Assessing the Outcomes of Community-University Engagement Networks in a Canadian Context
Bibliographic record
Abstract
Inter-organizational networks are proliferating as a tool for community-university engagement (CUE). Focusing on three Canadian inter-organizational networks that bring communities and universities together, Community Based Research Canada (CBRC), the Pacific Housing Research Network (PHRN) and the Indigenous Child Well-being Research Network, this paper identifies key criteria for assessing these networks’ outcomes and highlights factors that contribute to these networks’ challenges and successes. This work is part of a growing body of scholarship seeking to better understand the role and contribution of networks in society and more specifically how the outcomes of these engagements might benefit and enhance collaborative research partnerships between civil society and higher education institutions. The results illuminate lessons learned from each of these three networks and their members. These findings inform broader research into community-university engagement networks and illustrate how these types of engagements can help build a stronger knowledge democracy in Canada and elsewhere.
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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 | 0.910 | 0.494 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.669 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.000 | 0.681 |
| 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; both teacher heads agree on what is shown here.
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".