The Dynamics of Psycho-Social-Ecological Resilience in the Urban Environment: A Complex Adaptive Systems Theory Perspective
Bibliographic record
Abstract
As the proportion of people living in urban areas continues to grow (United Nations, 2019), it becomes increasingly important to understand urban resilience in the face of both chronic and acute, endogenous and exogenous stressors. Indeed, there is a growing literature on urban resilience, which includes several recent frameworks to operationalize and assess the concept and its indicators. Inherent in this literature, though rarely explicitly, is the psychology of the people comprising urban environments. The purpose of this paper is to explore the intersection of urban resilience and psychological resilience by viewing both in the context of complex adaptive systems theory. Arising from this juncture is a more robust and dynamic understanding of resilience, a psycho-social-ecological resilience. The discussion will draw from this notion of resilience a more thorough framework for understanding the reciprocal relationships among urban dwelling people and their total environments. Areas for future research and implications for our understandings of psychological resilience, urban resilience, and sustainable cities will be highlighted.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.012 |
| Scholarly communication | 0.004 | 0.005 |
| Open science | 0.001 | 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".