Potential Research Questions
These are questions that exist in the 911 space that might be informed by a standardized 911 dataset. Reimagine 911 needs a partner with deep domain experience in order to begin looking into these questions.
Geographic Questions
Urban & Rural - Differences in call types across urban and rural calls. Due to the general lack of open rural data, it may be necessary to seek data directly from individual rural 911 centers.
Income & Poverty: Compare alternative-response opportunities across communities with different income and poverty levels.
Demographics & Indicators
Health & Wellbeing factors: Are there any visible trends when 911 calls are crossed with quality of life indicators (eg wealth, employment, the environment, physical and mental health, education, recreation and leisure time, social belonging, religious beliefs, safety, security and freedom)? [1]
911 Industry Questions
Classification errors: Can we shed any light on the type or volume of coding errors made by 911 call takers? [2] Can we find datasets with both initial and cleared call types for comparison?
Response Time Correlation: Compare response times to calls between different jurisdictions, correlated with other types of indicators such as household income and budget data
Call Incidence Correlation: with certain indicators such as household income and mental health service coverage
Diversion questions
Frequently Diverted Calls: What is the prevalence of call types that are often associated with alternative responses (behavioral health, mediation, homelessness, etc)?
Diversion-Associated Reductions: In cities which have established policies for diverting 911 calls to non-police responders, is it possible to see changes in call volume elsewhere in the dataset?
Data Applications
Machine Learning - Could the standardized call types be used as training material for supervised learning in automatic call classification?
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See also County Health Rankings Model ↑
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