“In the Arena”: Reflections on Critical Public Engagements on College Sport
Bibliographic record
Abstract
In this paper, we reflect on the challenges, opportunities, motives, imperatives, and strategies of engagement associated with public scholarship about college athletics. Public scholarship has become a trendy topic across the academy as universities increasingly push academic workers to boost institutional brands suffering from chronic underfunding through highly visible engagement in the public sphere. We argue that although public scholarship is a vital part of academic work, principal imperatives driving this form of labor should be political/ethical rather than promotional. It is therefore not enough for academic workers to simply generate data for academic audiences, as without public dissemination, the impact is inherently limited and exclusionary. While public engagement is a necessary and important part of our work, it is fraught with the contradictions inherent to the critique of the same institutions that demand that engagement in the first place, as well as the associated collateral intellectual and personal damage that comes from wading into public debate. Through an autoethnographical account of our personal experiences, as scholars intervening in public discourse around the rights of campus athletic workers and our own encounter with ESPN college basketball personality and former college coach Dan Dakich, we will trace some institutional and personal strategies for educators to create protective measures, build community, and mobilize solidarity against real or perceived harassment. Such tactics aim to help scholars produce public work that genuinely contributes to societal conversations, challenges prevailing misconceptions, and centers the voices of minoritized, abused, and exploited athletes above all.
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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 | 0.036 | 0.057 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.005 | 0.004 |
| Science and technology studies | 0.061 | 0.161 |
| Scholarly communication | 0.038 | 0.029 |
| Open science | 0.007 | 0.035 |
| Research integrity | 0.018 | 0.037 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".