A Qualitative Study of Urban Mini-forest Initiation Within the Context of Canada’s Changing Climate
Bibliographic record
Abstract
This qualitative research, employing thematic analysis, provides insights into the factors that lead individuals to establish urban mini-forests using the Miyawaki method and whether they consider the impacts of climate change. Findings revealed that prior environmental experience, concerns about biodiversity loss, anticipation of outcomes, opportunities for community engagement, and community empowerment were common factors. For some, opportunities for reconciliation with Indigenous People were identified as a fundamental factor in initiating their project. The rapid increase in biodiversity, the transformative experience of forest stewardship, and the ability to develop forests throughout the community were compelling attributes of the mini-forest. The anticipated ecosystem services that mitigate various impacts of climate change, particularly concerning protection from extreme heat, were identified as factors, as was the opportunity to inspire future climate action. Additionally, participants had considered at least one climate impact affecting the long-term resilience of the mini-forests they planted, and for some, this was a motivating factor.
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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 | 0.008 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.026 | 0.014 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 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".