Hurricane resilience indicators in mexican caribbean coastal cities
Bibliographic record
Abstract
The use of indicators to prevent hurricane impacts locally is a new tool in the area of climate change and resilience. However, many critics the methods for designing these indicators, mainly those resulted from bottom-up and top-down models. Based on the social-ecological analysis, it is defined coastal urban resilience for hurricanes under the bottom-up and top-down model, with the support of experts and other key actors in the integral hurricane management in three coastal cities in the Mexican Caribbean: Chetumal, Tulum and Playa del Carmen. Thus, the objective of the present research is to generate coastal urban resilience indicators that comprehend the complex learning system, adaptation and selforganization in hurricanes. Indicators measures three spatial levels: local, regional and global and one temporal (1-year cohort of 1990). Besides, the following are the three dimensions of indicators: A. Resilience capacities (history of hurricane impacts). B. Consequences (management and self-organization). C. Learning and behaviors (in front of effects and damages).
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.
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 | 0.000 | 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 | 0.000 | 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 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".