Despite the general agreement that US schools have become increasingly punitive since the 1980s, researchers are uncertain about what types of schools use tough-on-crime measures. Some assert that punitive control is concentrated in poor, predominantly ethnic minority schools. Governing-through-crime scholars argue that US schools with mostly middle-class and white students are also punitive, but in less harsh ways using soft surveillance techniques. Relying on data from large, stratified samples of middle and secondary US public schools, we found that high rates of ethnic minority enrollment predicted heavy reliance on law enforcement and security personnel. As rates of student poverty increased, use of soft surveillance techniques as well as reporting students to the police significantly increased. Implications for governing-through-crime, racial control, and reproduction of inequalities theories are discussed.
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We prefer the racialized crime theories to racial threat theories, because classic racial threat perspectives assume a curvilinear relationship between minority group size and social control, which does not seem to occur in schools (see Welch and Payne 2010). Also, racialized control theories analyze the historic mechanisms of racial control in America (see Hawkins 2011) rather than shifts in the size of minority population in a given area.
Although we have presented race and class-based perspectives as independent, contemporary critical criminologists (see Burgess-Proctor 2006)—along with many critical theorists in general (see Collins 1991; Hancock 2007; Landry 2007; Pascale 2007)—view class and race (and gender) as interacting and overlapping forces. We separate our race and class-based inequalities and punishment arguments in this manuscript for clarity and by doing so do not mean to suggest that punishment scholars have not addressed overlap in systems of oppression. Despite acknowledging overlap here, we have decided not to offer or test a hypothesis regarding race and class interaction in this study for two reasons. First, there is no empirical evidence to support an interaction analysis. Past scholarship looking at race and class interaction effects in school punishments have failed to find interaction effects to be significant (Welch and Payne 2010). Second, even if there were empirical support to conduct an interaction effects analysis, we would be unlikely to find a RaceXClass variable to be significant. Theories addressing interlocking systems of oppression are extremely complex (see McCall 2001) and therefore race and class overlap or interconnections are not likely to be accurately represented in a single “RaceXClass” variable (at least not ones developed from the data available).
Hirschfield (2008) concludes that the accountability thesis is probably not correct because accountability predicts more, rather than less, discretion in schools. The popularity of zero tolerance since the 1990s suggests that there has been less discretion in school discipline practices across the US.
According to information from state legislatures (www.ncsl.org, retrieved 9/15/2006 and 6/05/2012), between April 20, 1999 (the date of the Columbine shootings) and June 5, 2012, 44 states passed legislation to combat school violence. Only 6.8 % of these states (n = 3) passed legislation between 1999 and 2000, while 63.6 % (n = 28) of these states passed legislation between 2001 and 2007. A remaining 29.5 % (n = 13) passed legislation after 2007. Because the vast majority of state-level legislative changes occurred after 2001, we argue that 1999–2000 is an adequate baseline year to test the hypothesis that repressive measures to combat school violence have been amplified in the years after Columbine. In addition, our 1999–2000 school year data is sufficient to test changes since the September 11th, 2001 terrorist attacks and the NCLB act of 2001 (which was signed into law in January of 2002).
As noted previously, our study was not designed to test theories of race and class interaction in school punishments. Given that past scholarship used but did not find a race and class interaction variable to be significant in punishment models (Welch and Payne 2010), we were curious about whether a race and class interaction variable would be significant in our models. Although not shown in this study, we ran this interaction variable in all of our models and it was not significant in any of them.
For example, in June 5–7 of 1998, 37 % of parents surveyed answered “yes” to the question “thinking about your oldest child, when he or she is at school, do you fear for his or her physical safety?” In contrast, 55, 52, and 43 % of parents surveyed answered “yes” to this question on April 21, 1999, May 21–22, 1999, and April 7–9, 2000, respectively (Gallup 2011).
This lack of data is consequential. For example, education statistics in the US (US Department of Education 2000, 2006) indicate that, between 2000 and 2006, African American students made up a larger percentage of students who were cut off from education services entirely (e.g., an increase from 29 to 46 %). From 2000 to 2006, the percentage of African American students in public schools dropped from 16.6 to 15.6 % (National Center for Education Statistics 2010). The lack of data mentioned here means that we cannot discern whether there is a connection between reliance on punitive measures and the increasing rate of exclusion of African Americans from public schools.
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Irwin, K., Davidson, J. & Hall-Sanchez, A. The Race to Punish in American Schools: Class and Race Predictors of Punitive School-Crime Control. Crit Crim 21, 47–71 (2013). https://doi.org/10.1007/s10612-012-9171-2
- White Student
- Critical Criminologist
- Harsh Punishment
- Ethnic Minority Student
- School Discipline