Description of original award (Fiscal Year 2020, $567,191)
School safety research rarely considers the school security climate as a product of the simultaneous implementation of several school safety interventions. This is potentially problematic, as schools seldom employ only one safety intervention. Rather, schools today employ several interventions simultaneously to meet their safety and security needs. The purpose of this study is to investigate and identify effective types of school security climates and examine student growth within these climates. This multi-year project attempts to meet two goals: 1) Identify effective types of school security climates; and 2) Determine how the school security climate affects individual students. This study proposes to continue a three-phase longitudinal design. This study will continue following the pilot cohort of 9th grade students (n=359) within Newark during the 2019-2020 and 2020-2021 school year. Starting in the 2019-2020 school year, and with the assistance of the BOE, all students in ninth and tenth grade (N=~5,000) across all high schools in Newark (N=14) will be recruited to participate in the study. Once data is collected in the 2019-2020 school year, students will be matched across different types of school security climates (Phase 2) to identify and compare student progress in schools with different types of security climates over time (Phase 3). Analysis: Latent Class Analysis and Logistic Regression was employed to classify schools by security climate using student self-report data. Propensity Matching will be used in place of randomization to match students on demographic characteristics with
the purpose of creating comparable groups of students within different climates. Growth Curve Modeling will be used to model students trajectories within different security climates over two and three year periods, respectively.
"Note: This project contains a research and/or development component, as defined in applicable law," and complies with Part 200 Uniform Requirements - 2 CFR 200.210(a)(14). nca/ncf
- Support Activities under Section 13(d) of Executive Order 14074: Workshops on Law Enforcement Use of Probabilistic DNA Technologies and Person-based Predictive Policing
- A Micro-and Macro Evaluation of the Effectiveness of Extreme Risk Protection Orders in Colorado
- Comprehensive Evaluation of Kinetic and Thermodynamic Approaches to Predict Evaporation of Ignitable Liquids for Fire Debris Applications