In this chapter, I will discuss the conclusions that can be drawn from the results in Chapter 4. I will also mention the limitations of this study as well as implications for policy and future research.
Discussion
The first research question of this study asked what student factors affect their likelihood to be subject to school suspension in North Carolina. Results show that many student factors strongly affect their likelihood of suspension, especially race, sex, economic status and academic performance.
Of all other demographic subgroups, the average Black economically disadvantaged male and the average Native American economically disadvantaged male have the highest likelihood for out-of-school suspension at 21%, and the average multiracial economically disadvantaged male has the highest likelihood for in-school suspension at 17%. This is consistent with the racial threat hypothesis and prior research that has concluded black and multiracial male students are disproportionately suspended. This is also consistent with research that says race and class can interact to put black students at especially high risk for discipline. What this study adds to that literature is a clearer look into Native American students’ likelihood for school discipline. Most studies on school discipline either do not include Native American as a separate racial category or simply do not have enough observations of Native American students to have statistically significant results. Because of the large Native American community in North Carolina, this study was able to observe and present the average Native American child’s high likelihood of suspension relative to other racial groups.
One surprising result of this study was that there is no statistical or practical significance in the likelihood of suspension between the average student with a disability and the average student without a disability. As discussed in Chapter 2, most research shows that students with disabilities are disproportionately disciplined unless the authors defined “disability” as having been identified as having a disability at a young age. Since this study measures disability in ninth grade, I expected to find differences between students with and without disabilities just as
previous research has.
The final interesting result from the first question is the effect school affluence had on likelihood of suspension. Figure 9 showed that the average student who attends a low affluence school has the same likelihood as the average student who attends a high affluence school to be suspended in-school but is more likely to be suspended out-of-school by a factor of 1.3. A possible explanation for this finding is that, compared to the average student who attends a high affluence school, the average student who attends a low affluence school in North Carolina is more likely to act out in a way that would warrant an out-of-school suspension. This would not be consistent with prior research, which fails to find that differential behavior accounts for differential discipline. A second possible explanation behind this that is consistent with the literature is that low affluence schools in North Carolina discipline their students more
punitively. Since this study did not have access to data on the details of the infraction, it cannot be determined which of these explanations is correct.
The second aim of this study was to investigate the association between school
suspension in ninth grade and criminal conviction in North Carolina. The results showed that the average student who is suspended in-school experiences an increase in likelihood of criminal conviction near a factor of 1.8 for both felonies and misdemeanors. For out-of-school
suspension, the average student’s likelihood for criminal conviction increases by a factor of 3.1 and 3.6 for misdemeanors and felonies, respectively. Additionally, analyses that used number of suspensions as the treatment variables showed that likelihood of criminal conviction increases as number of suspensions increases, particularly for out-of-school suspensions. This finding is consistent with prior research that shows additional suspension further increases the likelihood of adverse outcomes for students. However, no study has previously been able to analyze what an increased number of suspensions does for a student’s likelihood of criminal conviction in the adult justice system, so this finding is a unique contribution to the literature. An interesting element of this finding is that the rise in likelihood of convictions with number of out-of-school suspensions is driven primarily by an increase in the likelihood of a felony conviction. As it was discussed in Chapter 4, the average student who is suspended out-of-school eight to ten times in ninth grade has a likelihood of being conviction of a felony that is 4.7 times greater than the average student who is not suspended out-of-school in ninth grade. Comparatively, the difference between those two students is a 3.7 times greater likelihood to be convicted of a misdemeanor. The results of this section of Chapter 4 suggest that out-of-school suspension has particularly adverse effects on a student’s probability for being convicted of a serious criminal offense. Since out-of-school suspension is disproportionately administered to racially and economically
disadvantaged students, as evidenced in section A of Chapter 4, this finding should potentially alarm researchers and advocates in the education field.
At the same time, a positive conclusion that can be drawn is that the association between suspension and criminal conviction stays practically the same regardless of student
characteristics. Question three of this study asked whether any student factors have a moderating effect on the association between suspension and criminal conviction. Results suggest that
suspension may increase the likelihood of criminal conviction more for the average student who is not economically disadvantaged and the average female student compared to the average student who is economically disadvantaged and the average male student, respectively. Although academic performance, race, sex, and economic status all had a statistically significant
moderation effect in at least one model, the practical significance of these moderators are low. This finding adds to the discussion on the deterrent effect of punishment, which some scholars theoretically argue may vary based on who is receiving the punishment and how that punishment is perceived.
Lastly, this study investigated whether the early college intervention is particularly effective in diverting youth from adult criminal conviction. Consistent with findings from question three, the association between suspension and criminal did not based one early college attendance. However, the average early college student has a significantly lower likelihood of being suspended compared to a similar peer who does not attend an early college. Specifically, the average student who does not attend an ECHS has a 1.5 times greater likelihood of receiving an out-of-school suspension in ninth grade and a 4.7 times greater likelihood of receiving an in- school suspension compared to the average student who attends an ECHS. Therefore, although students who are suspended at an early college experience the same increased probability of criminal conviction as an otherwise similar student who was suspended in a non-ECHS, early college students are much less likely to be suspended in the first place, which likely decreases this student population’s rate of criminal conviction overall.
Limitations
The major limitation of this study derive from the lack of available data. First, this dataset did not provide information on the type or detail of the infraction that led to a suspension
incident. As discussed in Chapter 2, infraction data allows researchers to control for student misbehavior. Although these analyses were able to control for prior behavior, a control variable for the actual misbehavior that resulted in the infraction would have created more robust models. Specifically, the addition of this control in the models that predicted in-school and out-of-school suspension would have helped determine whether student demographics were causing higher rates of suspension for disadvantaged students or simply associated with higher raters because of differential behavior. Second, as stated in Chapter 3, only two of the available seven cohorts had full student disciplinary records from eighth to twelfth grade. Because of that, this study’s
conclusions are based exclusively on students who entered ninth grade in a North Carolina public school in 2011. Utilizing all cohorts would have increased statistical power and potentially produced different results.
Another limitation of this study is that it only attempts to predict the likelihood of
suspension for ninth grade, and it only analyzes the association between criminal conviction and ninth grade suspension record. Ninth grade was chosen because the highest proportion of
students are suspended in ninth grade compared to other grades. However, the effect of a ninth grade suspension on criminal conviction is likely not identical to the effect of a suspension in another grade or the cumulative effect of multiple years of being suspended. As mentioned in Chapter 2, research suggests that additional each year of suspension further increases adverse outcomes for students. Future research using this data should improve upon this study’s methods by combining suspension data across grade levels to create a comprehensive suspension record for each individual student.
Because the dataset did not include details on the nature of the infraction, this study can also not rule out school misbehavior that led to consequential criminal conviction. The data does
have the date that the criminal conviction charged originated. If dates can be acquired for school discipline, then instances in which a student’s punishment was referred to the adult criminal justice system can be eliminated from future analysis.
Additionally, this study was not able to investigate if there is a difference in effect between a short-term and a long-term suspension. Research shows that long-term suspensions, which are typically defined as disciplinary action that excludes a student from school for more than 10 school days, lead to more adverse outcomes for students compared to short-term
suspensions. Although there is a “days suspended” variable in the dataset, this variable measured cumulative days suspended throughout the year rather than the length of an individual
suspension. Future research should seek to see if the association between suspension and conviction is stronger for long-term suspensions.
Implications for Policy and Future Research
As one of the first analyses of its kind, this study contributes to a growing body of research on the negative effects of school suspension by adding evidence that there is a strong association between school suspension and criminal conviction. According to the predictions of this study, experiencing in-school suspension increases the likelihood that the average student will be convicted of a misdemeanor or a felony by a factor of 1.8, and experiencing out-of-school suspension increases the likelihood that the average student will be convicted of a misdemeanor or a felony by a factor of 3.1 and 3.6, respectively. Future research will have to investigate if these figures hold in other states and academic contexts. Further uncovering this relationship will help school officials and education advocates better know what the mechanisms of the
metaphorical school-to-prison pipeline look like and how much we are putting our children at risk by suspending them.
As stated in discussion section, the results of this study, as well as all previous research on the topic, should cause alarm. Not only is school discipline applied to disadvantaged students at disproportionate rates but it also is strongly associated with criminal conviction. The analyses on out-of-school suspension are particularly concerning. Racial gaps are larger in the distribution of out-of-school suspension than in-school suspension, and out-of-school suspension also has more serious adverse affects. As illustrated in Figure 12, the likelihood of being convicted of a felony for the average student increases dramatically with each additional out-of-school suspension.
Similar to other research conducted on exclusionary school discipline, these results call into question the effectiveness and value of out-of-school suspension. In recent years, many communities have been experimenting with alternatives to out-of-school suspension. In “Instead of Suspension,” researchers from Duke Law School and Duke Center for Child and Family Policy describe in-detail 11 alternative strategies for effective school discipline (Owens,
Wettach, & Hoffman, 2015). Of these, the most commonly discussed alternative to suspension in the school-to-prison pipeline literature is restorative justice. Restorative justice practices aim to change student behavior by requiring students to face the people who have been harmed by their actions (Owens, Wettach, & Hoffman, 2015). Although this technique can be implemented in many forms, the most common restorative justice practice is the peer jury, in which misbehaving students face a panel of five or six students who recommend the appropriate punishment (Owens, Wettach, & Hoffman, 2015). Research shows that school districts that implement restorative practices see lower suspension rates, decreases in racial disparities in the distribution of
suspension, and increases in school safety through a reduction of misbehavior (Owens, Wettach, & Hoffman, 2015). Schools in North Carolina have seen success, too. The Juvenile Justice Project at Campbell Law School offers free conflict resolution services at seven middle and high
schools in Wake County. One study from this project showed that students who attended a face- to-face meeting with their victim were three times less likely to have future conflicts than students who did not engage in restorative justice techniques (Owens, Wettach, & Hoffman, 2015).
After seeing a rise in suspensions and expulsions from 2001 to 2005, Denver Public Schools began implementing restorative practices starting in 2003 (Losen, 2014). The district created a multi-year plan that incorporated policy changes that encouraged alternative responses to misbehavior at the district- and school-level, particularly targeting schools in the district that had high rates of racial disproportionality in discipline (Losen, 2014). Even during the beginning stages of the plan, DPS was able to reduce racial disparities in school discipline every year for each racial group, and today researchers point to this case as one of the most successful wide- scale school discipline reforms (Losen, 2014). Many researchers on restorative justice practices argue that the development of comprehensive, multi-level plan is crucial to the successful implementation of the practices, and “multi-level” also means having supports outside of the school (Losen, 2014). As Losen (2014) points out, part of DPS’s success is attributable to their sustained partnership with a local nonprofit, Padres y Jóvenes Unidos. Padres y Jóvenes Unidos not only provided significant input and guidance on the development of effective and culturally responsive discipline strategies but they also raised external pressure that created accountability for DPS (Losen, 2014).
Another common alternative to exclusionary school discipline is Positive Behavior Intervention and Support (PBIS). PBIS’s programs seek to establish clear behavioral
expectations for students and set out incentives to positively encourage that behavior (Owens, Wettach, & Hoffman, 2015). As a part of PBIS, a school teacher might publicly acknowledge
when one of their students meets or exceeds behavioral expectations to encourage their peers to do the same. PBIS programs have been implemented in schools nationwide, and in 2005 an initiative in North Carolina sought to encourage administrators to adopt PBIS in their own schools. By the 2011-12 school year, 1,154 schools across North Carolina had initiated the adoption of PBIS, which is almost half of the state’s schools (Owens, Wettach, & Hoffman, 2015). Research conducted in North Carolina has shown that PBIS significantly improves academic outcomes of schools, decreases rates for suspension, expulsion, and office referrals, and reduces the amount of time administrators spend on discipline (Owens, Wettach, & Hoffman, 2015).
To tackle these national trends in school discipline, there is no one-size-fits-all approach (Losen, 2014). Long-term, school districts across the country will need to develop locally
tailored solutions that target student behavior and teacher behavior. For example, comprehensive implicit bias and cultural responsiveness training for teachers has been shown to decrease the disparities in the distribution of discipline (Barnes & Motz, 2018). At the district-level school districts will also likely need to review their own policies to ensure definitions of misbehavior are not culturally biased (Barnes & Motz, 2018). In the years to come, as we learn more about the mechanisms of the school-to-prison pipeline through research, we will also learn more about proven effective strategies to combat these trends.
Appendix
Table 1: Adjusted Logit Coefficient Estimates from Models Predicting Suspension
( 1 ) ( 2 ) Number of obs: 100,470 Out-of-School Suspension 9th In-School Suspension 9th Race Black 0.598*** 0.171*** 0.037 0.037 Hispanic 0.034 -0.04 0.059 0.058 Asian -0.465** -0.985*** 0.181 0.207 Native American 0.482*** -0.037 0.103 0.114 Multiracial 0.566*** 0.4*** 0.077 0.076 Sex Male 0.526*** 0.352*** 0.034 0.032
Race & Sex Interaction
Black Male -0.253*** -0.136** 0.046 0.047 Hispanic Male 0.045 0.032 0.07 0.069 Asian Male -0.348 0.229 0.234 0.253 Indian Male -0.018 -0.355* 0.138 0.156 Multiracial Male -0.308** -0.248* 0.104 0.103 School Affluence High -0.219*** -0.218*** 0.033 0.032 Low .163*** -0.121*** 0.025 0.026 Continued
Table 1 (continued)
( 1 ) ( 2 )
Out-of-School
Suspension 9th In-School Suspension 9th
Other Controls
Free and Reduced Price Lunch 0.486*** 0.528***
0.024 0.024
Disability 0.025 0.03
0.032 0.032
Limited English Proficiency -0.243*** -0.191***
0.055 0.056 Academic Achievement -0.546*** -0.485*** 0.013 0.013 Suspension 8th 1.418*** 1.297*** 0.024 0.022 Days Absent 8th 0.032*** 0.022*** 0.001 0.001
Early College High School 9th -0.59*** -1.84***
Table 2: Predicted Means Estimates from Models Predicting Race and Sex’s Effect on Criminal Conviction
( 1 ) ( 2 )
Out-of-School
Suspension In-School Suspension
White male Adjusted margin 0.148 0.138
Unadjusted margin 0.125 0.123
Number of obs. 29,584 29,584
White female Adjusted margin 0.101 0.105
Unadjusted margin 0.064 0.074
Number of obs. 28,061 28,061
Black male Adjusted margin 0.186 0.141
Unadjusted margin 0.312 0.221
Number of obs. 14,545 14,545
Black female Adjusted margin 0.155 0.12
Unadjusted margin 0.211 0.155
Number of obs. 14,172 14,172
Hispanic male Adjusted margin 0.156 0.137
Unadjusted margin 0.198 0.17
Number of obs. 5,831 5,831
Hispanic female Adjusted margin 0.104 0.102
Unadjusted margin 0.106 0.104
Number of obs. 5,610 5,610
Asian male Adjusted margin 0.082 0.076
Unadjusted margin 0.046 0.044
Number of obs. 1,289 1,289
Asian female Adjusted margin 0.071 0.046
Unadjusted margin 0.029 0.02
Number of obs. 1,223 1,223
Table 2 (continued)
( 1 ) ( 2 )
Out-of-School
Suspension In-School Suspension
Native American
male Adjusted margin 0.181 0.102
Unadjusted margin 0.297 0.166
Number of obs. 851 851
Native American
female Adjusted margin 0.143 0.102
Unadjusted margin 0.202 0.139
Number of obs. 848 848
Multiracial male Adjusted margin 0.175 0.154
Unadjusted margin 0.201 0.174
Number of obs. 1893 1893
Multiracial
female Adjusted margin 0.152 0.143
Unadjusted margin 0.143 0.136
Figure 1: Predicted Means of Suspension for Male Students, by Race and Economic Status
Figure 2:Predicted Means of Suspension for Female Students, by Race and Economic Status 0.00 0.05 0.10 0.15 0.20 0.25 Not Economically
Disadvantaged DisadvantagedEconomically Not Economically Disadvantaged DisadvantagedEconomically In-School Suspension Out-of-School Suspension
Pr edi ct ed M ea ns
Predicted Means of Suspension for Male Students, by
Race and Economic Status
White Black Hispanic Asian Native American Multiracial
0.00 0.02 0.04 0.06 0.08 0.10 0.12 0.14 0.16 0.18 0.20 Not Economically Disadvantaged Economically Disadvantaged Not Economically Disadvantaged Economically Disadvantaged In-School Suspension Out-of-School Suspension
Pr edi ct ed M ea ns