![Sample our Education journals, sign in here to start your access, latest two full volumes FREE to you for 14 days]({"type":"image" , "src" : "/sda/5932/TOC-Subject-Sample-2021-Education.jpg"})
ABSTRACT
Bullying has received increased attention from academics, scholars, and the media over the past decade and a half. The effects of bullying can be devastating and long lasting for victims and bullies alike. Recent prevention efforts and research has focused on the school environment as a whole. As such, two areas of interest that could affect bullying are the roles of school climate and school sector. School sector is important to examine as private schools make up 25% of all schools in the United States and approximately 80% of private school students attended faith-based institutions (Broughman & Swaim, Citation2013). This study utilized the School Crime Supplement to understand how school climate and school sector affect students’ experiences of bullying victimization. Using chi square analysis, propensity score analysis, and multiple regression models (of the total sample, public school sample, and private school sample), as well as Z-score coefficients, findings suggest that a positive school climate predicted less reporting of bullying incidents and that private school students in particular reported a more positive school climate and less bullying.
Disclosure statement
No potential conflict of interest was reported by the author.
Notes
1. All variables utilized in the following analyses were measured at the individual-level as the SCS was administered to students. The analyses do not contain school-level demographics.
2. Response pattern bias was not a concern as only one variable utilized in the scale creation was reverse coded (Idaszak & Drasgow, Citation1987). Response bias was also not a problem as all scales contained less than seven measures (Schmitt & Stults, Citation1985).
3. Preliminary analyses indicated that separate physical and verbal bullying scales did not yield differential predictors and factor analysis was chosen as a sufficient method to determine scale creation.
4. A robustness check was performed by dichotomizing the dependent variable and running a logistic regression. Significance of independent predictors was not affected.
5. The SCS survey does not make a distinction for students attending charter schools or those who transferred between public and private schools.
6. Due to a lower reliability score, analyses were run without this variable as a robustness check. Significance of independent predictors was not affected.
7. Due to the mixed nature of this relationship, analyses were rerun without these variables as a robustness check. Significance of independent predictors was not affected.