Bibliographic record
Abstract
Small cities often have unique limitations and opportunities related to sustainability. One avenue of addressing these challenges is through fostering greater community engagement and connection. This chapter investigates sustainability in Camrose, Alberta, a small Canadian city, by presenting two case studies that showcase the role of a postsecondary institution in delivering sustainability education through community-engaged research to promote local greenspace and wildlife stewardship goals. The first project investigates the role of urban forests in contributing toward sustainable and resilient urban centers by working with community members to measure and report ecosystem benefits from both public and private trees. The second project seeks to conserve the Purple Martin, a colonial and aerial insectivorous bird that relies on human-provided nest boxes. The project involves annual monitoring, landlord recruitment, environmental education, student-led research, partnerships across North America, and an annual Purple Martin festival. Students and community members engage in landlord mentoring, citizen science, and a variety of stewardship practices. Both projects highlight the importance of local partnerships, telling engaging and experiential stories, and the value of interdisciplinary perspectives when working toward long-term urban sustainability that envisions cities as places for nature.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.004 | 0.004 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.017 | 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".