Background and Rationale — CDC Guidance for Communities Assessing, Investigating, and Responding to Suicide Clusters, United States, 2024
Bibliographic record
Abstract
To assist community leaders in public health, mental health, education, and other fields with developing a community response plan for suicide clusters or for situations that might develop into suicide clusters, in 1988, CDC published Recommendations for a Community Plan for the Prevention and Containment of Suicide Clusters (MMWR Suppl 1988;37[No. Suppl 6]:1-12). Since that time, the reporting and investigation of suicide cluster events has increased, and more is known about cluster risk factors, assessment, and identification. This supplement updates and expands CDC guidance for assessing, investigating, and responding to suicide clusters based on current science and public health practice. This report is the first of three in the MMWR supplement that describes an overview of suicide clusters, information about the other reports in this supplement, methods used to develop the supplement guidance, and the intended use of the supplement reports. The second report, CDC Guidance for Community Assessment and Investigation of Suspected Suicide Clusters - United States 2024, describes the potential methods, data sources and analysis that communities can use to identify and confirm suspected suicide clusters, and better understand the relevant issues. The final report, CDC Guidance for Community Response to Suicide Clusters - United States, 2024, describes how local public health and community leaders can develop a response plan for suicide clusters. The guidance in this supplement is intended as a conceptual framework that can be used by public health practitioners and state and local health departments to develop response plans for assessing and investigating suspected clusters that are tailored to the needs, resources, and cultural characteristics of their communities.
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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 | 0.037 | 0.107 |
| Meta-epidemiology (narrow) | 0.003 | 0.003 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.008 | 0.007 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.009 | 0.006 |
| Open science | 0.009 | 0.007 |
| Research integrity | 0.012 | 0.014 |
| Insufficient payload (model declined to judge) | 0.020 | 0.018 |
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".