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Visible School Security Measures and Student Academic Performance, Attendance, and Postsecondary Aspirations

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Abstract

Many U.S. schools use visible security measures (security cameras, metal detectors, security personnel) in an effort to keep schools safe and promote adolescents’ academic success. This study examined how different patterns of visible security utilization were associated with U.S. middle and high school students’ academic performance, attendance, and postsecondary educational aspirations. The data for this study came from two large national surveys—the School Crime Supplement to the National Crime Victimization Survey (N = 38,707 students; 51 % male, 77 % White, MAge = 14.72) and the School Survey on Crime and Safety (N = 10,340 schools; average student composition of 50 % male, 57 % White). The results provided no evidence that visible security measures had consistent beneficial effects on adolescents’ academic outcomes; some security utilization patterns had modest detrimental effects on adolescents’ academic outcomes, particularly the heavy surveillance patterns observed in a small subset of high schools serving predominantly low socioeconomic students. The findings of this study provide no evidence that visible security measures have any sizeable effects on academic performance, attendance, or postsecondary aspirations among U.S. middle and high school students.

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Notes

  1. Although it is possible for the same adolescent to have been interviewed across multiple data collection periods, the national sampling frame of the SCS surveys means the probability of such overlap is small and the de-identified nature of the data makes it impossible to discern whether the same students were surveyed in multiple years.

  2. Although the SSOCS surveys include Common Core of Data identification numbers that allow linkage of SSOCS respondents (i.e., schools) longitudinally over time, the national sampling frame of the SSOCS surveys means that the probability is quite small for any overlap of schools across survey years.

  3. Indeed, this quasi-experimental design can minimize the impact of selection bias and confounding even more than simply using the baseline covariates as statistical controls in the regression models. This latter approach would not account for variability in the magnitude or direction of the effects of those covariates across the different security utilization patterns.

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Acknowledgments

The research reported here was supported by the Institute of Education Sciences, U.S. Department of Education, through Grant R305A120181 to Vanderbilt University. The opinions expressed are those of the authors and do not represent views of the Institute or the U.S. Department of Education. The authors would also like to thank Mark Lipsey and two peer reviewers for their comments on earlier drafts of the manuscript.

Author Contributions

ETS conceived of the study, participated in its design and coordination and drafted the manuscript; BWF participated in the analysis and interpretation of the data and helped to draft the manuscript. All authors read and approved the final manuscript. All authors declare no conflicts of interest.

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Correspondence to Emily E. Tanner-Smith.

Appendix

Appendix

See Tables 4, 5, 6.

Table 4 Variables used in propensity score models
Table 5 Effects of visible security measures on academic outcomes, SCS student surveys (N = 38,707)
Table 6 Effects of visible security measures on academic outcomes, SSOCS administrator surveys (N = 10,340)

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Tanner-Smith, E.E., Fisher, B.W. Visible School Security Measures and Student Academic Performance, Attendance, and Postsecondary Aspirations. J Youth Adolescence 45, 195–210 (2016). https://doi.org/10.1007/s10964-015-0265-5

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