A study of institutional origins and change in a Canadian urban commons
Bibliographic record
Abstract
Kenora is a small city located in northwestern Ontario, Canada. The study presented here focuses on Tunnel Island, 300 acres of forested land adjacent to Kenora’s downtown. The island is used and valued by both city residents and members of three nearby Ojibway nations. As a multiple-use, common-pool resource accessed by different groups for a range of non-extractive activities, the site has become an experiment in multicultural commons governance, and presents an excellent opportunity to examine the origins and development of institutions for managing collective environmental resources in an urban setting. Using participant observation, internet- and field-based user surveys, and semi-structured interviews, our research finds that grassroots ‘governance’ of the site is emerging through subtle processes of individual and social construction, with the strategies and norms (codes of conduct) employed by users providing relative harmony on the trails, which suggests functioning commons institutions. Nevertheless, values-based and epistemic tensions exist among users, pointing to governance challenges for planned joint management of the site, and specifically the need to develop formal, legitimate, and yet flexible and inclusive arrangements that can operate in conjunction with the social practice of existing users.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.023 | 0.013 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".