Community-university engagement in Canada : boundary spanner practice
Bibliographic record
Abstract
Historically, public universities have played a role in the development of society through the creation and sharing of knowledge and upholding democratic values. In recent decades, governments and the public have looked to universities to help drive economic prosperity and address the complex issues plaguing society (Benneworth, 2016; Fisher et al., 2006). This has been accompanied by declining base funding from provincial governments in Canada. The result has been an expansion of universities’ traditional purposes and roles to include their engagement with social and economic communities outside the university while also seeking ways to increase revenues. This research examines the practice of community-university engagement (CUE) in Canada by identifying existing tensions and contributions of CUE practitioners identified as “boundary spanners.” I took a qualitative research approach to this study, utilizing three sources of data: interviews with boundary spanners across Canada, reflective essays outlining their path to their positions, and key university documents articulating their values and place in society. My analysis involved a comparison of values, attitudes, and beliefs between boundary spanners and their institutions focusing on the purposes and roles of public universities in society, CUE practice, and the utility of formal evaluation of CUE practice. I draw upon the institutional logics perspective, as well as literature on boundary spanners and CUE, to understand and articulate the factors and dynamics that characterize their environment of practice. This research uncovers points of tension regarding the role of public universities, the place of CUE practice, and the ways in which formal evaluation responds to calls for accountability. Understanding the complexity and dynamics of CUE practice contributes to understanding institutional processes and to the creation of new imaginaries for higher education.
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 | 0.002 | 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 | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 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".