Katrina’s children: Social policy considerations for children in disasters social policy report
Bibliographic record
Abstract
Hurricane Katrina resulted in a disaster of proportions not previously known in the United States. The traumatic experiences of children and families during Hurricane Katrina, the fl ooding that resulted from the breach of the levees, the evacuation, and the aftermath are unprecedented. In responding to the enormous mental health needs of children post-Katrina, the Trauma Team of skilled mental health professionals from the Louisiana State University Health Sciences Center (LSUHSC) Department of Psychiatry provided crisis intervention and services. This paper discusses the work of the LSUHSC Trauma Team and provides a snapshot of the current mental health status of several thousand children and adolescents in post-Katrina New Orleans (not including those who were still displaced). Almost one half of the 4th to 12th grade students and over one quarter of younger children (based on parental report) met criteria for mental health services, based on the number and severity of their behavioral symptoms. Children who were separated from their parents or who had experienced previous trauma or loss were most likely to meet criteria. Ongoing risk relates to poverty, slowness of recovery, job loss, and family problems. Recommendations for rapid deployment of mental health services to children are provided, based on the Trauma Team’s experiences. Educational efforts, school-based services, after-school care, resilience-enhancing programs, and community-building strategies are also discussed. Most important, a clearly articulated national disaster plan for children and families is urgently
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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 | 0.009 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.017 | 0.005 |
| Scholarly communication | 0.008 | 0.005 |
| Open science | 0.003 | 0.012 |
| Research integrity | 0.017 | 0.016 |
| Insufficient payload (model declined to judge) | 0.019 | 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".