High School Exclusionary Discipline Data in Pennsylvania (SY 2016/2017)
Principal Investigator(s): View help for Principal Investigator(s) Jacob-Paul Taylor, Alvernia University; Malgorzata Zuber, Alvernia University; David Shoup, Alvernia University
Version: View help for Version V1
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Project Citation:
Taylor, Jacob-Paul, Zuber, Malgorzata , and Shoup, David. High School Exclusionary Discipline Data in Pennsylvania (SY 2016/2017). Ann Arbor, MI: Inter-university Consortium for Political and Social Research [distributor], 2023-12-31. https://doi.org/10.3886/E196441V1
Project Description
Summary:
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This dataset includes publicly available data published primarily by the Pennsylvania Department of Education and the Pennsylvania Office of Safe Schools. The dataset was created by combining several publications by the Pennsylvania Department of Education, including the 2017 School Fast Fact database, 2016-2017 Academic Performance database, and the 2017 Keystone Score database. The dataset includes institutional (school-wide) variables for every public high school in Pennslyvania (n = 407 ). The data includes information surrounding each institution's socio-economic status, racial composition, academic performance, and type of and total use of exclusionary discipline (in-school suspension, out-of-school suspension, and expulsion) for the school year 2016-2017.
The dataset also includes neighborhood information for each school location. This data was collected from AreaVibes, a website known for its ability to guide individuals in their search for ideal residential areas in the United States and Canada. AreaVibes deploys a unique algorithm that evaluates multiple different data points for each location, including amenities, cost of living, crime rates, employment, housing, schools, and user ratings. This dataset deployed AreaVibes to input the physical addresses of each high school in order to retrieve the livability score for the surrounding neighborhoods of these educational institutions. Furthermore, the website was instrumental in collecting neighborhood crime scores, offering valuable insights into the levels of criminal activity within specific geographic zones. The crime score takes into account both violent crime and property crime. However, higher weights are given to violent crimes (65%) than property crime (35%) as they are more severe. Data for calculation by Areavibes is derived from FBI Uniform Crime Report.
School discipline is crucial for ensuring safety, well-being, and academic success. However, the continued use of exclusionary discipline practices, such as suspension and expulsion, has raised concerns due to their ineffectiveness and harmful effects on students. Despite compelling evidence against these practices, many educational institutions persist in relying on them. This persistence has led to a troubling reality—a racial and socioeconomic discipline gap in schools. This data is used to explore the evident racial and socioeconomic disparities within high school discipline frameworks, shedding light on the complex web of factors that contribute to these disparities and exploring potential solutions. Drawing from social disorganization theory, the data explores the interplay between neighborhood and school characteristics, emphasizing the importance of considering the social context of schools.
The dataset also includes neighborhood information for each school location. This data was collected from AreaVibes, a website known for its ability to guide individuals in their search for ideal residential areas in the United States and Canada. AreaVibes deploys a unique algorithm that evaluates multiple different data points for each location, including amenities, cost of living, crime rates, employment, housing, schools, and user ratings. This dataset deployed AreaVibes to input the physical addresses of each high school in order to retrieve the livability score for the surrounding neighborhoods of these educational institutions. Furthermore, the website was instrumental in collecting neighborhood crime scores, offering valuable insights into the levels of criminal activity within specific geographic zones. The crime score takes into account both violent crime and property crime. However, higher weights are given to violent crimes (65%) than property crime (35%) as they are more severe. Data for calculation by Areavibes is derived from FBI Uniform Crime Report.
School discipline is crucial for ensuring safety, well-being, and academic success. However, the continued use of exclusionary discipline practices, such as suspension and expulsion, has raised concerns due to their ineffectiveness and harmful effects on students. Despite compelling evidence against these practices, many educational institutions persist in relying on them. This persistence has led to a troubling reality—a racial and socioeconomic discipline gap in schools. This data is used to explore the evident racial and socioeconomic disparities within high school discipline frameworks, shedding light on the complex web of factors that contribute to these disparities and exploring potential solutions. Drawing from social disorganization theory, the data explores the interplay between neighborhood and school characteristics, emphasizing the importance of considering the social context of schools.
Scope of Project
Subject Terms:
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school dropouts;
school attendance;
education;
educational policy;
educational achievement;
poverty;
quantitative methods;
racial/ethnic identity;
racial segregation;
academic disciplines;
discipline;
exclusionary discipline;
delinquent behavior;
delinquency;
juvenile crime;
juvenile
Geographic Coverage:
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Pennsylvania
Time Period(s):
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8/2016 – 6/2017 (School Year 2016-2017)
Collection Date(s):
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5/2021 – 8/2021
Universe:
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Public High Schools in Pennsylvania offering grades 9-12 in the SY 2016-2017
Data Type(s):
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administrative records data;
aggregate data
Methodology
Collection Mode(s):
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other
Unit(s) of Observation:
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Educational Institution (School)
Related Publications
Published Versions
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