From the Ground Up: Critical Reflections About Co-Constructing A New Non-Profit Sector Undergraduate Certificate
Bibliographic record
Abstract
Community-university engagement is a growing field and takes many different forms. We explain and reflect critically on a community-university developmental process that we created to design a new non-profit studies undergraduate certificate. A steering group comprising students, non-profit organizations (NPOs), and faculty guided our process. We adopted a community-based, emergent, multi-tactic process that went from testing an idea, to collectively designing and co-constructing the certificate to building momentum to operationalize it, over an 18-month period. Our strategy was based on the convergence of three main bodies of literature—community-engaged scholarship, citizen participation, and naturalistic inquiry—and included seven tactics: community-university dialogues, e-communication, interactive booths in public places, presentations and learning circles, student research projects, student and NPO surveys, and pilot-testing undergraduate courses. The outcomes of our process revealed strong community support for a new certificate, which was then co-constructed and later approved by the University Senate. Today, five years later, we reflect on the ebb and flow of our process, in particular: emergent design challenges, the space-in-between, community/university black boxes, ownership, and facilitation work. This exploration contributes to the knowledge base on co-construction processes.
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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 | 0.742 | 0.595 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.684 | 0.001 |
| Scholarly communication | 0.005 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.000 | 0.651 |
| 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".