How Student Vape Detection Technologies Threaten to Expand the School-to-Prison Pipeline in Minnesota and Beyond
ENDING YOUTH SURVEILLANCE
ABOUT THE NOTICE COALITION
The NOTICE Coalition (No Tech Criminalization in Education) is a national network of advocates, researchers and organizers building a movement to end police surveillance in schools and defend youth justice in the digital age. We seek to empower Black, Brown, Indigenous, disabled, and LGBTQIA+ youth and youth from other historically marginalized communities to imagine and build liberated futures. Since 2021, the NOTICE Coalition has sounded the alarm of the impact of school surveillance, digital pushout, and data criminalization on youth and young adults from marginalized communities.
ABOUT THE AUTHORS
ELLIE SPANGLER is an undergraduate student at Macalester College. She leverages her firsthand experience with educational surveillance technologies to drive informed research and advocacy, focusing on equitable, data-driven policy solutions.
CLARENCE OKOH is Senior Attorney at the Georgetown Law Center on Privacy and Technology. He works in collaboration with community partners to address the civil rights and racial justice implications of emerging technologies in communities of color and other historically marginalized groups.
MARIKA PFEFFERKORN is the Executive Director of the Midwest Center for School Transformation (MCST), Solutions and Sustainability Officer at the Twin Cities Innovation Alliance (TCIA), and co-founder of the No Tech Criminalization in Education (NOTICE) Coalition. She is an interdisciplinary and cross-sector thought leader in education and technology. She works to transform systems through collaborative, creative, and restorative approaches while focusing on shaping a future that serves the public good.
ACKNOWLEDGEMENTS
The authors of this report would like to acknowledge the following individuals and organizations for their contributions to developing this report: Ed Vogel, Dr. Catherine Squires, the Twin Cities Innovation Alliance, and all others who supported the development and release of the report.
3
CONTENTS Executive Summary 4
Findings
Context: The surge in youth vaping in the U.S. 6
Vape detection technology 7 How schools use vape detection technology
Political and financial influences on school security
Vape detection in Minnesota’s K-12 schools
Implications of increased school surveillance 11 Student privacy
School-to-prison pipeline and demographic disparities
Legal implications
Case Study: Cullman County’s “Vape Court”
Overlooking mental health and addiction support 13 Effectiveness and limitations of vape detectors
Alternative strategies for reducing vaping
Conclusion 14
Appendices 15
Endnotes 18
ENDING YOUTH SURVEILLANCE
Report Series
4
EXECUTIVE SUMMARY Motivated by more than a decade of school shooting tragedies, policymakers across the United States have made unprecedented investments in school surveillance technologies. School surveillance technologies introduce serious privacy, civil rights, and ethical challenges that directly shape the lives of vulnerable youth and young adults.
In this report, we highlight a growing trend in school surveillance across the United States: automated vape detection systems. Schools use automated vape detection sensors to enforce prohibitions on student e-cigarette use. Vape detection technologies use special sensors and complex algorithms to monitor air quality and detect the use of e-cigarette vapors and related prohibited substances. Sensors are often installed in school bathrooms, locker
rooms, and other sensitive locations and paired with nearby surveillance cameras to identify students in the vicinity of an alert. Vape sensors generate automatic alerts to school officials, including school-based police, which can result in disciplinary actions against students. Vape detection systems offer a range of controversial add-on surveillance features including speech recognition, “aggression” detection, and facial recognition. Over 1,500 school districts across the United States have purchased vape detection systems.1
In this report, we specifically examine the scope and prevalence of vape detection technologies in Minnesota public schools and offer a socio-technical analysis to better position student activists, parents, educators, advocates and policymakers to understand the potential of this technology to expand the school-to-prison pipeline and systematically violate students’ privacy rights.
OUR FINDINGS For this report, we investigated the scope and prevalence of vape detection in public schools in the state of Minnesota with a focus on the privacy and education equity implications of these systems. We examined school procurement and contract data with vape detection companies; submitted open records requests to understand vendor marketing practices; and researched public grant programs and other funding sources enabling schools to purchase these systems. We reviewed the public health literature on best practices to respond to young adult substance abuse. We also examined the civil and privacy rights protections implicated by school vaping practices.
KEY FINDINGS INCLUDE:
» Between 2019 to 2023, at least 43 school districts in Minnesota procured automated vape detection technology and services. These school districts collectively enrolled over 853,000 students in 2023.
» Since 2019, Minnesota school districts have spent over $442,000 on automated vape detection technology and services from private companies.
School districts in Minnesota
43
853,000 Students impacted by these technologies statewide
$442,000 Spent on vape detection technology from 2019 to 2023
+3%
+121%
From 2016 to 2022, student e-cigarette use increased just 3%, but the number
of students disciplined for tobacco use soared 121% in
Minnesota schools.
» Some automated vape detection systems contain controversial surveillance capabilities including facial recognition, “aggression detection” and video integration with “artificial intelligence-powered” camera systems
» Between 2016 and 2022, the number of students disciplined for tobacco use in Minnesota nearly doubled from 2,355 students to 5,202 students– even as the rate of student e-cigarette use only increased by 3% during the same time period.
» Student tobacco use is the fourth leading cause of student discipline in Minnesota.
» Beyond Minnesota, several school districts have taken zero tolerance approaches to student vaping, including: suspensions, law enforcement referrals, legal fines, probation and incarceration for student e-cigarette use.
» School district funding sources for automated vape detectors are varied and include state, federal and philanthropic grant programs.
» Public health research makes clear that punitive approaches to student substance use are associated with increased substance use, depression, social isolation, and disconnect from peers and educators.
6%
71%
In 2024, 6% of U.S. students reported vaping, but 71% of youth had been exposed to
e-cigarette marketing
CONTEXT: YOUTH VAPING IN THE UNITED STATES Student use of e-cigarettes, commonly referred to as “vaping,” has emerged as a pressing public health concern in schools across the United States. E-cigarette companies have made considerable investments to target their products to youth and young adults.2 As a consequence, vaping is notably higher among youth and young adults compared to the general adult population, making it the most commonly used tobacco product among young people.3
Consider the following:
» In 2024, 5.9% of students, equivalent to 1.63 million young people, report using e-cigarettes. This includes 7.8% of high school students and 3.5% of middle school students.4
» A 2024 study found that a total of 70.7% of youth and 73.9% of young adults who had never used tobacco—roughly 11 million and 7 million people in the United States, respectively—indicated exposure to e-cigarette marketing in the past month. This exposure is uneven across different racial and ethnic groups. Non-Hispanic African American youth (ages 12-17) reported higher levels of marketing exposure compared to their non- Hispanic white peers, although this trend reverses among young adults.5
» Between January 2020 and December 2022, e-cigarette unit sales surged by 46.6%, with a marked shift toward disposable vaping devices with youth-appealing flavors like fruit and sweets.6
» E-cigarette unit sales grew by 46.1% between February 2, 2020, and September 10, 2023, rising from 15.7 million to 22.9 million units.7
» Vaping poses serious health risks for youth and young adults, including nicotine addiction8, impaired brain development9, respiratory issues10, and an increased risk of psychiatric disorders and cognitive impairments later in life.11
African American youth report higher levels of
marketing exposure than non-Hispanic white peers.
15.7M
22.9M
E-cigarette sales grew 46% from Feb 2020 to
Sept 2023, rising from 15.7 million to 22.9 million units.
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WHAT IS VAPE DETECTION TECHNOLOGY? In response to rising vaping rates, schools have adopted various measures, including the deployment of vape detectors. These devices are designed to monitor and detect vaping activities in areas where traditional surveillance, like cameras, is impractical. Vape detectors use particulate matter (PM) sensors and volatile organic compound (VOC) sensors to identify vaping aerosols.12 PM sensors detect tiny aerosol particles, while VOC sensors identify chemical compounds associated with vaping.13 Advanced models incorporate machine learning algorithms to improve accuracy and reduce false positives.14 When vaping is detected, these systems can alert administrators in real-time and even trigger audible alarms for deterrence.15
Vape detectors operate through a combination of sensors and algorithmic technologies:
» Particulate Matter (PM) Sensors: Utilize laser scattering to measure aerosol particle size and concentration.
» Volatile Organic Compound (VOC) Sensors: Detect chemical compounds by reacting with Metal Oxide Semiconductors, altering electrical resistance based on VOC levels.
» Machine Learning: Enhances detection accuracy by distinguishing vaping from other aerosols over time.
» Other Surveillance Features: Some vape detectors also include additional features such as sound detection for abnormal activities like gunshots or shouting, keyword detection for phrases like “help me” or “stop it,” tamper alarms, and environmental monitoring for air quality.16
PARTICALE MATTER SENSORS Utilize laser scattering to measure aerosol particle size and concentration
VOLATILE ORGANIC COMPOUND SENSORS Detect chemical compounds by reacting with semiconductors
MACHINE LEARNING Enhances detection accuracy by distinguishing vaping from other aerosols over time
OTHER SURVEILLANCE Additional features such as sound detection for abnormal activities like gunshots or shouting, keyword detection for phrases like “help me” or “stop it,” tamper alarms, and environmental monitoring for air quality
HOW VAPE DETECTORS WORK
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HOW DO SCHOOLS USE VAPE DETECTION TECHNOLOGY? School officials procure vape detection technologies from commercial vendors. In some instances, companies will provide a “free trial” for the use of the technology before schools purchase the system in full. The total price of vape detectors can vary, but typically range between $1,025 to $5,700.
Once a vaping system is purchased, customers have flexibility to determine where the technology is installed, the level of sensitivity for the sensors, and whether to add other surveillance features to sensors. Schools often install these systems in areas where they believe students are prone to vape, including bathrooms, locker rooms and other sensitive locations. Once installation is complete, the sensors monitor the environment to detect the presence of air particulates that correspond to vape use. If the sensor detects e-cigarette vapors it will automatically generate a report of alleged vaping to school officials–in some cases school-based police. Some systems even provide automatic video recording at the time of the alert to identify students in the vicinity of the vaping episode.
POLITICAL AND FINANCIAL INFLUENCES ON SCHOOL SECURITY The adoption of surveillance technologies in schools is heavily influenced by the lobbying efforts of commercial vendors.17 In 2018, security trade organizations were instrumental in securing hundreds of millions in funding for school safety initiatives.18 These efforts culminated in additional legislative actions, such as the $300 million allocated in June 2022 to enhance school security.19 Similar lobbying activities at the state level have successfully garnered substantial grant funding.20
These initiatives have boosted revenues for the EdTech surveillance sector by making its products more accessible and affordable, sometimes even free, for schools.21 These companies invest millions to persuade state legislators to fund their products, often overshadowing research-based best practices in school safety.22 As a result, schools may allocate resources to high-tech surveillance rather than more effective, supportive safety strategies, such as youth cessation programs and peer support models.
Federal funding from the Department of Justice23, Department of Education24, and the Department of Homeland Security25 further fuels this trend. In Minnesota, schools have utilized grants from sources like the Hometown Health Grant, COVID Care Act, and Minnesota’s Safe School Levy to invest in vape detection technologies.
The adoption of surveillance technologies in schools is heavily influenced by the lobbying efforts of commercial vendors. These efforts have resulted in legislative actions, such as $300 million allocated in June 2022 to enhance school security.
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VAPE DETECTION IN MINNESOTA’S K-12 SCHOOLS The growing investment in school surveillance technology in Minnesota reflects broader national patterns of growth within the industry.26 Our investigation into the growing trend of vape detectors in Minnesota schools sought to understand the scale of the investment and its implications for student privacy, school culture, and the financial priorities of educational institutions.
We analyzed data from GovSpend to track school districts’ purchases of vape detection software between 2019 and 2023. The trend towards increasing purchases is evident, with the number of purchases and total spending rising each year.
Between 2019 and 2023 the total statewide expenditure on vape detection by Minnesota school districts exceeded $442,300–with statewide expenditures rising each year.27 This surge in investments underscores the growing concern among school districts about the impact of vaping on students and their rights.
Consider the following findings:
» The largest singular purchaser of automated vape detection technology and services was the Eden Prairie School District which has spent over $89,000 on Soter Technologies Flysense Vape Detector since 2020.28
» Commercial vendors and hardware providers present in Minnesota schools include: Zeptive, Verkada, Halo, Freedom Security and Surveillance, L And A Systems, Lightspeed Electric, Parallel Technologies and Soter Technologies.
» Number of purchases per year increased from 6 districts statewide in 2019 to 22 school districts in 2023.29
6 8 9
18 22
$27,574
$90,271
$29,485
$106,585
$189,142
2019 2020 2021 2022 2023
number of school districts
spending on vape detection technology
From 2019 to 2023, total statewide spending on vape detection technology by Minnesota school districts exceeded $442,300 – with expenditures rising each year.
10
TOTAL SPENDING BY SCHOOL DISTRICT
MN SCHOOL DISTRICTS THAT HAVE PURCHASED VAPE DETECTION TECHNOLOGY
2019 2023
6 43
IMPLICATIONS OF INCREASED SCHOOL SURVEILLANCE
STUDENT PRIVACY While vape detectors are marketed as tools to combat student vaping, their implementation often extends into broader, more intrusive surveillance practices that raise serious privacy concerns. Originally designed to detect vaping aerosols and alert school officials, these detectors are increasingly being integrated into expansive security systems. These systems often include video management systems (VMS) that connect the vape sensors to strategically placed cameras, such as those outside bathrooms. This setup allows school administrators not only to detect vaping but also to visually monitor and identify students, effectively broadening the scope of surveillance far beyond its initial purpose: to deter vaping. This method subjects students to continuous monitoring and recording, frequently without their knowledge. The growing integration of facial recognition technology with school security cameras further exemplifies this trend towards pervasive surveillance.30
THE SCHOOL-TO-PRISON PIPELINE & DEMOGRAPHIC DISPARITIES The school-to-prison pipeline refers to the connection between exclusionary school discipline and student involvement in the juvenile and adult criminal legal systems.31 Beginning in the 1970s, racial anxieties over school integration led to an era of draconian school discipline practices targeting Black, brown and Indigenous youth–punitive measures that often mirrored and contributed to the birth of mass incarceration in the United States.32 The adoption of “zero tolerance” policies, investment in “school hardening,” and expansion of law enforcement presence on campus dramatically expanded
the capacity of schools to surveil, discipline and criminalize students – often for benign conduct associated with normal youth development.33
Researchers and advocates have consistently found that repeated exposure to exclusionary discipline creates barriers to academic success, undermines student mental wellness, deteriorates social relationships and students’ sense of belonging, while also systematically abridging their rights.34 Nonetheless, the school pushout crisis remains an acute challenge in public education as school districts turn to new data-driven policing practices and surveillance technologies to reinforce long standing histories of educational inequity. Exclusionary discipline has, and continues, to disadvantage students of color, students with disabilities, and students who are queer, trans and gender nonconforming.35
The expansion of surveillance in school settings threatens to usher the school pushout crisis into the digital age. Minnesota schools continue to discipline and punish students of color at significantly higher rates than their peers. In 2017, the Minnesota Department of Human Rights found that several school districts across the state disciplined Black students at rates 8x to 10x the rate of white students in extreme cases.36 Since then, 41 school districts entered into settlement agreements with the state to address these disparities.37 Several school districts subject to state monitorship for racialized disciplinary practices made significant investments in automated vape detection systems including Eden Prairie, Osseo, and Bemidji. The disproportionate application of surveillance measures on underrepresented students is a dangerous possibility that threatens to exacerbate existing inequalities within the education system.
Vape sensors are often connected to cameras so school
administrators can visually monitor and identify students, broadening the scope of surveillance.
3 Minnesota districts under court decrees for racialized disciplinary practices have made significant investments in vape detection.
12
Research has shown a concerning link between increased surveillance and the school-to-prison pipeline, particularly through exclusionary discipline practices such as in-school suspension (ISS), out-of-school suspension (OSS), expulsion, and zero-tolerance policies38. Factors such as race39, socioeconomic status40, gender identity41, and binary sex42 significantly influence how school disciplinary measures are applied. High levels of school surveillance are associated with greater disparities in suspension rates between African- American and white students: “highly secure” schools are more likely to suspend African-American students than white students .43 This intersection of surveillance and school pushout highlights the ongoing issue of institutional racism, emphasizing how racial inequality continues to shape the educational experiences of historically marginalized communities and increased pushout of vulnerable students into the school-to-prison pipeline.
Unfortunately, Minnesota schools are increasingly turning to surveillance, exclusionary discipline and law enforcement notification as preferred methods of responding to tobacco and substance use rather than direct students to services that would help them avoid or recover from substance addiction. These responses threaten to increase student contact with the criminal legal system. In Minnesota, the number of students punished for tobacco use has dramatically surged in recent years, becoming the fourth leading cause for student discipline.44 According to data from the Minnesota Department of Education, the number of students disciplined in school for tobacco use between the 2016-17 to 2021-2022 school years nearly doubled from 2,355 to 5,202.45 One might think this increase would parallel an increase in substance use. However, student survey data reveals only a 3% increase in student vape use during the same period of time.46
Automated vape detection systems threaten to deepen student discipline and associated demographic disparities. Vape detectors reflect a surveillance-driven approach that not
only fails to address the root causes of the school-to-prison pipeline but also exacerbates the problem, particularly for the state’s most at-risk children. These students, who are subjected to repeated and severe disciplinary actions, are nearly three times more likely to come into contact with the juvenile justice system.47 Increasing high-tech surveillance in schools, therefore, risks worsening these disparities rather than resolving them. This is particularly concerning for students who already face more severe disciplinary actions and are pushed out of the education system.48
FACIAL RECOGNITION AND BIOMETRIC MONITORING Facial recognition technology in particular, poses significant risks, given its capability to track the movements and associations of students, teachers, and school personnel throughout the day. As described earlier, popular commercial vape sensors offer facial recognition as an add-on feature that can be integrated into the detection system–placing the legal and ethical considerations of facial recognition squarely into the debate on the use of vape detection in public schools. The widespread use of facial recognition and other forms of biometric surveillance technologies sets a dangerous precedent of constant surveillance and increases the risk of misuse of sensitive data. Similarly, some schools have introduced “aggression detecting microphones” in hallways, cafeterias, and other common areas. These devices claim to detect anger in human voices and alert school authorities before an incident occurs. However, an analysis by ProPublica revealed that these detectors are highly unreliable. In a two-hour test, the detectors produced 565 false positives from sounds such as laughing, coughing, singing, and regular conversations, while frequently failing to detect actual expressions of aggression like screaming or shouting49. While the utility of such technology remains questionable, its likely impact on marginalized youth—who are often wrongfully labeled as disruptive—poses a significant concern.
Research has shown a concerning link between increased surveillance and the school-to-prison pipeline.
13
LEGAL IMPLICATIONS School surveillance technologies such as automated vape detectors raise a host of legal considerations for school districts.50 Students are protected by a range of privacy rights, civil rights and civil liberties including Titles VI and IV of the Civil Rights Act, the Americans with Disabilities Act, Section 504 of the Rehabilitation Act, the Family Educational Rights and Privacy Act, the Fair Trade Commission Act and the Fourth and Fourteenth Amendments of the United States Constitution in addition to analogous legal protections in Minnesota state law.51 Critical questions related to school vape detection practices remain unanswered by existing case law and policy guidance. This regulatory uncertainty should caution school districts against adopting these technologies.
CASE STUDY: CULLMAN COUNTY’S “VAPE COURT” A key example of these dynamics in action is the program implemented in Cullman County, Alabama, where the installation of HALO Smart Sensors has been paired with a “vape court” initiative.52 This program is designed to combat student vaping by combining school-based punishments with legal consequences. Students caught vaping are not only subject to disciplinary actions within the school but also receive tickets and are required to appear in the county’s vape court. While proponents argue that the program sends a strong message about the seriousness of underage vaping, there are significant concerns about the financial and social implications for students and their families. The program’s fines and the hidden costs associated with attending court-mandated programs can place an additional burden on students, potentially exacerbating existing inequalities. This example highlights the broader issues surrounding the implementation of surveillance technology in schools, where punitive measures are prioritized over supportive interventions, raising questions about the effectiveness and fairness of such approaches.
OVERLOOKING MENTAL HEALTH AND ADDICTION SUPPORT Focusing on costly security measures like vape detectors often overshadows essential discussions about mental health and student addiction. These areas are crucial for a comprehensive approach to school safety but receive less attention amid the push for new surveillance technologies. Research highlights the link between substance use, mental health issues, and disciplinary actions. A 2022 study found that schools with higher substance use and depressive feelings among students also had higher rates of suspensions, expulsions, and police involvement.53 A 2023 survey revealed that students reporting substance use were more likely to face discipline and later arrest, while those suspended or expelled were more likely to use substances and face adult incarceration.54 This cycle contributes to the school-to-prison pipeline, especially in schools lacking adequate support systems.
Broadly, punitive measures and exclusionary discipline are associated with substance use or depressed feelings among students, lower levels of community support, feeling safe in school, and school support, and higher levels of violence/harassment in school.55 The U.S. Department of Education’s report underscores the detrimental effects of suspension and expulsion, including decreased graduation rates and increased involvement with the criminal justice system, highlighting the need for alternative disciplinary approaches.56 Moreover, the negative impact of expulsion and suspension extends beyond the individual student to affect the academic achievement of the entire student body, with high rates of school suspensions associated with lower standardized test scores and academic performance overall.57 Recommendations from the DOE emphasize reserving out-of-school punishments for severe infractions threatening school safety, rather than for tobacco-related violations.58
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EFFECTIVENESS AND LIMITATIONS OF VAPE DETECTORS Despite significant investments, vape detectors have limited effectiveness in reducing student vaping. Students addicted to nicotine often find ways to evade detection, such as vaping in less monitored areas or using methods to mask the vapor. These actions displace the behavior rather than addressing the addiction, failing to support students in overcoming dependence. Additionally, vape detectors do not engage with the psychological and social factors contributing to nicotine addiction. Instead of providing necessary support and education, the focus on surveillance and punishment can alienate students, potentially worsening the problem. Effective measures to reduce vaping should focus on comprehensive education about the dangers of nicotine, accessible support systems for those wanting to quit, and fostering a school culture that prioritizes student well-being over punitive measures.
ALTERNATIVE STRATEGIES FOR REDUCING VAPING Effective measures to reduce vaping among students should prioritize education, support, and fostering a positive school culture, including:
ALTERNATIVE-TO-SUSPENSION PROGRAMS: Prioritizing supportive interventions over punitive measures to address underlying issues related to substance use and mental health.
HEALING-CENTERED JUSTICE: Addressing the individual, collective and intergenerational trauma and oppression experienced by students and their communities through historic hardships like the COVID-19 pandemic by promoting cultural healing practices and addressing root causes of behavioral health challenges.59
COMPREHENSIVE EDUCATION: Informing students about the dangers of nicotine and the health risks associated with vaping.
ACCESSIBLE SUPPORT SYSTEMS: Providing resources and assistance for students who want to quit vaping, including counseling and cessation programs.
COMMUNITY-BASED PARTICIPATORY RESEARCH (CBPR): Engaging communities in designing and implementing smoking cessation programs.60
SCHOOL-BASED PREVENTION PROGRAMS: Implementing interactive curricula, refusal skills activities, and behavior change theories. Best practices include normative education, age-targeting, and teacher training.61
POLICE–FREE SCHOOLS:62 Removing surveillance technologies that police student substance use can restore student trust, foster social connections, and strengthen the effectiveness of public health interventions to promote safety and wellness.
CONCLUSION While the rise in youth vaping poses significant challenges, reliance on high-tech surveillance measures like vape detectors do not seem to be an effective solution if the goal is to stop or reduce youth vaping behavior. Instead, schools should adopt a healing-centered approach that prioritizes comprehensive education, accessible support systems, and community engagement. These interventions address the root causes of vaping and promote student well-being. By shifting focus from punitive surveillance to supportive and educational strategies, schools can create a safer and healthier environment that effectively tackles youth vaping and mitigates the broader issues of mental health and addiction and school pushout.
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School District Year of initial purchase
Total expenditures since 2019
Albany Area School 2022 $400.00
Alexandria School District No. 206 2019 $5,195.00
Annandale Independent School District No. 876 2019 $9,655.00
Bagley Independent School District No. 162 2022 $13,867.50
Becker Public School District No. 726 2022 $6,761.47
Belle Plaine Schools 2020 $1,278.00
APPENDIX B: COMPLETE LIST OF SCHOOL DISTRICT VAPE PROCUREMENT BY YEAR Based on our analysis of procurement data available through the GovSpend platform, we find a growing use of automated vape sensors purchased by Minnesota Public Schools. Forty-two school districts have purchased automated vape sensor technology since 2019. Below we provide the total expenditures by school districts statewide since 2019.
APPENDIX A: MAJOR EXPENDITURES FOR STUDENT
School District Year of initial purchase
Total expenditures since 2019
2023-2024 student population
Eden Prairie School District No. 272 2020 $89,078.07 61,089
Westbrook-Walnut Grove Schools 2020 $52,135.00 2,693
Grand Rapids Independent School District No. 318 2023 $30,746.00 27,904
HOPE Community Academy 2022 $28,768.00 –
Marshall Public School District No. 413 2019 $28,454.26 15,784
16
School District Year of initial purchase
Total expenditures since 2019
Bemidji Area Schools Independent School District No. 31 2021 $1,992.30
Canby Public School District 2022 $8,129.00
Crookston Public Schools - ISD No. 593 2021 $2,625.00
Eden Prairie School District No. 272 2020 $89,078.07
Faribault Public School District No. 656 2023 $1,498.00
Grand Rapids Independent School District No. 318 2023 $30,746.00
Hastings Public School District No. 200 2023 $3,300.00
HOPE Community Academy 2022 $28,768.00
Kelliher Public School 2020 $7,912.00
Lake Crystal Wellcome Memorial School District 2019 $2,799.40
Littlefork-Big Falls School District 362 2022 $420.00
Maple Lake Public Schools 2023 $6,654.00
Maple River Schools 2022 $12,979.47
Marshall Public School District No. 413 2019 $28,454.26
Mesabi East School District 2023 $470.56
Milaca Public School District No. 912 2023 $11,152.00
Minnetonka Independent School District No. 276 2019 $12,500.00
Montevideo Public Schools ISD No. 129 2021 $1,797.75
Murray County School District #2169 2023 $2,740.00
Nashwauk-Keewatin Public Schools 2022 $7,800.00
17
School District Year of initial purchase
Total expenditures since 2019
Onamia Public School District #480 2022 $8,965.00
Osseo Independent School District No. 279 2022 $3,100.80
Park Rapids Area Schools 2023 $6,930.00
Princeton Public Schools - Independent School District No. 477 2023 $8,784.00
Red Wing Independent School District No. 256 2020 $5,999.40
Redwood Area School District #2897 2022 $2,500.00
Rockford Independent School District No. 883 2019 $5,060.00
Rothsay Public School District 2021 $8,960.78
Round Lake-Brewster School District 2020 $5,114.90
Sibley East Public School 2021 $7,960.00
Spring Lake Park Independent School District No. 16 2023 $2,285.20
South Washington County School District No. 833 2023 $5,910.51
St. Michael-Albertville Public School District No. 885 2023 $9,584.00
Wabasha-Kellogg School District 2023 $5,565.00
Westbrook-Walnut Grove Schools 2020 $52,135.00
Willmar Public Schools - District No. 347 2023 $3,000.00
Windom Area Schools 2021 $1,568.96
18
ENDNOTES 1 Okoh, C. (2024, May 23). Dangerous Data: What Communities Should Know about Artificial Intelligence, the School-to-Prison Pipeline, and School Surveillance. CLASP. Retrieved October 3, 2024, from https://www.clasp.org/publications/report/brief/ai-data- justice-school-prison-pipeline/
2 Ali, F. R., Seidenberg, A. B., Crane, E., Seaman, E., Tynan, M. A., & Marynak, K. (2023). E-cigarette unit sales by product and flavor type, and top-selling brands, United States, 2020–2022. MMWR Morbidity and Mortality Weekly Report, 72(25), 672–677. https:// doi.org/10.15585/mmwr.mm7225a1
3 Birdsey, J., Cornelius, M., Jamal, A., Park-Lee, E., Cooper, M. R., Wang, J., Sawdey, M. D., Cullen, K. A., & Neff, L. (2023). Tobacco Product Use Among U.S. Middle and High School Students - National Youth Tobacco Survey, 2023. MMWR. Morbidity and mortality weekly report, 72(44), 1173–1182. https://doi. org/10.15585/mmwr.mm7244a1
4 Park-Lee, E., Jamal, A., Cowan, H., et al. (2024). Notes from the field: E-cigarette and nicotine pouch use among middle and high school students — United States, 2024. *MMWR Morbidity and Mortality Weekly Report*, *73*(35), 774–778. https://doi. org/10.15585/mmwr.mm7335a3
5 Chen-Sankey, J. C., Unger, J. B., Bansal-Travers, M., Niederdeppe, J., Bernat, E., & Choi, K. (2019). E-cigarette Marketing Exposure and Subsequent Experimentation Among Youth and Young Adults. Pediatrics, 144(5), e20191119. https://doi.org/10.1542/peds.2019- 1119
6 Ali, F. R., Seidenberg, A. B., Crane, E., Seaman, E., Tynan, M. A., & Marynak, K. (2023). E-cigarette unit sales by product and flavor type, and top-selling brands, United States, 2020–2022. MMWR Morbidity and Mortality Weekly Report, 72(25), 672–677. https:// doi.org/10.15585/mmwr.mm7225a1
7 CDC Foundation. (2024). Monitoring U.S. e-cigarette sales: National trends. *CDC Foundation*. https://www.cdcfoundation. org/Issue33-MonthlyECigaretteSalesDataBrief_9.10.2023.pdf?inline (Accessed September 11, 2024).
8 Fillon M. (2015). Electronic cigarettes may lead to nicotine addiction. Journal of the National Cancer Institute, 107(3), djv070. https://doi.org/10.1093/jnci/djv070
9 England, L. J., Bunnell, R. E., Pechacek, T. F., Tong, V. T., & McAfee, T. A. (2015). Nicotine and the Developing Human: A Neglected Element in the Electronic Cigarette Debate. American journal of preventive medicine, 49(2), 286–293. https://doi.org/10.1016/j. amepre.2015.01.015; Goriounova, N. A., & Mansvelder, H. D. (2012).
Short- and long-term consequences of nicotine exposure during adolescence for prefrontal cortex neuronal network function. Cold Spring Harbor perspectives in medicine, 2(12), a012120. https://doi. org/10.1101/cshperspect.a012120
10 National Academies of Sciences, Engineering, and Medicine, Health and Medicine Division, Board on Population Health and Public Health Practice, Committee on the Review of the Health Effects of Electronic Nicotine Delivery Systems, Eaton, D. L., Kwan, L. Y., & Stratton, K. (Eds.). (2018). Public Health Consequences of E-Cigarettes. National Academies Press (US).
11 England, L. J., Bunnell, R. E., Pechacek, T. F., Tong, V. T., & McAfee, T. A. (2015). Nicotine and the Developing Human: A Neglected Element in the Electronic Cigarette Debate. American journal of preventive medicine, 49(2), 286–293. https://doi. org/10.1016/j.amepre.2015.01.015; Goriounova, N. A., & Mansvelder, H. D. (2012). Short- and long-term consequences of nicotine exposure during adolescence for prefrontal cortex neuronal network function. Cold Spring Harbor perspectives in medicine, 2(12), a012120. https://doi.org/10.1101/cshperspect.a012120
12 HALO Smart Sensor. (2024, August 16). Health, Safety and Vape Detector: Halo Smart Sensor. Health, Safety and Vape Detector | HALO Smart Sensor. https://halodetect.com/
13 Soter Technologies. (2024a, May 29). What sensors detect Vape: Best Vape Sensor: 2024. Soter Technologies. https://www. sotertechnologies.com/news/sensorsforvapedetection/
14 Hsu, J. (2021, June 24). Schools enlist AI to detect vaping and bullies in bathrooms. IEEE Spectrum. https://spectrum.ieee.org/ schools-enlist-ai-to-detect-vaping-and-bullies-in-bathrooms
15 Triton Sensors. (2024a, January 14). Do Vape Smoke detectors really work?. Triton Sensors. https://tritonsensors.com/vape- smoke-detectors-work/#:~:text=How%20Vape%20Sensors%20 Work,the%20presence%20of%20vaping%20particles
16 Triton Sensors. (2024a, January 14). Do Vape Smoke detectors really work?. Triton Sensors. https://tritonsensors.com/vape- smoke-detectors-work/#:~:text=How%20Vape%20Sensors%20 Work,the%20presence%20of%20vaping%20particles
17 American Civil Liberties Union. (2023, October 2). Digital dystopia: The danger in buying what the EdTech surveillance industry is selling. ACLU Research Report. https://www.aclu.org/ publications/digital-dystopia-the-danger-in-buying-what-the-edtech- surveillance-industry-is-selling
18 Id.
19 Id.
19
20 Id.
21 Id.
22 Id.
23 Department of Justice. (2024, September 17). Justice Department awards over $600m to hire law enforcement officers, Keep Schools Safe, and improve law enforcement mental health and Wellness Services. Office of Public Affairs | Justice Department Awards Over $600M to Hire Law Enforcement Officers, Keep Schools Safe, and Improve Law Enforcement Mental Health and Wellness Services | United States Department of Justice. https:// www.justice.gov/opa/pr/justice-department-awards-over-600m- hire-law-enforcement-officers-keep-schools-safe-and
24 U.S. Department of Education. (n.d.). Elementary and Secondary School Emergency Relief Fund. U.S. Department of Education. https://www.ed.gov/grants-and-programs/formula-grants/response- formula-grants/covid-19-emergency-relief-grants/elementary-and- secondary-school-emergency-relief-fund
25 U.S. Department of Homeland Security. (n.d.). Homeland security grant program (HSGP): Homeland Security. U.S. Department of Homeland Security. https://www.dhs.gov/homeland- security-grant-program-hsgp
26 Nance, J. P. (2016). Student surveillance, racial inequalities, and implicit racial bias. Emory Law Journal, 66, 765.
27 See Appendix B for a more detailed breakdown and analysis of district-level expenditures.
28 Other major expenditures are captured in Appendix A.
29 Complete list of district purchases by year can be found at Appendix B.
30 Laird, E., & Dwyer, M. (2023, September 20). Report - Off Task: EdTech Threats to Student Privacy and Equity in the Age of AI. - Center for Democracy and Technology. Retrieved October 3, 2024, from https://cdt.org/insights/report-off-task-edtech-threats-to- student-privacy-and-equity-in-the-age-of-ai/
31 Archer, D. (2009). Introduction: Challenging the School-to- Prison Pipeline. New York Law School Law Review, 54(2009- 2010), 867. https://digitalcommons.nyls.edu/cgi/viewcontent. cgi?article=1360&context=fac_articles_chapters
32 The Advancement Project. (2023, June 23). We Came To Learn. Police Free Schools Campaign. https://policefreeschools. org/resources/we-came-to-learn-a-call-to-action-for-police-free- schools-2/
33 Id.
34 Henning, K. (2023). The Rage of Innocence: How America Criminalizes Black Youth. Knopf Doubleday Publishing Group.
35 (The Advancement Project, 2023)
36 Suspension and Expulsion Initiative Data. (n.d.). Minnesota. gov. Retrieved October 3, 2024, from https://mn.gov/mdhr/news- community/reports/data-reports-and-analytics/sedata.jsp
37 Id.
38 Nance, J. P. (2016). Student surveillance, racial inequalities, and implicit racial bias. Emory Law Journal, 66, 765.
39 Gordon, R., Della Piana, L., & Keleher, T. (2000). Facing the consequences: An examination of racial discrimination in U.S. public schools. Petras, H., Masyn, K. E., Buckley, J. A., Ialongo, N. S., & Kellam, S. (2011). Who is most at risk for school removal? A multilevel discrete-time survival analysis of individual- and context-level influences. Journal of Educational Psychology, 103(1), 223–237. https://doi.org/10.1037/a0021545; Skiba, R., & Rausch, M. K. (2006). School disciplinary systems: Alternatives to suspension and expulsion. Wallace, J. M., Goodkind, S., Wallace, C. M., & Bachman, J. G. (2008). Racial, ethnic, and gender differences in school discipline among U.S. high school students: 1991-2005. Negro Educational Review, 59(1-2), 47–62. PMID: 19430541; PMCID: PMC2678799.
40 Petras, H., Masyn, K. E., Buckley, J. A., Ialongo, N. S., & Kellam, S. (2011). Who is most at risk for school removal? A multilevel discrete-time survival analysis of individual- and context-level influences. Journal of Educational Psychology, 103(1), 223–237. https://doi.org/10.1037/a0021545; Skiba, R. J., Michael, R. S., Nardo, A. C., & Peterson, R. L. (2002). The color of discipline: Sources of racial and gender disproportionality in school punishment. The Urban Review, 34, 317–342.
41 Mendez, L. M. R., & Knoff, H. M. (2003). Who gets suspended from school and why: A demographic analysis of schools and disciplinary infractions in a large school district. Education and Treatment of Children, 26(1), 30–51. Skiba, R. J., Michael, R. S., Nardo, A. C., & Peterson, R. L. (2002). The color of discipline: Sources of racial and gender disproportionality in school punishment. The Urban Review, 34, 317–342. Petras, H., Masyn, K. E., Buckley, J. A., Ialongo, N. S., & Kellam, S. (2011). Who is most at risk for school removal? A multilevel discrete-time survival analysis of individual- and context- level influences. Journal of Educational Psychology, 103(1), 223–237. https://doi.org/10.1037/a0021545
20
42 Himmelstein, K. E. W., & Brückner, H. (2011). Criminal- justice and school sanctions against nonheterosexual youth: A national longitudinal study. Pediatrics, 127(1), 49–57. https://doi.org/10.1542/peds.2009-2306; Mittleman, J. (2018). Sexual orientation and school discipline: New evidence from a population-based sample. Educational Researcher, 47(3), 181–190. https://www.jstor.org/ stable/44971899
43 Nance, J. P. (2016). Student surveillance, racial inequalities, and implicit racial bias. Emory Law Journal, 66, 765.
44 Minnesota Department of Education. Data Center. Discipline Data. Retrieved September 20, 2024, from https://public.education.mn.gov/MDEAnalytics/DataTopic. jsp?TOPICID=133
45 Id.
46 Minnesota Department of Education. Data Center. Student Data. Retrieved September 20, 2024, from https://public. education.mn.gov/MDEAnalytics/DataTopic.jsp?TOPICID=2
47 Ma, A., & Mumphrey, C. (2024, August 30). Black students are still kicked out of school at higher rates despite reforms. AP News. https://apnews.com/article/ ferguson-black-lives-matter-school-discipline-suspension- d099aab519ff743dc2be04c6b6132144#
48 (Henning, 2023)
49 Gillum, J., & Kao, J. (2019, June 25). The unproven, invasive surveillance technology schools are using to monitor students. ProPublica. https://features.propublica. org/aggression-detector/the-unproven-invasive-surveillance- technology-schools-are-using-to-monitor-students/
50 Okoh, C. (2024, May 23). Dangerous Data: What Communities Should Know about Artificial Intelligence, the School-to-Prison Pipeline, and School Surveillance. CLASP. Retrieved September 20, 2024, from https://www.clasp. org/publications/report/brief/ai-data-justice-school-prison- pipeline/
51 Id.
52 Community Service, fines if you vape in Cullman County Schools. Community Service, Cullman County Schools. (2021, August 9). https://www.ccboe.org/article/506922
53 Prins, S. J., Kajeepeta, S., Hatzenbuehler, M. L., Branas, C. C., Metsch, L. R., & Russell, S. T. (2022). School Health Predictors of the School-to-Prison Pipeline: Substance Use and Developmental Risk and Resilience Factors. The Journal of adolescent health : official publication of the Society for Adolescent Medicine, 70(3), 463–469. https://doi. org/10.1016/j.jadohealth.2021.09.032
54 Prins, S. J., Shefner, R. T., Kajeepeta, S., Levy, N., Esie, P., & Mauro, P. M. (2023). Longitudinal relationships among exclusionary school discipline, adolescent substance use, and adult arrest: Public health implications of the school-to- prison pipeline. Drug and alcohol dependence, 251, 110949. https://doi.org/10.1016/j.drugalcdep.2023.110949
55 Prins, S. J., Shefner, R. T., Kajeepeta, S., Levy, N., Esie, P., & Mauro, P. M. (2023). Longitudinal relationships among exclusionary school discipline, adolescent substance use, and adult arrest: Public health implications of the school-to- prison pipeline. Drug and alcohol dependence, 251, 110949. https://doi.org/10.1016/j.drugalcdep.2023.110949
56 U.S. Department of Education. (2014). Guiding Principles: A Resource for Improving School Climate and Discipline.
57 U.S. Department of Education. (2014). Guiding Principles: A Resource for Improving School Climate and Discipline.
58 U.S. Department of Education. (2014). Guiding Principles: A Resource for Improving School Climate and Discipline.
59 Page, C., & Woodland, E. (2023). Healing Justice Lineages: Dreaming at the Crossroads of Liberation, Collective Care, and Safety. North Atlantic Books.
60 Sheikhattari, P., Apata, J., Kamangar, F., Schutzman, C., O’Keefe, A., Buccheri, J., & Wagner, F. A. (2016). Examining Smoking Cessation in a Community-Based Versus Clinic- Based Intervention Using Community-Based Participatory Research. Journal of community health, 41(6), 1146–1152. https://doi.org/10.1007/s10900-016-0264-9
61 Liu, J., Gaiha, S. M., & Halpern-Felsher, B. (2022). School- based programs to prevent adolescent e-cigarette use: A report card. Current problems in pediatric and adolescent health care, 52(6), 101204. https://doi.org/10.1016/j. cppeds.2022.101204
62 Police Free Schools. Retrieved September 20, 2024, from https://policefreeschools.org/