Post-crisis Resilient Governance in Centro region (Portugal) after 2017 wildfires
Bibliographic record
Abstract
Governance systems, when addressing post-disaster action, play an important role in minimizing the community’s vulnerability in future disruptive events. The literature describes how post-disaster actions towards resistance-resilience measures are often implemented, shifting to adaptive-resilience approaches as a second concern, and disregarding resilience-transformative strategies. Two consecutive wildfires in the Centro Region (Portugal), in 2017, cut off access to the Services of General Interest (SGIs) and knocked off-balance the socioeconomic territorial structure and identity (the main impact was 116 mortal victims). In this paper, the media coverage of the phenomena during the 12 months following the disaster is analysed using a sample of 150 news articles published in two newspapers. The public discourses are indicative of the overall importance given to the impact and to the responses based on resistance-resilience measures. Moreover, the theoretical and practical challenges for the policy design and organization of the governance systems in post-disaster contexts is discussed.
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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 | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".