Opting Out in the Empire State: A Geographic Analysis of Opting Out in New York, Spring 2015 & 2016
by Kathryn P. Chapman, Lydia Ross & Sherman Dorn - 2020
Background: Recently, states have experienced widely varying participation in annual assessments, with the opt-out movement concentrated in New York State and Colorado. Geographic variation between and within states suggests that the diffusion of opting out is multilayered and an appropriate phenomenon to explore geographic dimensions of social movements in education.
Purpose: The study analyzes the geographic patterns of opting out from state assessments in school districts in New York State.
Research design: We conducted linear regression and geographically weighted regression on district-level proportions of third- through eighth-grade students in local public school districts for 2015 and 2016 (n = 623), excluding New York City and charter schools. Independent variables included the district-level proportion of students with disabilities, identified as English Language Learners, and identified as White; census-based small-area child poverty estimates for the districts; and the geographic population density of the district. Linear regressions excluded racial and ethnic dummy variables to reduce collinearity problems, and geographically weighted regression limited geographically varying coefficients to child poverty and population density based on preliminary analyses.
Findings: The unweighted ordinary least squares (OLS) of district-level opting out in both spring 2015 and spring 2016 are weakly predictive as a whole (adjusted R2 < .20). In both years, population density was a statistically significant but low-magnitude predictor of change in opt-out behavior using OLS. The proportion of students with Individualized Education Plans was positively associated with opt-out behavior, and district-level child poverty was negatively associated with opt-out behavior. The proportion of White students was a statistically significant positive predictor of opt-out behavior in spring 2015 but not statistically significant for 2016, though with a coefficient in the same direction (positive). Analyzing the same data with geographically weighted regression more than doubled the adjusted R2 for each year and demonstrated that there were areas of New York State where the coefficients associated with child poverty and population density reversed direction, with suburban Long Island and the western upstate region as areas with a magnified negative association between district-level child poverty and opting-out percentages.
Conclusions: In the past five years, social networks have enabled the long-distance organizing of social and political movements in education, including opting-out and teacher walkouts. However, the long-distance transmission of ideas does not explain intrastate variations. In this study, geographically weighted regression revealed the local variations in relationships between opting-out and two key variables. Local networks still matter critically to social organizing around education.
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