human
summarize "Violent death surveillance provides a striking example of the promise and challenge of computational text analysis. Violent deaths are among the leading causes of mortality in the United States (6): More than seven people per hour die a violent death (7). Understanding and reducing the frequency of these deaths are major goals for public health. Much of what we know about violent death comes from large administrative databases like the National Violent Death Reporting System (NVDRS), a nationwide public-health surveillance dataset established by the Centers for Disease Control (CDC) in 2003 (8, 9). The NVDRS contains both structured variables (e.g., victim demographics) and unstructured text narratives. These narratives describe the circumstances of death incidents based on reports from law enforcement, medical examiners/coroners, toxicology, and crime laboratories. While much has been learned from the NVDRS, researchers have largely used the structured variables; traditional qualitative methods are too labor intensive to use at scale. The narratives, summarizing more than 300,000 violent deaths, remain mostly unused, despite their potential to illuminate many aspects of violent death, from proximate correlates to nuanced context."
gpt
--- Reasoning ---
1. Is the question multiple-choice question?
No
2. Is it implied multiple-choice question?
No
3. If two experts were independently asked the question, will the final answer be exactly the same?
No

--- Answer ---
open