Challenges Faced and Solutions Implemented in Response to the COVID-19 Pandemic among North American College Campus Recreation Staff
Bibliographic record
Abstract
The COVID-19 pandemic has had a significant impact on the operation and availability of campus recreation services at North American colleges and universities. This study examined the challenges faced and solutions implemented by campus recreation departments as a result of the COVID-19 pandemic from the perspective of campus recreation staff from across North America. Institution and staff characteristics along with challenges and solutions were collected from 174 campus recreation department staff via an online survey in November 2020. Qualitative data were analyzed using thematic analyses. As a result of the pandemic, campus recreation departments have experienced challenges regarding finances, staffing, student engagement, and health and safety. To address these challenges, departments have limited facility access and capacity, reduced spending, adjusted staffing levels and responsibilities, transitioned to virtual or modified in-person programming, leveraged intrauniversity collaborations, and implemented new health and safety protocols. Solutions have the potential to help institutions meet the needs of students during the pandemic and beyond. Virtual programming and reservation systems may be especially useful post-pandemic, and lessons learned regarding multi-faceted COVID-19 policy enforcement could help advance compliance with other policies, such as harassment.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 teacher head, 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".