Potential adverse equity consequences of coastal climate adaptation interventions in Canada
Bibliographic record
Abstract
Coastal communities around the world are facing increasingly severe climate change impacts that threaten their current and future livability. To address these impacts, coastal climate adaptation projects have taken various approaches to decreasing climate vulnerability through nature-based solutions and hard infrastructure centered around minimizing stormwater flooding, coastal erosion, and sea-level rise; as well as coastal retreat programs for when vulnerabilities cannot be mitigated. While these adaptation projects are important in addressing current climate impacts, many adaptation projects run the risk of exacerbating pre-existing social inequalities and/or creating new ones. We surveyed current coastal climate adaptation projects in Canada, which include a mix of nature-based, hard infrastructure, relocation, and hybrid projects, and performed a literature review to assess adaptation projects’ potential social equity risks based on the information available. We find that all adaptation plans have the potential of generating equity risks, with different kinds of interventions potentially generating different risks, such as redirecting climate impacts to other communities, displacing communities, and promoting development in risky areas. Adaptation projects are more likely to experience maladaptive social outcomes when they are planned and implemented by people removed from the impacted communities, as this removal often creates oversights in exactly who and how people will be impacted. Maladaptive outcomes may also be the result of processing and funding limitations. Conversely, we found that there are important mediating steps that can limit or avoid maladaptive outcomes, most importantly inclusive planning processes where marginalized groups are involved in decision-making. We argue that this risk-based approach to purposely outline potential maladaptive outcomes are important to assess how adaptation projects may perpetuate the historical marginalization, dispossession, and displacement of marginalized communities. If potential risks can be outlined in advance, there are opportunities for planning processes to mitigate and avoid these risks.
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How this classification was reachedexpand
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 | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".