“Sometimes, I just want to scream”: Institutional barriers limiting adaptive capacity and resilience to extreme events
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
• Community resilience demands functioning infrastructure and emergency management. • Infrastructure deficit increases impact severity during extreme events. • Emergency management requires high adaptive capacity and effective infrastructure. • Hierarchical governance limits local-level adaptive capacity. • Development-driven decision-making compromises community resilience. Climate change is increasing atmospheric river risk, requiring communities to build resilience and implement adaptation strategies. Effective infrastructure and emergency management are two adaptations required for communities to cope with, and respond to, acute impacts of climate-related extreme events. In 2021, Fraser Valley, British Columbia, Canada experienced an unprecedented, yet anticipated, atmospheric river that exceeded risk-mitigation infrastructure and emergency management capacity. We ask: if they knew, why were they not prepared? Through a review of strategic planning documents and a qualitative analysis of semi-structured, key actor interviews, we analyze the impact of adaptive capacity on adaptation implementation. Our findings demonstrate that institutional barriers limited adaptive capacity, stagnated adaptation implementation and, in consequence, existing infrastructure and emergency management were insufficient to prevent acute impacts during the event. Further discussion identified formal and informal institutions preventing adaptation implementation: Formally, hierarchical governance decreased community adaptive capacity and led to infrastructure deficit, while informally, development-driven decision-making overshadowed infrastructure mitigation and preparedness priorities. Historical anthropocentric decisions persisted through path dependencies, preventing resilient decision-making during a time of rapid change. Recommendations are made to address these barriers and empower communities to prepare for climate change. This research offers understanding on institutional barriers limiting adaptive capacity and, more generally, contributes to a growing body of research that elucidates why communities face climate change underprepared.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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 it