Holding together after disaster: The role of social skills in strengthening family cohesion and resilience
Bibliographic record
Abstract
Abstract Objective This study investigated how a flooding disaster impacted family cohesion and resilience. Background Disasters present challenges for families, often threatening family cohesion. Although there is extensive research on the impacts of disasters on mental health at the individual level, less is known about how family units recover from disasters, and how parental relationship dynamics and parent–child dynamics influence family functioning during and after such traumatic events. Method Qualitative face‐to‐face interviews were conducted 1 year after the 2013 southern Alberta flood with 105 parents of children ages 17 years and under. Results Findings reveal that families who experienced more loss were not necessarily more negatively impacted overall. Some families reported the flood caused them to grow further apart, whereas for others it brought them closer together. Those who reported that the flood brought them closer together demonstrated the following three main social skills: (a) communication, (b) conflict resolution, and (c) coping. Findings also reveal that families have higher levels of cohesiveness and resilience post‐disaster when they exhibit these important skills. Conclusion This research concludes that coming together as a family unit created a supportive space for families to process and reduce the stress generated by the flood event. Families who demonstrate and practice communication, conflict resolution, and coping in the face of challenging events like disasters are more cohesive and resilient. Implications Understanding how key social skills influence family members' functioning post‐disaster in terms of cohesion and resilience provides important insight into strategies, services, and resources that can be adopted and utilized to support families in disaster contexts.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.000 | 0.001 |
| 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".