(Mis-)belonging to the climate-resilient city: Making place in multi-risk communities of racialized urban America
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
Through climate adaptation planning cities are transforming places and relations, most recently via green climate resilient infrastructure (GRI). Yet, GRI's incorporation into existing, racialized infrastructure systems of urban development, regeneration and finance has raised questions about the socio-cultural impacts and justice dimensions of recent directions in climate adaptation planning and urbanism. While critical scholars highlight the exclusion of historically marginalized residents, this paper's analysis of the impacts of GRI-driven planning for sense of belonging reveals a complex and multi-faceted experience of gentrification and displacement in the racialized, settler colonial city. Drawing on insights from civic actors about their lived experience of green and climate resilient projects in Boston, Massachusetts, we develop a novel understanding of belonging, which entails degrees of (mis)belonging. Our analysis uncovers three pathways by which climate urbanism shapes belonging into various alienated, subordinated, assimilated and emancipated forms, and reveals the kinds of political subjects and socio-cultural relations that emerge from the lived experience of climate adaptation projects. More broadly, this study sheds light on how less visible placemaking practices and alternative modes of addressing socio-climate vulnerability contribute to climate justice and injustice dynamics.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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