Students as Community-Engaged Researchers in Responding to Crises: Insights From the Embedded Thesis Model
Bibliographic record
Abstract
The Community-Campus Responses to Crisis project, led by Community Campus Engage Canada and the University of Regina, explores how postsecondary institutions can best support community initiatives that address social impacts of climate change. The project aims to strengthen universities’ capacity to support community initiatives and build a pan-national knowledge-sharing network that centralizes effective crisis response strategies. The project involves case studies at Canadian institutions, two of which—the University of Regina and Acadia University—focused on community engagement efforts with homelessness-related organizations. These two case studies used an embedded thesis model that allows graduate students to lead the community engagement process, determine the direction of the research, and integrate the study into their thesis. This reflection explores the experiences of two master’s students (Adhika, University of Regina, and Shasta, Acadia University) who participated in the embedded thesis model.
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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 | 0.019 | 0.020 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.017 | 0.033 |
| Scholarly communication | 0.021 | 0.012 |
| Open science | 0.004 | 0.019 |
| Research integrity | 0.005 | 0.008 |
| Insufficient payload (model declined to judge) | 0.004 | 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".