Distributive Justice in Intercollegiate Athletics: Perceptions of Athletic Directors and Athletic Board Chairs
Bibliographic record
Abstract
Hums and Chelladurai (1994b) found NCAA coaches and administrators believed distributing resources based on equality and need was more just than distributing them based on equity (i.e., contribution). However, Mahony and Pastore (1998) found actual distributions, particularly at the NCAA Division I level, appear to be based on equity over equality and need. The main purpose of the current study was to determine why the findings in these studies differed. The authors of the current study reexamined the principles from Hums and Chelladurai's (1994b) study, while making significant changes in the sample examined, asking new questions, and adding more distribution options. The results indicated that need based principles were considered to be the most fair, but there was less support for equality than in prior research. In addition, the current study found differences between Division I and Division III administrators with regards to some equality and equity based principles.
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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 | 0.009 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.006 | 0.005 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| 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".