Salutogenesis as a Framework for Social Recovery After Disaster
Bibliographic record
Abstract
Abstract This chapter has its starting point in 2013, when a train carrying crude oil derailed in Lac-Mégantic, Quebec, Canada. Research on the aftermath of this tragedy indicates that the adverse psychosocial impacts resulting from the rail tragedy decreased over time. The authors explain that although the tragedy certainly has left its mark, the local community is gradually adapting to its new reality. The asset-based approach to recovery that has been encouraged seems to have contributed to the “new reality,” emphasizing the importance of social capital to activate individual and community resilience in post-disaster contexts. The authors identify and discuss success factors supporting the recovery of citizens and the social reconstruction of the community, and they document the positive development of the psychosocial situation in Lac-Mégantic, commenting also on the importance of developing a shared understanding of risks and working together in finding solutions. The authors conclude by discussing the importance of long-term initiatives to promote understanding, preventing, and reducing psychosocial risks in the months and years following a disaster, and the need to move from disaster management to risk management logic in response to disasters.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.026 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.011 | 0.001 |
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".