University of California, Irvine, School of Social Ecology Irvine at 50: A Tale of Continuity and Change • November 1 2021
Appendix A number of data sources were used to compile this Report. The city-level crime data was obtained from the FBI’s Uniform Crime Reporting (UCR) program data, which provides crime data for all cities that reported their information to the FBI. We used the Part 1 crimes: violent crime was aggregated from homicides, robberies, and aggravated assaults. Property crime was aggregated from burglaries, motor vehicle thefts, and larcenies. City crime rates were calculated by dividing by the population, and then multiplying by 10,000 to express the rates per 10,000 residents. » The police staffing data come from the FBI’s Law Enforcement Officers Killed and Assaulted (LEOKA) dataset, which also provides information on police staffing levels. » We used city-level demographic data from the U.S. Census (for 1980, 1990, and 2000) and American Community Survey 5-year estimates data for 2010 (using the 2008-2012 5-year estimates) and 2017 (using the 2015-2019 5-year estimates). » For 1970 for Irvine, the city was not yet incorporated. Therefore, in that year we used census tract-level data for that decade and aggregated the information in the tracts that were within the boundaries of the eventual city to compute the measures of interest. » For the city-level regression models, the crime data is based on three-year averages centered on the year of the model. This smooths year to year fluctuations. » For the computations on the number of cul-de-sacs and intersections in Irvine, we constructed a street network for the entire Southern California region. We then computed the values of interest based on the street network within Irvine, and compared this to the values for the entire region. For the computations of the clustering of businesses and jobs, we used the Reference USA Historical Business dataset. These are proprietary data with information on the locations of all businesses in the region for each year between 1997 and 2014. The businesses were geocoded to a specific location, and then aggregated to the appropriate census block. The data also provide information on the number of employees in each business.
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