Extreme Measures: A National Descriptive Analysis of Closure and Restructuring of Traditional Public, Charter, and Private Schools

IF 1.7 3区 教育学 Q2 ECONOMICS
Douglas N. Harris, Valentina Martinez-Pabon
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引用次数: 2

Abstract

We describe the levels, trends, and patterns of school closure and restructuring in the United States from 1991 to 2019 across all sectors using a near census of K-12 schools. Focusing on the years with the best available data, 2014-2018, we find that the annual closure rate of charter, private, and traditional public schools (TPS) were 5.1, 2.9, and 0.9 percent respectively. The annual restructuring rates are 2.0 percent for charter schools and 0.6 percent for TPS. Regression analysis shows that these differences in closure and restructuring rates by sector drop slightly after controlling for student and school characteristics. The strongest predictor of increased closures is low student enrollment, especially in private schools. In charter and traditional public schools, achievement measures predict closure and restructuring nearly as strongly as enrollment. While racial and income composition are weaker predictors of closure/restructuring, that they predict at all, after controlling for many other factors, raises some equity concerns. We also discuss ways in which the forces behind closure/restructuring may be difficult to uncover with this type of quantitative analysis.
极端措施:对传统公立、特许和私立学校关闭和重组的全国性描述性分析
我们通过对K-12学校的近人口普查,描述了1991年至2019年美国所有部门的学校关闭和重组的水平、趋势和模式。关注2014-2018年这一最优数据年份,我们发现特许学校、私立学校和传统公立学校(TPS)的年关闭率分别为5.1%、2.9%和0.9%。特许学校的年重组率为2.0%,TPS为0.6%。回归分析表明,在控制了学生和学校的特点后,各部门在关闭和重组率方面的差异略有下降。最有力的预测因素是学生入学率低,尤其是私立学校。在特许学校和传统公立学校,成绩指标预测关闭和重组的可能性几乎和预测入学人数一样大。虽然种族和收入构成是关闭/重组的较弱预测因素,但在控制了许多其他因素之后,它们完全可以预测,这引起了一些公平问题。我们还讨论了关闭/重组背后的力量可能难以用这种类型的定量分析揭示的方式。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
CiteScore
3.00
自引率
4.80%
发文量
46
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