U.S. cities’ integration and evaluation of equity considerations into climate action plans
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract While cities in the United States play an active role developing and implementing climate policy, urban centers are often sites of socio-spatial inequity. Thus, we explore how cities grapple with these inequities in their Climate Action Plans (CAPs). While CAPs can empower cities to engage in equitable planning practices that prioritize marginalized communities, little empirical research examines how equity goals are measured and evaluated. We find that among large U.S. cities with CAPs, less than one third include measurable indicators to evaluate progress towards achieving equity goals. Across climate adaptation and mitigation planning, nineteen cities consider equity goals as they relate to ten thematic areas, six outcomes, and five dimensions of equity. We suggest ways forward for cities to develop, implement, and measure a diverse and holistic set of equity indicators to use in their climate planning efforts and beyond.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.006 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it