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Using latent profile analysis on measures spanning leadership, instructional agency, professional growth, rigorous instruction, student behavior management, family engagement, physical environment, and safety, the research identifies four school classes: Supportive, Unsupportive, Unstructured, and Structured. 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\nArticle reuse guidelines: [sagepub.com/journals-permissions](sagepub.com/journals-permissions)[ ](sagepub.com/journals-permissions)© The Author(s) 2025. [https://journals.sagepub.com/home/ero](https://journals.sagepub.com/home/ero)  \nLatent School-Level Classes of Teacher Working Conditions in Virginia: Description, Teacher Preferences, and Contextual Factors  \nLuke C. Miller  \nUniversity of Virginia  \nJames Soland  \nUniversity of Virginia  \nDaniel W. Lipscomb  \nUniversity of Virginia  \nDaniel W. Player  \nUniversity of Virginia  \nRachel S. White  \nUniversity of Texas at Austin  \nMany dimensions of teacher working conditions influence both teacher and student outcomes; yet, analyses of schools’overall working conditions are challenged by high correlations among the dimensions. Our study overcame this challenge by applying latent profile analysis to school-level measures of school leadership, instructional agency, professional growth opportunities, rigorous instruction, managing student behavior, family engagement, physical environment, and safety. We identified four classes of schools: Supportive (61%), Unsupportive (7%), Unstructured (22%), and Structured (11%). The patterns of these classes suggest that schools may face tradeoffs between factors such as more teacher autonomy for less instructional rigor or discipline. Teacher satisfaction and their stated career intentions were predicted by their school’s working conditions class, and school contextual factors predicted class membership. By identifying formerly unseen profiles of school-level teacher working conditions and considering the implications of being a teacher in each, decision-makers can provide schools with targeted supports and investments.  \nKeywords: Administration, educational policy, educational reform, factor analysis, latent profile analysis, organization theory/change, psychometrics, regression analyses, retention, school improvement, survey research, teacher context, teachers, working conditions  \nIn order to close persistent achievement gaps along lines of race and ethnicity and socioeconomic status, all students must be taught by an effective teacher. Teachers represent the most significant school factor related to student achievement, and evidence suggests that teachers vary significantly in their effectiveness (Rivkin et al., 2005; Rockoff, 2004) . However, solely focusing on what the individual teacher does in the classroom to improve teaching quality is missing something important—the school context defined by teacher working conditions (Johnson, 1990, 2019; Kennedy, 2010) . Many school-and district-level working conditions  \ninfluence teacher effectiveness. Most apparent, teacher skills are influenced by conditions such as the quality and availability of ongoing professional development (Kennedy, 2016), the day-to-day instructional support and mentoring they receive (Goddard et al., 2015), and a supportive professional environment (Kraft & Papay, 2014) . These factors are within the control of school and district leadership and constitute important components of teacher working conditions.  \nTeacher surveys are a commonplace means of characterizing a school’s working conditions. Such surveys are useful  \nCreative Commons Non Commercial CC BY-NC: This article is distributed under the terms of the Creative Commons  \nAttribution-NonCommercial 4.0 License ([https://creativecommons.org/licenses/by-nc/4.0/](https://creativecommons.org/licenses/by-nc/4.0/)) which permits non-commercial use,  \nreproduction and distribution of the work without further permission provided the original work is attributed as specified on the SAGE and Open Access pages ([https://us.sagepub.com/en-us/nam/open-access-at-sage](https://us.sagepub.com/en-us/nam/open-access-at-sage)).  \nMiller et al.  \nfor identifying which aspects of working conditions the school needs to improve, for track","cbCaiurpBFuqYcHT","https://ap.wps.com/l/cbCaiurpBFuqYcHT","pdf",888882,"English","# Introduction\n## Research focus and rationale\n# Method and Analysis\n## Latent profile analysis approach\n# Findings\n## Identified classes and patterns\n# Implications\n## Targeted supports based on profiles","[{\"question\":\"Why do researchers need a method that handles correlations among working-condition dimensions?\",\"answer\":\"School working conditions include many dimensions that tend to be highly correlated, making it difficult to analyze the overall construct without accounting for that interdependence.\"},{\"question\":\"What method is used to classify schools by working conditions?\",\"answer\":\"The study applies latent profile analysis (LPA) using a mixture modeling framework to identify distinct classes based on patterns across eight school-level dimensions.\"},{\"question\":\"Which school-level working-condition classes were identified?\",\"answer\":\"Four classes were identified: Supportive (61%), Unsupportive (7%), Unstructured (22%), and Structured (11%).\"},{\"question\":\"How do the working-condition classes relate to teacher outcomes?\",\"answer\":\"Teacher satisfaction and stated career intentions are predicted by the school’s working-conditions class, while school contextual factors help explain class membership.\"}]","Latent School-Level Classes of Teacher Working Conditions in Virginia - Description, Teacher Preferences, and Contextual Factors | PDF",1792069335,48]