1. Connor Brooks and Kevin M. Scott (2015), ``Number of arrest-related deaths,
percent confirmed by survey respondents, and death-identification source,
by state, June-August 2015,'' v 07/30/2019, Arrest-Related Deaths Program:
Pilot Study of Redesigned Survey Methodology NCJ 252675, Bureau of Justice
Statistics.
2. 2010 US Census
3. ``Police Use of Force Policy Analysis,'' Campaign Zero.
4. Samuel Sinyangwe (2016), ``Examining the Role of Use of Force Policies in Ending
Police Violence.''
5. Mapping Police Violence database (mappingpoliceviolence.org)
num_deaths: Number of deaths that met Arrest-Related Deaths program-eligibility criteria (June-August 2015) [1] pct_confirmed: Percent of deaths confirmed by at least one survey respondent * [1] pct_media: Percent of deaths initially identified through media review [1] pct_survey: Percent of deaths initially identified by survey respondent [1]
Deaths were initially identified by a survey respondent or were confirmed by either the law enforcement agency or medical examiner's/ coroner’s office respondent associated with a media-identified death.
pop2010: total population of city (NOT metro area) [2] black_pop2010: total Black population of city [2] white_pop2010: total white population of city [2] deaths2016: number of police killings, Jan 1-July 15 2016 [4] all other variables: has the policy been enacted? (1 for yes; 0 for no) [3]
Scripts to scrape data on city police budgets
- scrape_citydata.R: code to scrape city-data.com
- large_city_budgets.csv: example dataset (cities over 450K pop)
- Connection will be blocked by host if you make too many requests
- dates scraped from web still interpreted as chr vectors instead of datetimes
- Should scrape Crime stats table as well (Anyone want to contribute?)
# Get URLS for each city
city_urls <- states$URL %>%
map_df(get_city_urls)
# Get budgets for entire country
city_budgets <- city_urls$URL %>%
map_df(get_city_payroll)
# get budgets, single state
nv_urls <- city_urls %>%
filter(URL %>% str_detect("Nevada.html"))
nv_budgets <- nv_urls$URL %>%
map_df(get_city_payroll)
> nv_budgets
# A tibble: 326 x 9
state city Function date_str `Full-time_employe… `Part-time_employe… `Monthly_full-time_pay… `Average_yearly_full-tim… `Monthly_part-time_pay…
<chr> <chr> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl>
1 Nevada Carson C… Correction March 2016 69 12 393180 68379 18111
2 Nevada Carson C… Police Protection - Off… March 2016 65 0 419167 77385 0
3 Nevada Carson C… Judicial and Legal March 2016 63 5 368178 70129 9902
4 Nevada Carson C… Firefighters March 2016 59 5 475073 96625 2682
5 Nevada Carson C… Streets and Highways March 2016 49 0 268154 65670 0
6 Nevada Carson C… Financial Administration March 2016 34 5 191263 67505 4189
7 Nevada Carson C… Police - Other March 2016 30 7 170473 68189 7832
8 Nevada Carson C… Other Government Admini… March 2016 29 5 155354 64284 5917
9 Nevada Carson C… Other and Unallocable March 2016 29 4 141163 58412 5146
10 Nevada Carson C… Health March 2016 28 9 155853 66794 17413
# … with 316 more rows