Bases for Determining Need: Perspectives of Intercollegiate Athletic Directors and Athletic Board Chairs
Bibliographic record
Abstract
The distribution of resources in intercollegiate athletics has been controversial for many years. Prior research indicated various stakeholders believed need-based distributions were fair and were more likely to be used. It was not clear, however, how the stakeholders determined need or which sports had the greatest needs. The results of the current study indicate that athletic administrators believe programs need more resources when they lack resources, have high program costs, or lack adequate resources to be competitively successful. Although these three reasons were each identified by all groups, Division I administrators cited competitive success more often, and Division III administrators cited high program costs more often. The current study also found that football was the sport believed to have the greatest needs at both the NCAA Division I and Division III levels, and men’s sports were generally believed to have greater needs.
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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 | 0.026 | 0.029 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.015 | 0.008 |
| Scholarly communication | 0.010 | 0.004 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.002 | 0.007 |
| 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".