Establishing the Roots of Community Service-Learning in Canada: Advocating for a Community First Approach
Bibliographic record
Abstract
This article explores the roots of the Canadian community service-learning (CSL) movement through a comparative discussion of service-learning in Canada and the United States. The article provides a brief overview of CSL’s historical foundations in both countries, addressing especially how differences in CSL funding infrastructure have distinctly shaped the movement in each country. While national funding bodies and nation-wide institutionalization remain central to CSL in the U.S., Canada’s CSL efforts have predominantly been shaped by the efforts of private foundations and grassroots community agents. This essay analyzes the obstacles and problems currently within Canadian CSL, but also provides recommendations around documentation, sustainability, and the future of CSL in Canada, including the recommendation to maintain a community first approach in Canadian CSL. As it considers how the influence of the United States continues to shape CSL in Canada, and how the two national movements remain distinct from one another, we hope this examination will contribute an historical perspective to scholarship on Canadian CSL and will offer entry points to engage in critical conversations on the emergence of the field.
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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 | 0.011 | 0.019 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.051 | 0.040 |
| Scholarly communication | 0.022 | 0.009 |
| Open science | 0.004 | 0.014 |
| Research integrity | 0.007 | 0.011 |
| Insufficient payload (model declined to judge) | 0.006 | 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; 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".