When Law Enforcement Meets School Discipline: School-related Arrests in Maryland 2015-16

Gail L. Sunderman & Erin Janulis

6/1/2018 | Download This Brief

The 2018 school shootings in Maryland, Florida, and Indiana resurrected conversations about school security including the role of police officers on school grounds. Despite the potential benefits of protecting students during violent incidents, the presence of police officers in schools raises other concerns. Research has found that police presence in schools relates to increased rates of arrests and juvenile justice referrals (Curtis, 2013). In addition, research documents that school-related arrests are often for minor misbehaviors rather than actions that endanger other students (Redfield & Nance, 2016; Wolf, 2013), and black students, male students, and students with disabilities (SWD) are arrested disproportionately (USDE-OCR, 2014; Wolf, 2013). While little research exists on the impacts of school-related arrests (by itself) on student’s lives, other research finds that exclusionary discipline practices are associated with school disengagement, low graduation rates, increased dropout rates, and increased involvement with the criminal justice system (Wolf & Kupchik, 2017; Skiba, Arredondo, & Williams, 2014; Kirk & Sampson, 2011, Fabio, et. al., 2011; Gregory, Skiba, & Noguera, 2010; Kang-Brown, Trone, Fratello, & Daftary-Kapur, 2013).

Until recently, data on school-related arrests in Maryland has not been easily attainable or widely reported. This situation changed when the Maryland State Department of Education (MSDE) released data on school-related arrests publically for the first time in 2018 (MSDE, 2018). In this data brief, we examine how school-related arrests vary across school districts in Maryland. We examine arrests rates by race, gender, and students receiving special services to identify potential disparities between groups of students. Since the data released from MSDE captures a single year of arrest data, our analysis is limited to comparisons across districts and different populations of students and does not include trends over time.

Data and Analysis

To examine school-related arrests in Maryland, we use data from the MSDE Student Arrest Data Collection for the 2015-16 school year (MSDE, 2018). This report defines school-related arrests as “an arrest of a student for any activity conducted on school grounds, during off-campus school activities, or due to referral by any school official” (MSDE, 2016).  School-related arrests are reported as the number of incidents rather than the number of students arrested. That is, these duplicated counts include multiple arrests of a single student as separate incidents. We also use 2016 demographic and enrollment data downloaded from the MSDE school report card (MSDE, 2016) and national school arrest data from the United States Department of Education Office of Civil Rights for the 2015-16 school year (USDE-OCR, 2018).

The arrest rate shows the difference between a group’s representation in the population at large and it’s over or underrepresentation in school-related arrests. To examine how school-related arrests vary across districts, we calculated the arrest rate per 1000 students. This is calculated by dividing the number of arrests in a district by the total district enrollment multiplied by 1000. Since larger districts may have more school-related arrests simply because of the number of students enrolled in the district, arrest rates per 1000 students allow us to consider the school-related arrests relative to enrollment rather than simply the frequency of arrests. We also calculate the arrest rate for specific subgroups: race/ethnicity, gender, students with disabilities served by IDEA (SWD), English learners (EL), and students eligible for free and reduced-price meals (FARM).

To compare differences in arrests rates between groups, we calculated the relative risk or risk ratio. The risk ratio shows the probability of a specific subgroup of students receiving a school-related arrest compared to a reference group. For this brief, we compared male to female students, black to non-black students, students with disabilities to students without disabilities, and FARM to non-FARM students. Risk ratios by school district are presented in Appendix B.

School-Related Arrest Rates

School-related arrest rates vary by district

Maryland reported 2,759 school-related arrests in the 2015-16 school year. With a statewide enrollment of 879,196, the arrest rate was 3.1 arrests for every 1000 Maryland K-12 public school students. Comparatively, in 2015-16 the national school-related arrest rate was 1.2 per 1000 students (USDE-OCR, 2018).

At the district level, Prince George’s County accounted for the largest share of arrests (21%), followed by Baltimore (14%), and Montgomery (11%) counties (Appendix A). However, when accounting for district size, a very different picture emerges. The district arrest rate ranged from 16.2 arrests in Dorchester County, 11.2 in Washington County, and 10.4 in St. Mary’s County to 0 in Frederick County, which reported no school-related arrests (figure 1). While Prince George’s County had the largest share of arrests, its arrest rate was 4.6; the arrest rate in Baltimore County was 3.5 and in Montgomery County it was 1.9. Among districts with the lowest arrest rates were Anna Arundel (0.5), Wicomico (0.8), Carroll (0.9), Baltimore City (1.1) and Allegany (1.2).

Reasons for school-related arrests

Figure 2 shows that 84% of all arrests fall into four categories:  38% for assault, 25% for other, 12% for possession of controlled substances on school property, and 9% for disorderly conduct. Further, Appendix C shows that black students are over-represented in all arrest categories, with the exception of possession of controlled substances on campus. Many of the reasons for student arrests are relatively minor infractions and/or behaviors that rely on subjective interpretation of behavior (i.e., disorderly conduct, other) rather than more objectively observable criteria (i.e., possession of controlled substance, trespassing, possession of a firearm). Both factors can contribute to disparities in arrests.

School-Related Arrests by Race, Gender, and Student Status

Black students are disproportionally arrested at school

Our analysis shows that black students were the only racial group arrested at a higher rate than their proportion of school enrollment at the state level and across districts. Black students represented 66% of 2015-16 school-related arrests while comprising 34.6% of the K-12 public school population (figure 3). Comparatively, white students made up 39% of school enrollment and 21% of school-related arrests. This means that black students are 3.67 times as likely to be arrested at school than non-black students in Maryland, a rate that is higher than the national average of 3.11 (USDE-OCR, 2018). At the district level, the risk of arrest for black students versus non-black students ranged from 16.95 in Queen Anne’s, 11.14 in Talbot, and 10.47 in Howard counties to 2.43 in Montgomery County (Appendix B).

Male students are disproportionally subject to arrest at school

In Maryland male students are more likely to receive a school-related arrest compared to female students. As shown in figure 4, male students comprised 51% of the school-age population in 2015-16, yet they represented

67% of school-related arrests. While female students made up 49% of K-12 public school students in Maryland, they represented 33% of school-related arrests statewide. Considered another way, male students in Maryland are almost twice as likely as female students to receive a school-related arrest (RRR=1.97; Appendix B). Nationwide, male students are 2.00 times as likely to be arrested at school than female students (USDE-OCR, 2018). At the district level, the risk that a male student is arrested relative to a female student ranged from 1.42 in Washington County to 4.79 in Queen Anne’s County (Appendix B).

 

 

Students with disabilities and students eligible for free and reduced priced meals are disproportionally subject to arrest at school

Students with disabilities represented 11% of the student population but comprised 22% of school-related arrests (figure 5). As shown in Appendix B, SWD are 2.45 times as likely to be arrested at school than students without disabilities. Comparatively, the Maryland state average is slightly below the national risk ratio of 2.80 for this group (USDE-OCR, 2018). At the district level, the risk of arrest for SWD ranged from 0.66 in Wicomico

to 6.86 in Anne Arundel. While 63% of school-related arrests in Maryland were FARM students, they represented 45% of the student population. Students eligible for FARM are arrested at a rate 2.82 times greater than non-FARM students; the risk of a school-related arrest ranged from 1.11 in Worchester to 7.15 in Wicomico (Appendix B). No national comparison data is available for FARM students. In contrast, English Learners are not arrested at disproportionally high rates (2% arrested compared to 8% of student enrollment).

 

 

 

Conclusion and Recommendations

The results of our analyses found disparities in school-related arrest rates in Maryland, particularly among black students, students with disabilities, and male students. FARM students were also subject to disproportionality in school arrests. Furthermore, the disproportionalities occurred in varying magnitudes in every school district in Maryland where there was sufficient data to examine. The findings suggest that differential treatment of students may be related to these disparities. 

In addition, there is considerable variation between districts in arrest rates and in disproportionalities.  Some of the patterns were unexpected. For example, Baltimore City has among the lowest arrest rates in the state at 1.1 per 1000 students. On the other hand, Anne Arundel County has a relatively low arrest rate (0.5 per 1000 students), but the risk of arrest for black students (7.79) and SWD (6.86) is high. The finding that arrest rates and disproportionalities are much higher in some districts than others suggests that district and/or school level factors likely influence the probability of a school-related arrest. Additional research is necessary to uncover specific school-level characteristics and practices associated with disparities in school-related arrests in Maryland schools. Knowing which schools have higher arrest rates will help to develop targeted school-level interventions designed to help educators improve their disciplinary practices.

Finally, because the Maryland General Assembly passed legislation in 2018 (SB 1265) requiring all schools to have a school resource officer (SRO) or other local law enforcement officer in the school, monitoring arrest rates can be used to gauge the impact of this increased police presence in the schools. The current data suggest that school-related arrests are not restricted to serious or dangerous behavior, but appear to be used for other types of disruptions, especially disorderly conduct and ‘other.’ Because research suggests that the presence of a SRO or other security personnel in a school may have both positive and negative consequences for students (Jennings, Khey, Maskaly, & Donner 2011), particularly students of color and those with disabilities (Pigott, Stearns, & Khey 2018), the need for more research and monitoring as the law is implemented is necessary to determine how the presence of these officers impacts arrest patterns.

We applaud MSDE for releasing these data and encourage the continued monitoring of school-related arrests as data become available. A critical first step in creating positive change in disciplinary practices is for MSDE is to broadly share these data with education stakeholders, including educators, administrators, families, and community members. Raising awareness of disparities can create incentives for school leaders to seek out programs and strategies to address them. We recommend the following:

• Continue monitoring, reporting, and disaggregating school-related arrests annually to identify trends over time. Data collection and reporting are essential for developing and implementing effective strategies for reducing school-related arrests. This analysis establishes a baseline that teachers and administrators can use to track changes over time. In addition, publicly reporting and disaggregating data provides transparency about which groups are disciplined more than others and for what offences. 

• Develop and implement alternative disciplinary approaches targeted to the needs of each district and school. There are a number of research-based interventions that districts and schools can adopt that are effective in improving school discipline and have the potential to reduce disparities. These strategies focus on three key components:  relationship building through approaches such as restorative practices; social-emotional learning programs that help students understand social interactions and manage their emotions; and changing the structure of the disciplinary system through interventions such as Positive Behavioral Interventions and Supports (PBIS) or revising disciplinary codes of conduct (Skiba & Losen, 2015). In order for educators to integrate these strategies into their practice, it will require time and resources to learn and implement new approaches and ongoing support from school, district, and state leadership.

• Develop and standardize the definitions of the offenses that can result in a school-related arrest that are consistent and uniform across districts. The MSDE (2016) student arrest manual defines some offenses, but not others. In addition, the reporting categories are broad and include both minor and serious offenses. For example, the MSDE student arrest manual defines physical attack or fighting as “actual and intentional touching or striking of another person against his/her will, or the intentional causing of bodily harm to an individual.” By conflating touching and striking, this definition does not account for the severity of the offense.  

• Monitor the implementation of SB 1265 to ensure that the increased presence of school resource officers and/or police officers in the schools does not lead to increases in school-related arrests and disparities by race and for vulnerable populations of students.

References

Curtis, A. J. (2013). Tracing the school-to-prison pipeline from zero-tolerance policies to juvenile justice dispositions. The Georgetown Law Journal, 102, 1251-1277.

Fabelo, T., Thompson, M.D. Plotkin, M., Carmichael, D., Marbanks, M.P., & Booth, E.A. (2011, July). Breaking schools’ rules: A statewide study of how school discipline relates to students’ success and juvenile justice involvement. New York: Council of State Governments Justice Center & Public Policy Research Institute at Texas A&M. Retrieved from https://csgjusticecenter.org/wp-content/uploads/2012/08/Breaking_Schools_Rules_Report_Final.pdf

Gregory, A., Skiba, R. J., & Noguera, P. A. (2010). The achievement gap and the discipline gap: Two sides of the same coin? Educational Researcher, 39(1), 59-68.

Jennings, W. G., Khey, D. N., Maskaly, J., & Donner, C. M. (2011). Evaluating the relationship between law enforcement and school security measures and violent crime in schools. Journal of Police Crisis Negotiations, 11(2), 109–124.

Kang-Brown, J., Trone, J., Fratello, J., & Daftary-Kapur, T. (2013).  A generation later: What we've learned about zero tolerance in schools. Vera Institute of Justice. New York: Vera Institute of Justice. Retrieved from https://storage.googleapis.com/vera-web-assets/downloads/Publications/a-generation-later-what-weve-learned-about-zero-tolerance-in-schools/legacy_downloads/zero-tolerance-in-schools-policy-brief.pdf

Kirk, D. S. & Sampson, R. J. (2011). Crime and the production of safe schools. In Duncan, G. J. & Murnane, R. J., Eds. Whither opportunity? Rising inequality, schools, and children’s life chances. 397-417.

Maryland Safe to Learn Act of 2018 (Maryland) SB1265 (US) http://mgaleg.maryland.gov/2018RS/chapters_noln/Ch_30_sb1265E.pdf

Maryland State Department of Education (2018). Maryland public schools arrest data 2015-2016 [Data file]. Retrieved from http://marylandpublicschools.org/about/Documents/DSFSS/SSSP/StudentArrest/MarylandPublicSchoolsArrestData011218.pdf

Maryland State Department of Education (2016). State report card [Data File]. Retrieved from http://msp2016.msde.state.md.us/

Maryland State Department of Education (2016). Student arrest data collection manual. Retrieved from http://marylandpublicschools.org/about/Documents/DSFSS/SSSP/StudentArrest/20152016StudentArrestsManual072016.pdf

Pigott, C., Stearns, A. E., & Khey, D. N. (2018). School resource officers and the school to prison pipeline: Discovering trends of expulsions in public schools. American Journal of Criminal Justice, 43, 120-138.

Redfield, S.E. & Nance, J.P. (2016, February). The American Bar Association Joint Task Force on Reversing the School-to-Prison Pipeline Preliminary Report. American Bar Association Coalition on Racial and Ethnic Justice, Criminal Justice Section, and Council for Racial & Ethnic Diversity in the Educational Pipeline (2016). Retrieved from https://scholarship.law.ufl.edu/facultypub/750/

Skiba, R. J. & Losen, D. J. (2015).  From reaction to prevention: Turning the page on school discipline.  American Educator. Retrieved from https://www.aft.org/ae/winter2015-2016/skiba_losen

Skiba, R. J., Arredondo, M. I. & Williams, N. T. (2014). More than a metaphor: The contribution of exclusionary discipline to a school-to-prison pipeline.  Equity & Excellence in Education, 47:4, 546-564. 

Skiba, R. J., Shure, L., & Williams, N. (2012). Racial and ethnic disproportionality in suspension and expulsion. In A. L. Noltemeyer & C. S. McLoughlin (Eds.), Disproportionality in education and special education. Springfield, IL: Charles C. Thomas Publisher, Ltd.

Wolf, K.C. (2013). “Booking students: An analysis of school arrests and court outcomes.” Northwestern Journal of Law & Social Policy, 9:1, 58-87.

Wolf, K. C. & Kupchik, A. (2017). School suspensions and adverse experiences in adulthood. Justice Quarterly, 34:3, 407-430.

United States Department of Education Office for Civil Rights (2018). 2015-2016 Civil rights data collection (CRDC)[Data file]. Retrieved from https://www2.ed.gov/about/offices/list/ocr/docs/crdc-2015-16.html   

Appendix A: School-related Arrest Rate by District

District	Arrests	Enrollment	% of Total Arrests	Arrest rate per 1000 Students
MARYLAND	2761	879,196	-	3.1
Allegany	11	8812	0.40%	1.2
Anne Arundel	39	80,387	1.41%	0.5
Baltimore City	90	83,666	3.26%	1.1
Baltimore County	393	111,138	14.23%	3.5
Calvert	88	16,017	3.19%	5.5
Caroline	*	5602	*	*
Carroll	23	25,551	0.83%	0.9
Cecil	75	15,859	2.72%	4.7
Charles	176	26,307	6.37%	6.7
Dorchester	77	4739	2.79%	16.2
Frederick	0	40,655	0.00%	0.0
Garrett	17	3856	0.62%	4.4
Harford	98	37,448	3.55%	2.6
Howard	242	54,870	8.76%	4.4
Kent	15	2029	0.54%	7.4
Montgomery	304	156380	11.01%	1.9
Prince George's	588	128,936	21.30%	4.6
Queen Anne's	18	7717	0.65%	2.3
Somerset	14	2908	0.51%	4.8
St. Mary's	186	17,941	6.74%	10.4
Talbot	25	4625	0.91%	5.4
Washington	249	22,303	9.02%	11.2
Wicomico	12	14,790	0.43%	0.8
Worchester	19	6660	0.69%	2.9

 Appendix B: Risk Ratio by District

District	Male/Female	Black/Non-Black	SWD (served by IDEA) /Non SWD	FARM/Non FARM
MARYLAND	1.97	3.67	2.45	2.82
Allegany	*	*	*	*
Anne Arundel	3.72	7.79	6.86	4.25
Baltimore City	2.25	4.77	3.80	4.77
Baltimore County	2.04	4.20	1.92	2.62
Calvert	2.07	4.08	2.72	2.42
Caroline	*	*	*	*
Carroll	2.70	*	1.26	1.68
Cecil	2.31	4.60	3.16	3.98
Charles	2.02	3.79	2.40	3.13
Dorchester	2.97	2.68	2.78	3.30
Frederick	*	*	*	*
Garrett	3.03	*	1.86	3.66
Harford	2.91	2.46	3.03	3.54
Howard	1.98	10.47	*	*
Kent	1.96	7.00	*	*
Montgomery	3.75	2.43	1.61	2.02
Prince George's	1.53	4.98	2.73	1.16
Queen Anne's	4.79	16.95	3.14	5.56
Somerset	*	4.78	2.40	*
St. Mary's	1.50	7.31	2.17	5.83
Talbot	1.68	11.14	1.76	6.46
Washington	1.42	5.57	3.42	5.89
Wicomico	*	*	0.66	7.15
Worchester	2.61	8.93	1.96	1.11

Appendix C: School-related Arrests by Offense and Race, Maryland

Arresting Offense	Total	Black		White		Other
	#	#	%	#	%	#	%
Arson	15	*	*	*	*	*	*
Assault	1059	760	72%	180	17%	119	11%
Breaking and Entering	14	13	93%	0	0%	*	*
Controlled Substance Possession to or on school property	331	139	42%	135	41%	57	17%
Controlled Substance Possession with intent to distribute	100	64	64%	18	18%	18	*
Disorderly Conduct	251	196	78%	32	13%	23	9%
Other	683	370	54%	167	24%	146	21%
Physical Attack or fight with Weapon	17	16	94%	*	*	*	*
Physical Attack or fight without a weapon	33	*	*	*	*	*	*
Possession of firearm or explosive device	30	25	83%	*	*	*	*
Robbery with a weapon	12	*	*	*	*	*	*
Robbery without a weapon	30	28	93%	*	*	*	*
Sexual Battery	10	*	*	*	*	*	*
Theft Misdemeanor	133	100	75%	22	17%	11	8%
Trespassing	61	47	77%	*	*	*	*

About the Maryland Equity Project

Website: www.mdequity.org
Twitter @mdequity

Gail L. Sunderman, Ph.D., is Co-Director of the Maryland Equity Project and senior research scientist in the Department of Teaching and Learning, Policy and Leadership in the College of Education at the University of Maryland.

Erin Janulis, M.A., is a doctoral student in the Department of Teaching and Learning, Policy and Leadership, College of Education at the University of Maryland.