[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"detail-sidebar-cat-0-en-105":3,"doc-seo-590343-105":59,"doc-detail-590343-en":130},{"code":4,"msg":5,"data":6},0,"success",[7,13,18,23,28,33,38,43,48,51,55],{"id":8,"doc_module":4,"doc_module_name":9,"category_name":10,"show_sort_weight":11,"slug":12},1,"Document","Story & Novel",90,"story-novel",{"id":14,"doc_module":4,"doc_module_name":9,"category_name":15,"show_sort_weight":16,"slug":17},2,"Literature",80,"literature",{"id":19,"doc_module":4,"doc_module_name":9,"category_name":20,"show_sort_weight":21,"slug":22},4,"Exam",70,"exam",{"id":24,"doc_module":4,"doc_module_name":9,"category_name":25,"show_sort_weight":26,"slug":27},5,"Comic",60,"comic",{"id":29,"doc_module":4,"doc_module_name":9,"category_name":30,"show_sort_weight":31,"slug":32},6,"Technology",50,"technology",{"id":34,"doc_module":4,"doc_module_name":9,"category_name":35,"show_sort_weight":36,"slug":37},7,"Healthcare",40,"healthcare",{"id":39,"doc_module":4,"doc_module_name":9,"category_name":40,"show_sort_weight":41,"slug":42},8,"Research & Report",30,"research-report",{"id":44,"doc_module":4,"doc_module_name":9,"category_name":45,"show_sort_weight":46,"slug":47},9,"Religion & Spirituality",20,"religion-spirituality",{"id":46,"doc_module":4,"doc_module_name":9,"category_name":49,"show_sort_weight":46,"slug":50},"World Cup","world-cup",{"id":52,"doc_module":4,"doc_module_name":9,"category_name":53,"show_sort_weight":52,"slug":54},10,"Lifestyle","lifestyle",{"id":56,"doc_module":4,"doc_module_name":9,"category_name":57,"show_sort_weight":24,"slug":58},19,"General","general",{"code":4,"msg":60,"data":61},"ok",{"site_id":62,"language":63,"slug":64,"title":65,"keywords":66,"description":67,"schema_data":68,"social_meta":123,"head_meta":125,"extra_data":127,"updated_unix":129},105,"en","from-school-to-school-examining-the-contours-of-within-field-switching-in-the-special-education-teacher-labor-market","From School to School - Examining the Contours of Within-Field Switching in the Special Education Teacher Labor Market","","Teacher shortages in the United States are increasing and unevenly affect schools serving students of color, low-income students, and rural or urban communities. Special education teachers face especially high demand, yet research has rarely analyzed how teachers switch schools within their field. Using longitudinal Texas data covering 27 years and over 1.2 million teachers, the study models SET switching patterns versus core subject teachers with hazard and fixed-effect methods, plus GIS mapping, finding higher switching rates for SETs linked to experience, salary, and student demographics.",{"@graph":69,"@context":122},[70,84,105],{"@type":71,"itemListElement":72},"BreadcrumbList",[73,77,79,82],{"item":74,"name":75,"@type":76,"position":8},"https://docshare.wps.com","Home","ListItem",{"item":78,"name":9,"@type":76,"position":14},"https://docshare.wps.com/document/",{"item":80,"name":40,"@type":76,"position":81},"https://docshare.wps.com/document/research-report/",3,{"item":83,"name":65,"@type":76,"position":19},"https://docshare.wps.com/document/from-school-to-school-examining-the-contours-of-within-field-switching-in-the-special-education-teacher-labor-market/590343/",{"url":83,"name":65,"@type":85,"image":86,"author":91,"headline":65,"publisher":94,"fileFormat":97,"inLanguage":63,"description":67,"dateModified":98,"datePublished":99,"encodingFormat":97,"isAccessibleForFree":100,"interactionStatistic":101},"DigitalDocument",{"url":87,"@type":88,"width":89,"height":90},"https://docshare.wps.com/thumbnails/from-school-to-school-examining-the-contours-of-within-field-switching-in-the-special-education-teacher-labor-market/590343.png","ImageObject",300,407,{"name":92,"@type":93},"Pentious","Person",{"url":74,"name":95,"@type":96},"DocShare","Organization","application/pdf","2026-10-31","2026-10-15",true,{"@type":102,"interactionType":103,"userInteractionCount":34},"InteractionCounter",{"@type":104},"ViewAction",{"@type":106,"mainEntity":107},"FAQPage",[108,114,118],{"name":109,"@type":110,"acceptedAnswer":111},"What issue does the study investigate in the teacher labor market?","Question",{"text":112,"@type":113},"It examines how teachers switch schools within their subject field, with a specific focus on special education teachers.","Answer",{"name":115,"@type":110,"acceptedAnswer":116},"How does the study analyze teacher switching patterns?",{"text":117,"@type":113},"It uses longitudinal Texas data and applies discrete-time hazard modeling, fixed-effect regressions, and GIS mapping to compare SETs with core subject teachers.",{"name":119,"@type":110,"acceptedAnswer":120},"What do the findings suggest about special education teacher switching?",{"text":121,"@type":113},"SETs switch schools at higher rates than their peers, associated with experience, salary, and student demographics, and they generally transfer shorter distances.","https://schema.org",{"og:url":83,"og:type":124,"og:title":65,"og:site_name":95,"og:description":67},"article",{"robots":126,"canonical":83},"index,follow",{"doc_id":128,"site_id":62},590343,1792191074,{"code":4,"msg":5,"data":131},{"doc_id":128,"user_id":132,"nickname":92,"user_avatar":133,"doc_module":4,"category_id":39,"category_name":40,"doc_title":65,"doc_description":67,"doc_content":134,"file_id":135,"file_url":136,"file_type":137,"file_size":138,"view_count":34,"is_deleted":4,"is_public":8,"is_downloadable":8,"audit_status":8,"page_count":139,"language":140,"language_code":63,"site_id":62,"html_lang":63,"table_of_contents":141,"faqs":142,"seo_title":143,"seo_description":67,"update_tm":144,"read_time":145,"preview_page_count":4},1374404730887,"https://ap-avatar.wpscdn.com/davatar_6f874abed73319feea01a86fa6f0fab8","AERA Open  \nJanuary-December 2025, Vol. 11, No. 11, pp. 1–26 DOI: 10. 1177/23328584251347941  \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)  \nFrom School to School: Examining the Contours of Within-Field Switching in the Special Education Teacher Labor Market  \nAndrew Pendola  \nAuburn University  \nFrank Perrone  \nIndiana University-Bloomington  \nThe United States faces growing teacher shortages, disproportionately impacting schools serving students of color, lowincome students, and those in rural or urban areas. Special education teachers (SETs) are especially in demand. Nearly half of all teaching vacancies are filled by teachers switching schools each year, yet little research explores switching, particularly by subject. Utilizing longitudinal data covering 27years and over 1.2 million teachers in Texas, this study examines SET switching patterns relative to core subject teachers, utilizing discrete time hazard modeling, fixed-effect regressions, and geographic information system mapping. Results show that SETs switch schools at much higher rates, associated with experience, salary, and student demographics, yet generally transfer shorter distances than their peers. These findings highlight differential subject-specific labor market dynamics, suggesting targeted recruitment and retention strategies to address widespread shortages.  \nKeywords: special education, policy, retention, longitudinal studies, regression analyses, teacher shortages, teacher turnover, special education teacher, teacher labor market, teacher transfer  \nIntroduction  \nConcerns about teacher supply, demand, and shortages have intensified in recent years—and with good reason. Teacher preparation numbers have remained stagnant since the 2010s (Fuller, 2022), while teacher dissatisfaction (Kraft & Lyon, 2024) and the intention to leave the profession (Doan et al., 2023)—both strong predictors of actual attrition (Nguyen et al., 2020)—have reached record levels. In the 2024–2025 school year, approximately two-thirds of U.S. public schools reported difficulties filling vacancies with qualified teachers (National Center for Education Statistics (NCES), 2025). Teacher shortages are highly contextual, varying by geographic location (Nguyen, 2020), subject area (Mason-Williams et al., 2020), and both teacher and school characteristics (Clotfelter et al., 2007) . Urban, rural, low-performing schools, and those serving high concentrations of students living in poverty have historically faced greater challenges in recruiting and retaining teachers—particularly in special education and science, technology, engineering, and math (STEM)—compared to suburban, higher-achieving, Whiter, and more socioeconomically advantaged schools (Bettini et al., 2023; Goldhaber et al.,  \n2023), which are more likely to offer favorable working conditions (Simon & Johnson, 2015) . Much of this uneven teacher sorting has long been attributed to teachers starting their careers in schools with one or more of the former set of characteristics and then moving to schools that are suburban, higher-achieving, Whiter, and/or more socioeconomically advantaged (e.g., Simon & Johnson, 2015) . However, researchers have rarely tracked individual teacher career paths across multiple positions and schools to gain a comprehensive view of how switching schools impacts the labor market and shortage trends. A better understanding of these patterns could inform policies aimed at improving teacher  \nretention and addressing shortages in high-need areas.  \nResearch on teacher shortages has substantively and positively informed policy and practice, especially in terms of (a) novice teacher placement (e.g., Perrone & Meyers, 2023) and (b) teacher retention/turnover as a binary outcome (e.g., Nguyen et al., 2020), especially for ","cbCailCBVbJtNrkz","https://ap.wps.com/l/cbCailCBVbJtNrkz","pdf",8144196,26,"English","# Introduction\n## Teacher supply, demand, and shortage context\n## Teachers as \"switchers\" and limits of prior research\n## Study aims and focus on special education","[{\"question\":\"What issue does the study investigate in the teacher labor market?\",\"answer\":\"It examines how teachers switch schools within their subject field, with a specific focus on special education teachers.\"},{\"question\":\"How does the study analyze teacher switching patterns?\",\"answer\":\"It uses longitudinal Texas data and applies discrete-time hazard modeling, fixed-effect regressions, and GIS mapping to compare SETs with core subject teachers.\"},{\"question\":\"What do the findings suggest about special education teacher switching?\",\"answer\":\"SETs switch schools at higher rates than their peers, associated with experience, salary, and student demographics, and they generally transfer shorter distances.\"}]","From School to School - Examining the Contours of Within-Field Switching in the Special Education Teacher Labor Market | PDF",1792069383,66]