Mecklenburg County Justice Reinvestment Initiative
Analysis of Jail Population Drivers 2008 - 2011
Kevin Baldwin, Ph.D.
Applied Research Services, Inc.
April 13, 2012
As part of the Mecklenburg County Justice Reinvestment Initiative work, Applied Research Services
obtained and subjected to statistical analysis a data extract from the Arrest Processing Center and the
Jail. The extract is referred to as a release cohort, in that the records represent releases during the
specified time period. This extract contained selected fields (variables) of interest, and covered the
period between January 1, 2008 and December 31, 2011. The original data was organized such that each
record represented a unique charge. For purposes of these analyses, the data was restructured such
that each record represented a unique jail episode, so each record could (and often did) contain more
than one charge. The most serious charge in each episode was identified, and represents the charge of
record for each unique jail episode.
Table 1. Jail Bookings and Releases, 2008 – 2011
Year
2007 and before
2008
2009
2010
2011
Total
Bookings
2084
31868
34443
33615
31127
133137
Percent
2%
24%
26%
25%
23%
100%
Releases
NA
32041
34648
33821
32627
133137
Percent
0%
24%
26%
25%
25%
100%
The tables below provide data relative to the demographic characteristics of jail inmates for the fouryear period from 2008 through 2011. These data represent unique bookings rather than unique
individuals, and therefore individual persons can and often do appear in the data more than once.
Table 2. Race/Ethnicity of Jail Bookings, expressed as percent of total.
Race/Ethnicity
African American
Caucasian
Hispanic
Other
2008 (%)
61.9
21.5
9.9
6.7
2009 (%)
61.8
21.9
10.0
6.3
2010 (%)
63.1
21.7
8.5
6.7
2011 (%)
63.2
22.4
7.5
6.9
Analysis of Jail Population Drivers 2008 – 2011 – April 13, 2012
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Table 3. Gender of Jail Bookings, expressed as percent of total.
Gender
Male
Female
2008 (%)
83.4
16.6
2009 (%)
83.0
17.0
2010 (%)
81.6
18.4
2011 (%)
81.2
18.8
As indicated in table 3, above, the percentage of female bookings into the jail has increased over the
past four years. This change is statistically significant, and therefore may be of interest in terms of future
programming and planning.
Regarding the types of crimes represented by bookings during this period, table 4, below, indicates the
classification of the most serious offense at the time of booking, for releases during 2008 through 2011.
Table 4. Crime Type of Jail Releases, expressed as percent of total.
Crime Type
Misdemeanor
Felony
Traffic
Total
2008 (%)
52.7
30.0
17.3
100.0
2009 (%)
53.2
28.0
18.7
100.0
2010 (%)
53.2
29.0
17.8
100.0
2011 (%)
52.5
29.4
18.1
100.0
As is apparent from the data in Table 4, above, the distribution of misdemeanors, felonies, and traffic
offenses has remained quite stable over the past four years. We further coded offenses according to
whether they represented person, property, drug, or other offense, with the results appearing in Table
5, below.
Table 5. Crime class of Jail Bookings, expressed as percent of total.
Crime Class
Person
Property
Drug
Other (inc. traffic)
2008 (%)
19.2
14.8
30.1
35.8
2009 (%)
19.3
15.0
27.4
38.2
2010 (%)
20.5
16.3
27.1
36.0
2011 (%)
21.8
16.3
26.5
35.8
The above data on crime type reveals a statistically significant difference in the representation of these
categories over the past four years, with an increase in person offenses and a corresponding decrease in
drug offenses. Property and other offenses remained relatively consistent over the time span. This trend
suggests that the jail population is increasingly made up of violent offenders, reflecting national trends
as well as citizens’ and policy makers’ preferences.
In terms of number of charges per booking, 43.5%, 47%, 46.9%, and 48% of bookings represented only a
single charge in the years 2008 through 2011, respectively. Ninety percent of jail bookings represented
four or fewer charges.
Analysis of Jail Population Drivers 2008 – 2011 – April 13, 2012
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As would be expected, jail occupants are released for a number of reasons, with the most frequent
being that pretrial offenders made bond and post-conviction offenders completed their sentence. The
table below provides the reasons for release of upwards of 95% of releases each year.
Table 6. Type of Release by Year, expressed as a percent.
Type of Release
Bond Satisfied
Sentence Expired
OJ
Unsecured
Dismissed
Released on Probation/Parole
Released per Court
Pretrial Release
Complied
All others
2008 (%)
43.4
15.0
14.6
12.3
4.3
3.1
1.3
1.1
1.0
3.9
2009 (%)
45.0
12.9
13.0
16.6
3.6
2.4
1.4
0.7
0.9
3.5
2010 (%)
46.0
12.3
12.5
17.4
3.6
2.0
1.2
0.4
0.9
3.7
2011 (%)
44.6
13.2
12.7
16.3
3.7
2.0
0.9
0.6
1.0
5.0
In addition to the data in Table 6, above, it is important to note that only about 13% to 15% of releases
were accounted for by transfer each year.
Besides knowing why persons are released from jail, it is of course also critical to examine the reasons
why people enter jail in the first place. Table 7, below, provides the top five offenses responsible for
people coming into the jail during the four year span between 2008 through 2011.
Table 7. Top five offenses, 2008 – 2011.
Offense (Literal)
Driving While Impaired
Driving While License Revoked
Drug Paraphernalia – Possession of
Possession of Marijuana, Misdemeanor
Assault on a Female – Non-Aggressive Physical Force
All others
2008 (%)
7.8
6.5
5.9
4.3
3.7
71.8
2009 (%)
7.8
7.5
5.3
4.1
3.7
71.7
2010 (%)
8.2
6.9
5.1
3.7
3.8
72.4
2011 (%)
8.5
7.1
4.8
3.6
4.7
71.3
The above data concerning the top five offenses, together with discussions among CJAG team members,
the focus groups, and the working group, all suggest that taking a closer look at these relatively low level
offenses likely presents opportunities to employ JRI strategies. Additionally, taking a closer look at the
offenders who are most frequently arrested and jailed is also likely to present opportunities to bring JRI
methods to achieve cost savings and cost avoidance strategies.
Analysis of Jail Population Drivers 2008 – 2011 – April 13, 2012
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The following data provide information on the Length of Stay (LOS) for jail episodes where these
offenses represent the most serious offense, for the years 2008 through 2011.
Table 8. Average LOS (ALOS) for the Top Five Offenses, 2008 – 2011.
Offense (Literal)
Driving While Impaired*
Driving While License Revoked*
Drug Paraphernalia – Possession of*
Marijuana – Possession of (Misdemeanor)*
Assault on a Female – Non-Aggressive Physical Force*
* Significant at the .05 level
Average Length of Stay (ALOS)
2008
2009
2010
2011
20.1
13.3
11.1
7.8
6.4
4.5
3.3
4.5
11.9
9.5
7.8
7.9
5.2
2.9
3.4
4.0
18.3
14.4
13.8
13.0
As is apparent from Table 8, above, the average length of stay for each of these offenses has decreased
significantly over the past four years. These decreases are most significant for jail episodes due to DUI
and Assault on a Female – Non-Aggressive Physical Force. Given the volume associated with these
particular offenses, the decreasing ALOS suggests that these trends are certainly in the right direction,
and should be sustained.
Another potential area in which to achieve cost savings is in diverting habitual, low-level offenders from
further involvement or deeper penetration into the criminal justice system. To that end, the CJAG
working group in Mecklenburg County was curious as to the characteristics of citizens who were
arrested on a frequent basis, out of proportion to their actual numbers. An extract of arrest data
inclusive of years 2008 through 2011 was used in order to provide empirical data to address these
questions. Similar to the analysis of the jail data described above, the source data was organized such
that each record represented a separate charge, and was therefore reformatted such that each record
represented a separate arrest episode. Also as with the jail data, the most serious charge was identified
as the charge of record. During this time period there were a total of 163,733 arrest episodes. Table 9,
below, provides the number of arrest episodes per year, 2008 through 2011.
Table 9. Arrests by Year, 2008 – 2011.
Year
2008
2009
2010
2011
Totals
Number
42,987
41,839
39,095
39,812
163,733
Percent
26.3
25.6
23.9
24.3
100.0
Cumulative
Percent
26.3
51.8
75.7
100.0
A total of 86,162 individuals (as indicated by the number of unique PIDs) accounted for these arrest
episodes, with an average of 1.9 arrests per arrestee over the four years from 2008 to 2011. Looking at
the top 1% of arrest episodes however, we find that 48 arrestees (.05%, or five one-hundredths of one
percent) of all arrestees account for fully 1% of all arrest episodes (1704 total arrest episodes between
Analysis of Jail Population Drivers 2008 – 2011 – April 13, 2012
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them), an amount far out of proportion to their actual number. In terms of frequency of arrests, the top
five individuals accounted for 70, 65, 62, 56, and 55 arrests over the four year span. Eighteen arrestees
accounted for just under half (49.7%) of the 1704 total arrest episodes for this entire group of 48
arrestees.
When examining the charges brought against this group of arrestees (counting the most serious charge
only), the offenses are overwhelmingly misdemeanor in nature (93%), followed by felony (4.4%) and
traffic (2.6%) offenses. Table 10, below, provides the 15 most common charges for this group, which
together account for three-quarters of all charges.
Table 10. Charges (listing most serious charge per arrest episode only).
Charge
Trespass - Second Degree – Notified Not to Enter
Solicit Alms/Beg for Money
Drug Paraphernalia – Possession of
Intoxicated and Disruptive
Larceny (Misdemeanor) – Under $50
Larceny (Misdemeanor) - $50 - $199
Soliciting from the Street or Median
Resisting Public Officer
Alcoholic Bev. – Consume Wine/Beer on Public Street
Probation Violation
Driving While License Revoked
Larceny (Misdemeanor) - $200 and up
Open Container Ordinance
Alcoholic Bev. – Public Consumption
C/S – SCH II – Possession of Cocaine
113 other charges
Number
302
199
147
133
110
57
53
48
46
36
35
34
34
29
28
Percent
17.7
11.7
8.6
7.8
6.4
3.3
3.1
2.8
2.7
2.1
2.0
2.0
2.0
1.7
1.6
24.4
Cumulative
Percent
17.7
29.3
37.9
45.7
52.2
55.5
58.6
61.4
64.1
66.2
68.3
70.3
72.2
73.9
75.6
100.0
These arrestees were predominantly African American (69%) and male (98%). Sixty-one percent of
arrestees had only one charge for the arrest episode of record, while 23.6% had two charges, 8.5% had
three charges, and 3.7% had four charges. In terms of arrest type, close to three quarters (72.2%) were
the result of a visual arrest (code ORD), 21.4% were due to the issuance of an Order for Arrest (OFA),
and 6.4% were the result of an arrest warrant being issued.
Regarding the type of bond issued, secured bonds were indicated in 96.4% of arrest episodes, with no
bond issued (code: NBD) at 1.3% and NULL at 1%. A third of arrest episodes had a bond amount of
$500, with 12% each having bond amounts of $1000 and $250. After removing the null cases, 1092 out
of 1657 arrest episodes, or 66%, had bond amounts of $500 or less. The vast majority (93.2%) of arrest
episodes ended with a NULL release, with 2.8% receiving a secured bond, 2.3% an unsecured bond, and
1% released via a Written Promise to Appear (code WPA).
Likely due to their status as frequent arrestees as well as other characteristics, 94% of the arrest
episodes for this group also involved a jail stay. As such, this group of 48 persons had a combined total
Analysis of Jail Population Drivers 2008 – 2011 – April 13, 2012
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of 1601 jail episodes between 2008 and 2011, for a total of 21,445 bed days. Table 11, below, provides
the total number of bed days for this group for each year from 2008 – 2011, as well as the total cost of
these bed days using cost figures provided by the jail.
Table 11. Bed days consumed by the 48 most frequent users of the jail, 2008 – 2011.
Year
2008
2009
2010
2011
Total (Avg.)
Total Bed Days
4715
5488
5664
5578
21445
Cost per Day
$102.15
$110.05
$124.73
$131.04
($116.99)
$
$
$
$
$
Total Cost
481,637.25
603,954.40
706,470.72
730,941.12
2,508,850.55
As is apparent from the data above, this group of 48 persons accounted for 1704 arrests and 1601 jail
episodes over a four year period. The jail episodes resulted in a total of 21,445 bed days, for a cost of
over $2.5 million dollars. These costs are considerable, and do not include the cost borne by the
arresting agencies or the cost of processing them in the Arrest Processing Center and Jail.
Taken together, it would appear that a relatively large number of arrests concern a very small number of
persons, in that five one hundredths of one percent (.05%) of arrestees accounted for 1% of all arrest
episodes during the four years between January 1, 2008 and December 31, 2011. Fully 94% of these
arrests were followed by a jail episode, at the cost of just over $2.5 million dollars in bed days alone.
These persons were most likely to be arrested for minor crimes, often referred to as public order or
public nuisance offenses, such as begging, trespassing, and public alcohol use and/or intoxication. This
pattern of offenses is suggestive of a typical problem concerning offenses committed by persons
afflicted with mental illness and or substance abuse issues, and who are also likely to be homeless.
In terms of next steps, these data suggest that provision of mental health, substance abuse, and related
social services within the community has the potential to reduce the demonstrated overutilization of
criminal justice resources by this small group of persons. One possible means of addressing these
offenders, many of whom are likely to be suffering from mental illness, would be to have officers who
have received Crisis Intervention Team (CIT) training respond to these arrest situations. Doing so may
result in transport of the potential arrestee to a mental health or social services facility and
correspondingly reduce the likelihood that some of these situations result in an arrest. Such diversions
save public funds and allow officers to devote their time to relatively more serious offenses and
offenders. They also have the potential to address the underlying issues presented by these individuals,
potentially reducing their likelihood of future arrest and incarceration. These data, and the conclusions
derived from them, closely mirror the findings of a study of chronic offenders published in March, 2007
by the Mecklenburg County Sheriff’s Office.1
1
Eberly, T.A., Takahashi, Y., & Messina, M. (2007). Chronic Offender Study: Final Report. Charlotte, NC:
Mecklenburg County Sheriff’s Office, Research and Planning Unit.
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