Bringing adaptation home: Citizen engagements with climate change at home site scales in Ottawa and Halifax
Bibliographic record
Abstract
Climate change impacts are becoming increasingly evident in cities, generating hazards such as heatwaves and flooding events that may cause discomfort or trauma for residents. Climate change scholars suggest that measures undertaken on private lands provide a significant counterpart to public adaptation initiatives, and increasingly position the home site as an important scale of analysis within climate change research (Bichard & Kazmiercak, 2009; Jeffers, 2014; Pyhala et al., 2016; Wilson et al., 2014). Select scholars have also considered how municipalities may effectively engage with citizens to encourage greater home-based responses to climate-related hazards (Groulx et al., 2014; Hjerpe et al., 2014; Klein, 2014). This thesis explores citizen perspectives of climate change impacts, risk and opportunities for adaptation that are based at the scale of the urban home site in two mid-sized Canadian cities, Ottawa and Halifax. Through a qualitative research approach of discourse analysis, this thesis explores several distinct but related sub-themes: (1) how residents understand local places of climate change impacts and risk; (2) how residents engage with home site natures within a context of emerging ecosystem-based adaptation practices; and (3) how residents conceptualize the residential property in situating responsibility for managing neighbourhood stormwater flows. Within these sub-themes, I argue: (1) that places of significant climate change impacts are frequently conceptualized by residents beyond the home site; (2) that residents hold multiple conceptualizations of local natures, as reducing climate change impacts (through stormwater absorption and home cooling benefits) but also potentially contributing to additional risk (through treefalls during storms) from climate-related hazards; and (3) that ideas of property autonomy and boundaries are enacted in fluid ways by residents, as they situate obligation for neighbourhood stormwater management alternately toward individual self-governing efforts, wider municipal measures on public lands, or neighbouring free-rider private (re)development projects. Building on these key findings, municipal adaptation agencies are advised to assist residents in recognizing climate change impacts at localized scales, communicate recommended ecosystem-based adaptation measures to incorporate diverse values among residents toward home site natures, and address residents' anxieties regarding neighbouring development activities that diminish permeable land area and stormwater management potential across neighbourhoods.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.023 | 0.016 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.002 | 0.005 |
| 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".