Adaptation for whom? Assessing Environmental Equity within British Columbia’s Climate Change Adaptation Policies
Bibliographic record
Abstract
Climate change is expected to disproportionately affect social groups and geographical regions made vulnerable by persistent social inequalities understood in terms of race, Indigenous status, age, gender, and disability (Anguelovski et al., 2016; BCCDC, 2020; Leonard, 2021; Solecki & Friedman, 2021; Vadeboncoeur, 2016). Globally, research on climate justice has shed light on how adaptation policies disproportionately impact vulnerable communities. In Canada, research has begun to explore adaptation responses to flooding and rising sea levels in New Brunswick (Chouinard et al., 2020), British Columbia (Birchall & Bonnett, 2021; Oulahen et al., 2918) and Quebec (Friesinger & Bernatchez, 2010; Lapointe et al., 2020). However, an explicit analysis of Canadian adaptation policies in terms of environmental justice, including its distributional, procedural, corrective, and social justice dimensions (Kuehn, 2020) is yet to be conducted. Recent climate-driven crises in British Columbia such as wildfires, flash flooding, and collapse of salmon fisheries bring urgency to developing climate adaptation policies and for considering the inequities of climate change. Coastal communities in British Columbia face an unavoidable challenge as sea levels continue rise. With 80% of British Columbia’s population residing within 5km of the coast and near sea level (BCCDC, 2020, pg.71), efficient and holistic adaptation protocols are needed. Through a discursive policy analysis (DPA) and semi-structured interviews (n=15) with key informants, this thesis examined how government climate adaptation strategies and plans for British Columbia’s west coast communities conceptualize and address equity concerns. The findings revealed inconsistent and vague perceptions of environmental equity within adaptation strategies and plans; lack of monitoring of initiatives and efforts being made across government; the fragmenting of adaptation efforts from complementary work; and the lack of awareness of roles and responsibilities within and across jurisdictions. Beyond the urgency for vulnerable groups, addressing equity concerns in adaptation strategies and practices could offer co-benefits in improving the efficiency of broader government operations. This study provides a foundation for future research that explores how multi-level government systems can deepen the conceptualization of environmental equity and prioritize addressing equity concerns within adaptation strategies and plans. The integration of such principles is vital to ensure a just and sustainable response to climate change impacts in British Columbia and beyond.
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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 | 0.006 | 0.020 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.006 |
| Science and technology studies | 0.010 | 0.003 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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".