University-Community Engagement from the Perspective of the University Populace
Bibliographic record
Abstract
Researchers have long supported increased engagement between institutions of higher learning and the communities that exist beyond campuses. It has been suggested that universities, especially metropolitan core ones, can benefit from making concerted efforts to engage with surrounding communities in meaningful ways. Examining the efforts universities make to better engage with the community will help to inform future practice and hopefully lead to greater success and prevalence of university-community engagement. To that end, this study examined university-community engagement from the perspective of various constituencies that make up a university’s populace (e.g., students, faculty). Specifically, using a descriptive exploratory case study design, this research examined students, faculty, staff, and administrators’ perceptions regarding university-community engagement and awareness of community learning programs at one Canadian university, a decade after a university wide community engagement policy was instituted. Data was collected using an online survey which was completed by a self-selecting sample of participants from the university populace. The results expand on existing literature by providing perspective from the internal university populace regarding university-community engagement efforts. Furthermore, the study results provide insight into the awareness of and support for university-community engagement efforts among various university constituencies.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.013 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".