Varsity Sports in Canada from the student-athlete's point of view
Bibliographic record
Abstract
Title: Varsity sport in Canada in the perspective of foreign and domestic student- athletes Objectives: The aim of this thesis is to analyze the system of varsity sport in Canada, to identify its problematic areas from the perspective of student-athletes and to make suggestions for its improvements. Methods: In this thesis the method of descriptive analysis was used. The information on varsity sport in Canada was mainly collected by exploring the documents of the governing body for varsity sports, the Canadian University Sport. The second method used was an interview. This was used in order to get additional information on varsity sports and to get suggestions and ideas from student-athletes. Results: Several problematic areas in varsity sports in Canada were identified: athletic financial awards, funding of the teams, several eligibility rules (number of years of eligibility, academic requirements, athletes' age limit), non-Canadian student-athletes, limited number of varsity sports, and limited opportunities for the athletes to continue their sport after graduation. Suggestions were made in order to improve these areas. Keywords: varsity sport, student-athlete, eligibility rules, Sport Canada, Canadian Sport System, Canadian University Sport
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.008 |
| Science and technology studies | 0.016 | 0.006 |
| Scholarly communication | 0.006 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".