The Incubation Model of University-Community Relationships: A Case Study in Creating New Programs, New Knowledge, and New Fields of Practice
Bibliographic record
Abstract
Universities in Canada and elsewhere are recognizing the importance of being more engaged with their communities. Indeed, the president of the University of Alberta made engaging with external communities one of the cornerstones of her vision for the institution. So how are universities meeting this challenge? In his book, Managing Civic and Community Engagement, David Watson laments the dearth of scholarly attention paid to the practice of civic engagement by universities (Watson, 2007). In this article, I discuss the university community partnership between the Faculty of Extension, University of Alberta, and the Legal Resource Centre of Alberta Ltd., which began more than 30 years ago. Both a success story and a cautionary tale, the case study helps to define a little-discussed model of university community engagement and to expose some of its strengths and limitations. It is useful in advancing both the theory and the practice of university-community engagement.
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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 | 0.010 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.040 | 0.026 |
| Scholarly communication | 0.012 | 0.013 |
| Open science | 0.003 | 0.013 |
| Research integrity | 0.006 | 0.007 |
| Insufficient payload (model declined to judge) | 0.003 | 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".