Unveiling inequity: Community perspectives on climate action planning in Ontario cities
Bibliographic record
Abstract
Researchers have repeatedly demonstrated that climate change disproportionately affects equity-deserving groups and that climate policies do not necessarily reduce disparities. Planners and policymakers need to understand the needs of underserved communities to design responsive and equitable solutions. This study explores the self-identified needs and priorities of equity-deserving groups in three cities in Ontario, Canada, to develop a set of recommendations for more equitable climate action planning based on input from equity-deserving group representatives. Findings also contribute to clarifying whether universal criteria for assessing equity in climate action planning can reliably be used to compare progress across cities. • Equity challenges are cross-cutting but populations of concern are location-specific. • Equity-deserving groups report superficial forms of community engagement. • Policymakers need a better understanding of intersectionality. • There is low awareness of climate action among advocacy organizations. • Researchers need to make the connection between climate change and equity explicit.
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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 | 0.006 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.041 | 0.018 |
| Scholarly communication | 0.008 | 0.003 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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".