Framing well-being in a college campus setting
Bibliographic record
Abstract
This investigatory study sought to explore the range and variation of well-being initiatives on a select cross-section of college campuses across the United States and in Canada. This whitepaper seeks to highlight innovative practices that may inspire institutions to consider new ways of promoting well-being for both students and employees. In this whitepaper, we report findings from 10 participating higher education institutions across three major categories: student-serving programs, employee-serving programs, and hybrid programs. The qualitative data collected from key stakeholder interviews and focus groups were analyzed for trends between and across institutions. Importantly, the results of this study are intended to be hypothesis-generating as opposed to hypothesis-testing. In an effort to describe the state of the field with respect to both common and innovative practices the findings have generated additional questions for further research. Several themes emerged from this study: (1) Campuses have not adopted a universally-accepted definition of well-being; (2) While many institutions are using iterations of the wellness wheel and its various dimensions (e.g. physical, emotional, intellectual, social, spiritual, financial) to guide their efforts, there is not a dominant model for structuring or measuring well-being initiatives on campus; (3) There appears to be a systematic shift from use of the term "wellness" to "well-being"; (4) While many institutions are still utilizing traditional health education practices, there appears to be a movement toward more systemic, environmental approaches to well- being, including structural, organizational, and financial strategies, in addition to a range of policy initiatives; (5) There is a range of engagement in well-being initiatives, with significant variance based on institutional philosophy; and (6) Many institutions are designing well-being initiatives that address health disparities-particularly among underrepresented or marginalized populations.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 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) | 0.000 | 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".