USincarcerations {Ecdat} | R Documentation |
US incarcerations 1925 onward
Description
Counts of prisoners under the jurisdiction of state and federal correctional authorities in the US. This does not include jail inmates.
Usage
data("USincarcerations")
Format
A data frame with 95 observations on the following 7 variables.
- year
-
an integer vector giving the year
c(1925:2019)
. - stateFedIncarcerees
-
Total number of incarcerees =
maleTotal + femaleTotal
. - stateFedIncarcerationRate
-
incarceration rate =
stateFedIncarcerees
per 100,000 population. - stateFedMales
-
Total number of male incarcerees.
- stateFedMaleRate
-
male incarceration rate =
maleTotal
per 100,000 males in the US population. - stateFedFemales
-
Total number of female incarcerees.
- stateFedFemaleRate
-
female incarceration rate =
femaleTotal
per 100,000 females in the US population.
Details
This dataset began as an effort to update
File:U.S. incarceration rates 1925 onwards.png
on Wikimedia Commons.
Conveniently data on these variables
was provided in a table for 1925 to 2014.
And a description was given of how to update
that table using files p*t03.csv
and
p*t05.csv
from
Prisoners In 2019.
An initial rationality check was to compute
checkTot
<-
stateFedIncarcerees
-
stateFedMales
-
stateFedFemales
This was 0 except for 1927 and 1973, when it
was 637 and 684. The stateFedFemales
for 1972:1974 was 6269, 6004, 7389. We
replaced 6004 with 6688, which made the
checkTot
0 for 1973.
Similar checks for 1927 yielded nothing as
obvious. However, the
stateFedIncarcerees
increased 6.9
percent in 1926 over 1925, and 12.2 and
5.8 percent in the following two years.
Subtracting 637 from 109983 for 1927 gave us
109346, which reduced the increase to 11.6
percent for 1927. It's no longer the maximum
annual increase prior to 1975.
Next, these numbers were compared with those
in p19t03.csv
and p19t05.csv
,
which include numbers of incarcerees and
rates per 100,000 population for 2009:2019.
The numbers were identical for 2009:2011,
but there were several differences for the
more recent counts.
For USincarcerations
, we used the
numbers from p19t03.csv
and
p19t05.csv
, because they seem likely
to be more accurate.
However, these numbers include only people in state and federal prisons. It excludes jails.
Key Statistic: Total correctional population
includes a plot of "Total adult
correctional population 1980-2016", which
does include jails. The data there are
available as
Total_correctional_population_counts_by_status.csv
. Data on these variables covering
2008-2018 are available as
cpus1718.csv
from "Data tables" at
Publication Correctional Populations In The United States, 2017-2018.
The data in cpus1718.csv
is mostly
but not entirely identical to "Total adult
correctional population 1980-2016" for
2008-2016, the period of overlap. We
therefore used the older data up to 2007
and cpus1718.csv
for 2008-2018.
Actual analysis of the jail data is left for another project.
Source
Data from 1925 to 2014 from
File:U.S. incarceration rates 1925 onwards.png
on Wikimedia Commons, accessed 2020-11-23.
The primary source for the more recent data are
files p*t03.csv
and p*t05.csv
from
Prisoners In 2019, accessed 2020-11-23.
Data on jails and community supervision dating back to 1980 are available in Key Statistic: Total correctional population with data on the most recent years available from Publication Correctional Populations In The United States, 2017-2018.
Some time in 2021 or later more recent data should become available. When that happens, it may be desired to update this table to include those numbers – and check for any revisions of earlier numbers.
References
United States incarceration rate.
Examples
data(USincarcerations)
matplot(USincarcerations[1],
0.001*USincarcerations[c(3, 5, 7)], type='l',
xlab='', ylab='incarceration rate (%)')
abline(h=0.5, lty='dotted', col='gray')
lbl <- paste("US incarceration rate",
'(percent of the population)', sep='\n')
text(1955, 0.75, lbl)
text(2007, 0.86, 'male', col=2)
text(2007, 0.15, 'female', col=3)