The climate change adaptation readiness of co‐operative housing in <scp>Nova Scotia</scp>, <scp>Canada</scp>
Bibliographic record
Abstract
Abstract Climate adaptation policy in Canada is emerging in the context of another major challenge: the diminishing availability of affordable housing. Housing is a well‐known driver of social vulnerability to environmental risks, so as governments respond to these challenges, it will be essential to understand how housing is being situated within adaptation, particularly with respect to differences in housing tenure and how decisions around equity and social vulnerability are factored into planning and policy processes. This research examines how adaptation plans and policies in Nova Scotia are addressing the needs of the non‐profit co‐operative housing sector and assesses the adaptation readiness of housing co‐operatives in the province. Two methods are employed: a systematic content analysis of municipal and provincial climate policy documents, and interviews with key informants across the co‐operative housing sector and government agencies. Using a modified adaptation readiness framework, we consider the potential for co‐operative adaptation and complimentary public policy to address vulnerability at the intersection of housing and climate change. Findings indicate that non‐market forms of tenure have been largely neglected by adaptation planners and state policymakers. Several barriers which contribute to a low level of adaptation readiness for co‐ops are highlighted, notably a lack of usable science and funding to facilitate adaptation. Characteristics such as affordability and a propensity for collective action position housing co‐ops to be agents of equitable and systemic adaptation, but this potential will only be realized in Canada if key barriers are overcome through targeted governmental rt for non‐profit housing organizations.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".