Transforming planning and policy making processes at the intersections of climate, equity, and decolonization challenges
Bibliographic record
Abstract
Cities are facing increasing pressures to address complex challenges of climate change, equity, and reconciliation with Indigenous Peoples as intersecting issues, and innovation into planning and policy-making processes is urgently needed to achieve this. It is no longer good enough to work on these challenges discreetly, or solely within the dominant, western colonial paradigm and practices of governance. There are ongoing harms being caused by climate work that does not embed justice, and there are missed opportunities for synergies across these domains as they have the same systemic root causes. Cities must adapt and transform the processes and practices of planning and policy-making in order to work at these problematic roots. Drawing on an empirical study, this article describes how social innovation, systemic design, and decolonizing practices can shape a different approach to planning and policy-making processes when working at the intersections of climate, equity, and decolonization.
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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 | 0.019 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.009 | 0.047 |
| Scholarly communication | 0.014 | 0.009 |
| Open science | 0.002 | 0.014 |
| Research integrity | 0.002 | 0.005 |
| 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".