Blinders of extreme heat adaptation: uneven urban development and the reproduction of vulnerabilities
Bibliographic record
Abstract
Despite its deadly nature, extreme heat has received fragmented and scattered responses in cities, often overlooking the crucial social and equity components. Dominant adaptation approaches have paid little attention to chronic socio-economic vulnerabilities to heat stress, resulting in a lack of strategic planning to address them. Building upon critical urban studies and adaptation scholarship, this article examines how the dynamics of urban climate adaptation in the Global North have sidestepped the root causes of heat vulnerability and their (re)production in past, present and future practices of uneven urban development and planning under austerity. We investigate this empirically in attending to the framing of adaptation, the instruments used and the biases they introduce in Montreal (Canada), as well the perception from planners and community groups regarding their agency in responding to extreme heat. We contribute to the literature in analysing how the urban governance of adaptation in urban planning tends to silence the social production of vulnerabilities by three intersecting processes: the biases of instruments used, the unacknowledged legacies of uneven urban development, and the lacking recognition and support for community organisations caring practices.
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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 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.009 | 0.057 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.001 | 0.013 |
| Research integrity | 0.001 | 0.002 |
| 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".