding Academic Performance in Canadian Student Athletes
Bibliographic record
Abstract
This study examines the various impediments to academic performance of Canadian university student-athletes compared to non-athletes. Student-athletes face unique challenges as they strive to balance the demands of both their athletic and academic commitments. Previous research indicates that several factors including anxiety (Petrie et al., 1995), alcohol and substance use (Leichliter et al., 1998), gambling (Huang et al., 2007), extracurricular activities (Adler 1985; Edwards & Froehle 2023), social experiences and relationships (Sedlacek et al.,1992), and sleep (Turner et al., 2021), can influence the academic performance of student-athletes. The current study used the 2019 Canadian Reference Group of the ACHA’s National College Health Assessment database. Varsity athletes (n = 2004) and non-athletes (n = 45,482) reported whether they perceived the following variables to be “impediments to their academic performance”: alcohol use, anxiety, depression, gambling, relationship difficulties, sleep difficulties, and stress. Chi-square analyses showed that student-athletes were significantly more likely than non-athletes to report alcohol use, gambling difficulties, and relationship difficulties as impediments, and were less likely than non-athletes to note anxiety, depression, and stress as impediments. There was no difference between the two groups with respect to sleep. Recent studies have proved the effectiveness of alcohol-related interventions for athletes (Cimini et al., 2014). However, there is a lack of research focused on gambling and relationship interventions specifically tailored to student-athletes. The findings of this study could aid in the development of applied interventions specific to student-athletes regarding issues of gambling, alcohol use and relationship difficulties.
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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 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".