Elsevier

Journal of Criminal Justice

Volume 83, November–December 2022, 101983
Journal of Criminal Justice

Infrastructure of social control: A multi-level counterfactual analysis of surveillance and Black education

https://doi.org/10.1016/j.jcrimjus.2022.101983Get rights and content

Highlights

  • All else equal, suspension rates are higher in high versus low surveillance schools.

  • Blacks are four times more likely to attend a high versus low surveillance school.

  • High surveillance schools lower all students' math scores and odds of college entry.

  • Between-school variation in math scores increases once suspensions are controlled.

Abstract

In response to the continued reoccurrence of school shootings, policymakers have increased surveillance measures to ensure safer learning environments. However, in addition to being used to preempt school shootings, these surveillance measures may have increased the capacity of schools to identify and punish students for more common and less serious offenses, which may negatively impact the learning environment. Using counterfactual and multi-level modeling strategies with national survey data, we show that schools ranking highest in surveillance infrastructure suspend more students than schools that rank among the lowest in their surveillance capability, even when controlling for school social disorder and student misbehavior. In addition to suspending more students, the infrastructure of surveillance reduces test scores in mathematics and college enrollment altogether for suspended and non-suspended alike, suggesting the presence of negative spillover effects. We conclude that the “safety tax” students pay with their average levels of test performance and college going rates is greatest for Black students of both genders given their overrepresentation in high-surveillance schools. The article concludes with a discussion of control wave theory and the study's implications for policy and practice.

Introduction

In response to the continued reoccurrence of school shootings, policymakers have increased surveillance measures to ensure safer learning environments (Johnson Jr., Jabbari, Williams, & Marcucci, 2019; Muschert, Henry, Bracy, & Peguero, 2014). These measures can include detection mechanisms (e.g. metal detectors and drug sniffing dogs), security personnel (e.g. school resource officers), visual monitors (e.g. security cameras), and even restrictions on cultural expressions (e.g. strict dress codes) (Addington, 2009; Muschert et al., 2014). While public dialogue has questioned whether these additional measures of surveillance make schools safer (Price & Khubchandani, 2019; Skiba & Rausch, 2006), it is also important to know the impact of surveillance measures on the academic wellbeing of students—especially when considering educational outcomes are powerful social determinants of incarceration risks (Couloute, 2018), high-risk health behaviors (CDC, 2020), and life-course health outcomes (Jones et al., 2019; Olshansky et al., 2012; Ross & Wu, 1995). Yet, research has focused more on punishment's impact on students (Peguero, Portillos, & Gonzalez, 2015), including which students are more likely to be punished and by what means (e.g. exclusion, arrest, etc.), rather than how a school's surveillance apparatus may influence student outcomes—both through detection and punishment and independent of punishment. As some policymakers are now implementing artificial intelligence (AI) systems within schools that collect biometric information and profess to have emotion recognition capabilities for predictive care (Ascione, 2019; Ropke, 2019), there is an urgent need for research that can demonstrate not only the impact of the surveillance systems currently in use, but also the mechanisms through which they affect education, a key life-course determinant.

To fill this gap in research, we explore the degree to which surveillance apparatuses relate to a range of student outcomes. We refine our interests in surveillance with a focus on the intersectional social locations of race and gender for Black adolescents for a few reasons. First, the Federal Bureau of Prisons reports that, in 2022, 38.3% of federal inmates were Black (Federal Bureau of Prisons, 2022). At the state level, Black Americans were incarcerated at a state average of 1240 per 100,000 residents in that same year, and Latinx and White non-Latinx Americans at a rate of 349 and 261 per 100,000, respectively (Mendel, 2022). Second, Black students are not only impacted via the disproportionate rates at which their parents are incarcerated, but also by parallel systems of disproportionate surveillance, punishment, and arrest in their neighborhoods (Brunson, 2007; Brunson & Miller, 2006) and schools (Ferguson, 2001; Office for Civil Rights, 2021; Shedd, 2015; Skiba, Michael, Nardo, & Peterson, 2002). Furthermore, punishment is often applied differently across gender (Annamma et al., 2019; Ferguson, 2001; Noguera, 2009; Wun, 2018), potentially leading to differences within race.

Rather than focusing exclusively on individual level determinants of these racial and gender disparities, this analysis considers whether the school's surveillance infrastructure has an impact on suspension rates, math test scores, and college attendance independent of student behavior and their experiences with discipline. We do so using the Educational Longitudinal Survey of 2002 (ELS) collected by the National Center for Education Statistics, and a research methodology that features a counterfactual and multi-level modeling approach. The ELS is ideal for an analysis of this type since it is one of the only federal datasets that has both school-level surveillance measures and student-level outcomes. Using these data, we demonstrate that with the infrastructure of surveillance in place, students are more likely to be suspended even when controlling for school social disorder and student misbehavior. In addition to placing more students on the discipline track, spillover effects occur within high surveillance high schools, resulting in reduced mathematics performances and college enrollment for suspended and non-suspended students alike. In sum, students in high surveillance high schools pay a safety tax, which is compounded once they receive the punishment for behavior that the surveillance detected. This is most true for Black students, who were four times more likely than not to attend high surveillance high schools. Revisiting Ditton's (1979) control wave theory, this article concludes with a discussion of implications for practices and policies in relation to the intersectional experiences and wellbeing of Black adolescents.

Section snippets

Literature review

This analysis builds on three theoretical perspectives and an interdisciplinary body of research that relates student behavior and school practices and policies to intersectional disparities. Beginning with social control, the concept refers to the social forces that allow a society, culture, or organization to internally regulate the behavior of its membership (Hughes, 1946). Social control has been theorized to reduce anti-social behavior, maintain social order, and ultimately, enhance the

Data

This study utilized restricted-use data from the National Center for Education Statistics' (NCES) Educational Longitudinal Study of 2002 (ELS). The ELS is an ideal dataset for understanding social control, as it is one of the most recent NCES dataset that collected data using a facilities checklist. We initially considered the High School Longitudinal Study, 2009, to address these questions and learned it did not utilize the NCES facilities checklist to collect data. The facilities checklist,

Results

In addition to the outcomes of variable balancing in the propensity score weighting process, Table 2a also reveals the largest pre- and post-weighted treatment difference is in the proportion of students who attend high surveillance schools who are Black. Prior to propensity score weighting, 24% of students within high surveillance schools (HSS) were Black, despite the population being only 12% of the total sample—this is four times larger than the percent of students in low surveillance

Discussion

The goal of this study was to understand how students' discipline, mathematics, and college attendance outcomes are impacted by attending a high school that has a relatively prominent surveillance infrastructure to achieve formal social control. This study has several key takeaways and implications to consider. First, the study findings demonstrate that with apparatuses of surveillance in place, students are more likely to be suspended—even when controlling for school social disorder and

Acknowledgements

This work was supported by the National Science Foundation [EEC-1619843].

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