The Impact of a Community-University Collaboration: Opening the “Black Box”
Bibliographic record
Abstract
ABSTRACTWithin the Social Economy, universities are working with community representatives to undertake research projects, service learning opportunities, and increasingly, academic program development, all with the objective of addressing social challenges. As many are quick to caution, the community is actually a sum of its various actors, interests, accountabilities and needs, which university staff and faculty must work to understand. Like the community, the university is a complex organization with politics, conflicts, tensions, and competing goals and objectives. Within this larger context, these various components, focusing on government, academic and administrative stakeholders, will impact and may even limit aspects of a collaboration between the university and its community partners. Through examination of a case study related to a graduate program, which was collaboratively developed between the university and community representatives, this article will identify and explore those accountabilities and the resulting impact on the collaboration. It will conclude withrecommendations for similar partnerships.RÉSUMÉDans l’économie sociale, les universités travaillent de pair avec des représentants de la communauté pour lancer des projets de recherche, créer des occasions d’apprentissage par le service et, de plus en plus, développer des programmes d’études universitaires; tout cela dans le but de régler des défis sociaux. Beaucoup s’empressent de formuler une mise en garde : la communauté est en réalité la somme des divers acteurs, intérêts, responsabilités et besoins qui la composent, ce que les membres du personnel et les facultés des universités doivent tenter de comprendre par leur travail. Au même titre qu’une communauté, une université est une organisation complexe constituée de politiques, de conflits, de tensions ainsi que d’objectifs concurrents. Dans ce contexte large, ces diverses composantes, en particulier les intervenants gouvernementaux, universitaires et administratifs, auront des conséquences sur la collaboration entre l’université et ses partenaires communautaires, et peuvent même en limiter certains aspects. Cette étude définit et analyse ces responsabilités et leurs conséquences sur la collaboration par le moyen d’une étude de cas liée à un programme d’études supérieures développé grâce à la collaboration de l’université et des représentants de la communauté. L’étude se termine par des recommandations visant des partenariats similaires.
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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 | 0.026 | 0.026 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.033 | 0.030 |
| Scholarly communication | 0.023 | 0.020 |
| Open science | 0.003 | 0.042 |
| Research integrity | 0.006 | 0.005 |
| Insufficient payload (model declined to judge) | 0.021 | 0.002 |
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".