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Examining the Actor Coalitions and Discourse Coalitions of the Opt-Out Movement in New York: A Discourse Network Analysisby Yinying Wang - 2021 Background/Context: Since 2013, opting out of state standardized tests has become a movement—the grassroots, organized efforts to refuse to take high-stakes state standardized tests. In particular, opt-out rates in the state of New York have been consistently fluctuating around 20%. Purpose/Objective: This study aims to examine the actor coalitions and discourse coalitions that have propelled the opt-out movement in the state of New York—the movement’s epicenter with the highest opt-out rate in the United States. Conceptual Framework: This study is conceptually grounded in the advocacy coalition framework (ACF), a prominent conceptual lens to investigate the formation of coalitions and their impact on policymaking. The ACF posits that advocacy coalitions are forged by policy actors who have similar policy preferences. By contrast, differences in policy preferences are manifested in the discourse that serves to defend or propose coherent arguments as justifications for policy preferences held by the opposition coalitions. Research Design: This study compiled the Opt-out Discourse Data Set by using data from 323 press articles and 52 archival documents from 2015 to 2018. Each news article or archival document was coded with three variables: movement actors, statements articulated by the actors, and the actors’ sentiment toward the statements. An actor-statement bipartite network, an actor coalition network, and a discourse coalition network were created, respectively. Next, Freeman degree centrality was calculated to identify major actors and their statements. The network metrics of density and connectedness of the two competing coalitions were calculated to compare the coalitions’ network structure. Findings: In the actor coalition network, the movement advocacy coalition is clearly more densely connected than the movement opposition coalition in terms of the number of actors, coalition density, and coalition connectedness. The discourse coalition network shows similar patterns: the movement advocacy coalition is densely connected, as evidenced by the numbers of nodes in each coalition and the network metrics of coalition density and connectedness. Conclusions/Recommendations: This study concludes with a discussion on how the future of the opt-out movement depends on (1) how the movement advocacy coalition continues to amass power and influence in education policymaking, and (2) how the New York State Education Department exercises its power over implementation of the Every Student Succeeds Act (ESSA). Moreover, this article demonstrates the application of discourse network analysis to examine qualitative data in education research. The discourse network approach is particularly instrumental in explaining a policy output by identifying coalitions and their interactions within and across the coalitions. The purpose of this study is to examine the actor coalitions and discourse coalitions that have propelled the opt-out movement in the state of New York. Since the sweeping adoption of the Common Core State Standards in 2009 across the states, the Common Core and its implementation have met with growing resistance to high-stakes standardized testing (Hagopian, 2014). The resistance from education stakeholders (e.g., teachers, students, and parents) has grown into a movement to opt out of standardized testing (Wang, 2017). Nationally, over 670,000 students opted out of high-stakes standardized tests in 2015 (FairTest, 2016). In a 2017 national survey, 31.4% of the respondents supported the opt-out movement (Pizmony-Levy & Cosman, 2017). On Facebook, the Long Island Opt-Out Info public group has attracted over 24,000 members (Long Island Opt-Out Info, n.d.). On Twitter, the hashtag #OptOut was frequently used in tweets about the Common Core (Wang & Fikis, 2019). Opting out has become a movementthe grassroots, organized efforts to refuse to take high-stakes standardized tests (Bennett, 2016). The state of New York, with the highest opt-out rate in the nation, has been the epicenter of the opt-out movement (Wang, 2017). In 2014, approximately 60,000 students opted out of the New York State Assessment. The number grew rapidly to about 200,000 (20%) students in 2015. The opt-out rate peaked at 21% (approximately 230,000) in 2016 and dropped to 19% in 2017 (Samsel, 2017). In 2018, despite a slight decline in the opt-out rate to 18%, the number of students who opted out of the New York State Assessment was still over 210,000 (Hildebrand, 2018b). As a grassroots movement, parents who opted their children out of the New York State Assessment were not the only actors propelling the opt-out movement. Other actors who supported the movement include parents whose children were in public schools but did not opt out, parents whose children were homeschooled and/or in private schools, individuals without children who were supporting the movement, and some teachers (Pizmony‐Levy & Green Saraisky, 2016). These movement actors had relatively less authority-based power in education policymaking than education agencies and legislators. However, the movement has already led to some policy changes, ranging from cutting the number of questions in the state standardized tests, removing test time limits for students, reducing the number of testing days from six to four, hiring a new testing company, changing the Common Core State Standards to the New York State Next Generation Learning Standards, having teachers review the tests, to imposing a four-year moratorium on using test results to evaluate teachers and principals (Hildebrand, 2018b). In policymaking and implementation, actors with similar policy preferences and beliefs tend to bind together as a coalition (Sabatier, 1998). More importantly, to achieve their common objective, policy actors need to continuously identify allies to grow winning coalitions (Sabatier & Weible, 2007). How did opting out parentswho did not have much authority-based powercoordinate their efforts with other policy actors to forge a coalition in the opt-out movement? How did the actors articulate their views and beliefs to forge a coalition to propel the movement forward? The answers are important because the coalitionsalong with the power relations between themshape both policy processes and outputs (Ingold, 2011). Given that the opt-out movement in New York has already led to an array of policy changes, this study is particularly interested in the movement actors and how they forged coalitions through their views and beliefs about the movement. This study first draws on the advocacy coalition framework, and then connects the conceptual framework to the methodological approach by applying discourse network analysisan emerging, alternative analytical approach built on content analysis and network analysis (Leifeld, 2017)to uncover the actor coalitions and discourse coalitions of the opt-out movement. Specifically, this study seeks to answer two research questions: " Who were the central actors in the opt-out movement in the state of New York? " How did the central actors views and beliefs on the opt-out movement facilitate the formation of coalitions in the movement? ADVOCACY COALITION FRAMEWORK This study is conceptually grounded in the advocacy coalition framework (ACF), a prominent conceptual lens to investigate the formation of coalitions and their impact on policymaking (Ingold, 2011). The ACF (Sabatier, 1998) argues that advocacy coalitions are forged by policy actors who have similar policy preferences. Take climate change as an example. The coalitions of climate change issues emerged from the actors consensus view of economic implications of regulating greenhouse gases and the policy instrument for regulation (Fisher et al., 2013). In education, the opposition coalition of the Common Core forged around views about President Obama, testing, and misconceptions and negative conceptions about the standards (Polikoff et al., 2016). These similar policy preferences and views function as the glue holding coalitions together (Sabatier & Weible, 2007). By contrast, the differences in policy preferences are manifested in the discourse that serves to defend or propose coherent arguments as justifications for policy preferences held by the opposition coalitions (Hajer, 1995). As a result, the ACF posits the policy process as a competition between coalitions of policy actors who advocate their views about policy problems and policy solutions. Policy actors make public statements about a policy in order to signal their policy preferences to potential allies, convince other actors to adopt their policy preferences, or reduce their uncertainty by learning from other actors. A coalition, according to the ACF, thus emerges from similar policy preferences (Sabatier, 1998). Over time, similar policy preferences prompt policy actors to engage in a coordinated activity (Zafonte & Sabatier, 2004). For instance, in the networks of reading curriculum policymaking, the coalition emerged as the actors (e.g., educational organizations, school districts, businesses or business associations, private reading consultants, and philanthropic foundations) shared their policy preferences, and then collaborated over the policymaking process (Song & Miskel, 2005; Young et al., 2016). In the case of the opt-out movement, the New York State Education Department and the U.S. Department of Education shared a consensus view of sanctioning districts with a high opt-out rate. Their shared view led to coordination of activity: the U.S. Department of Education urged the New York State Education Department to sanction local education agencies with a high opt-out rate (i.e., exceeding 5%), and the New York State Education Department later punished the schools with the high opt-out rate by withholding grants (Schools Miss Out, 2016). Applying the ACF to the opt-out movement, the movement actors, along with their views and beliefs, can be conceptualized as networks. In such networks, movement actors are connected by their articulated views and beliefs about the opt-out movement. Movement actors within the coalition tend to hold similar views and present similar arguments; those who hold divergent views and present dissimilar arguments tend to forge competing coalitions. METHODS Grounded in the ACF, to uncover the actor coalitions and discourse coalitions of the opt-out movement, this study used the data collected from press articles and archival documents to conduct discourse network analysis. DATA SOURCES Data for this study came from 323 press articles and 52 archival documents on the opt-out movement in New York from 2015 to 2018. The opt-out rate in New York has been the highest in the country since the beginning of the movement; therefore, the movement in New York has garnered much media attention. A total of 323 press articles is the primary data source for this study. This is because media attention helps to define public understanding of a movement itselfwho its leaders are, what it wants, and how it seeks to bring about social change (Andrews & Caren, 2010, p. 841), rendering press articles a well-suited data source to fulfill the purpose of this study. To collect the press articles on the movement, the keywords opt out, education, and New York were used to set up Google Alerts to monitor and archive the press articles on the movement on a daily basis from January 1, 2016 to December 31, 2018. The press articles includes national liberal (e.g., The New York Times), centrist (e.g., Cable News Network), and conservative (e.g., Fox News) sources, as well as local sources such as The Long Island Press. I included only the press articles related to opting out of state standardized tests, excluding the articles on opting out of other issues, such as sexual education, religious education, and public schools. Although prior education policy research has used press articles as a data source (e.g., Pizmony-Levy, 2018), these are affected by biases, including selection bias (i.e., press selectively reporting events) and description bias (i.e., the potentially erroneous information in press; Earl et al., 2004). One way to address reporting biases is the use of multiple sources. To do so, this study examined 52 publicly available archival documents, adding to the reliability and credibility of the findings in this study. The documents were identified and included in this study if their hyperlinks were inserted by the press articles online, the Google searches by the document names mentioned in the press articles directed the researcher to the location the documents were published online, and they were germane to the opt-out movement in New York. Next, the archival documents were downloaded from the websites of an array of organizations (e.g., the U.S. Department of Education and the New York State Education Department) and groups (e.g., United Opt Out, Long Island Opt-Out, and the Leadership Conference on Civil and Human Rights). The documents include the organizations policy briefs, proposed legislation (e.g., the Enable More Parents to Opt-Out Without Endangering Resources Act introduced to the U.S. Congress in 2015), and press releases. Together, the 323 press articles and 52 archival documents make up the Opt-out Discourse Data Set. DISCOURSE NETWORK ANALYSIS Conceptually grounded in the ACF framework, discourse network analysis is a methodological advancement, offering a network analytical approach to investigate qualitative discourse data (Leifeld, 2017). A Java-based software called Discourse Network Analyzer was used to analyze the Opt-out Discourse Data Set in this study. Each news article or archival document was coded with three variables. First, the actor a ∈ A = {a1, a2, …, am} is the person or organization who revealed their views and beliefs about the opt-out movement. Using Discourse Network Analyzer, coding involved noting who revealed what views and beliefs about the movement. For example, the president of New York State United Teachers stated, They [test scores] are derived from a broken testing system & and are the foundation of a totally discredited teacher evaluation system (Spector, 2017, para. 16). The actor in this statement was coded as New York State United Teachers. Second, the statement s ∈ S = {s1, s2, …, sm} is a statement relevant to the opt-out movement articulated by the actors (Leifeld, 2013). To identify statements, I began by reading the press articles and documents, familiarizing myself with arguments about the movement. I then identified themes of the arguments and categorized similar arguments that repeated across the Data Set into statements. For example, many movement supporters articulated that Parents right to opt out should be protected (Statement 11). Whenever an argument fell under a statement, the statement was coded; therefore, the coding was deductive. The coding was performed by the researcher. While there is no measure of intercoder reliability in this study, the coded statements were explicitly articulated by actors without much room for speculation. A full list of 15 statements coded in the Discourse Data Set is shown in the Appendix. The third variable is the agreement relationship r ∈ R = {r1, r2} where r is a dichotomous variable capturing the actors’ sentiment toward the statement (Leifeld, 2017). Specifically, r1 is positive (1) if the actor refers to the statement in an affirmative way; r2 is negative (-1) if the actor rejects the statement or uses a negative connotation. For example, regarding Statement 8 (States should sanction the districts and schools with a high opt-out rate), the U.S. Department of Education agreed with the statement, whereas the New York State Allies for Public Education disagreed. The distinction between the positive and negative sentiment towards a statement is valuable because it reveals competing coalitions revolving around a statement. After coding the three variables for each press article and archival document, I exported the three variables from the Discourse Network Analyzer and imported them into the UCINET 6 network analysis program (Borgatti et al., 2002) to create an actor-statement bipartite network Gr,affiliation = (A, S, Er,affiliation) to connect movement actors and their statements. In such a network, a movement actor is connected via ties to a statement in a positive or negative way, in short er,affiliation (a, s) ∈ Er,affiliation, where Eraffiliation denotes the ties connecting movement actors and their statements. To identify coalitions, the actor-statement bipartite network was then converted into an actor coalition network in Figure 1 and a discourse coalition network in Figure 2. In the actor coalition network in Figure 1, the nodes represent the movement actors, and the ties connect the actors who articulated the same statements. For instance, five movement supportersopt-out parents, Opt Out Central New York (CNY) group, New York State United Teachers, Network for Public Education, and National Center for Fair and Open Testingarticulated Statement 1 (Standardized testing is part of the punitive system imposed on students and teachers); therefore, there are ties connecting all five actors. In the discourse coalition network in Figure 2, the nodes represent the statements; the ties connect two statements if they were articulated by the same actors. For instance, there is a tie connecting Statement 10 (Standardized testing is so profitable) and Statement 11 (Parents right to opt out of standardized testing should be protected), because both statements were articulated by opt-out parents, pro-opt-out teachers, and pro-opt-out parent teacher associations. Once the actor coalition network and discourse coalition network were constructed, Freeman degree centrality was calculated to identify the central nodes (i.e., major actors and their statements). Freeman degree centrality takes into account tie strength, indicating the relative importance and influence of a node within an overall network (Freeman, 1979). Specifically, the more central a node is in the network, the more important and influential the node is. Further, the network metrics of density and connectedness of the two competing coalitions were calculated to compare the coalitions network structure. Notably, discourse network analysis distinguishes itself from social network analysis. In social network analysis, the ties represent social relationships among actors. For example, in Pizmony‐Levy and Green Saraisky’s (2016) study on the opt-out movement, the ties represented what organizations contacted the same survey respondent regarding the opting out. Discourse network analysis, however, focuses on similarities of actors policy claims and preferences in discourse. Conceptually grounded in the ACF which argues that advocacy coalitions are forged by actors who have similar policy preferences, discourse network analysis can identify (1) actor coalitionsincluding competing coalitionsbased on the co-occurrences of the same policy claims and preferences articulated by a pair of actors, and (2) discourse coalitionsincluding competing coalitionsbased on the co-occurrences of the same actors who articulated a pair of policy claims and preferences. The frequency of co-occurrences is indicated by tie strength in the actor coalition network and the discourse coalition network, respectively.
ACTOR COALITION NETWORK The actor coalition network of the opt-out movement (see Figure 1) is composed of two coalitions. The movement opposition coalition on the left is formed by nine actors who opposed the movement (visualized as the square nodes), including education agencies (e.g., the U.S. Department of Education and the New York State Education Department), the anti-opt-out Civil and Human Rights Coalition, the opposing groups (e.g., High Achievement New York, Education TrustNew York, New York Campaign for Achievement Now, and Bellwether Education), and anti-opt-out school administrators (e.g., superintendents and school principals). By comparison, the movement advocacy coalition on the right is formed by 15 actors who advocated for the movement (visualized as the nodes in dots), including opt-out parents, pro-opt-out parent teacher associations, pro-opt-out teachers, teacher unions (e.g., New York State United Teachers), opting out advocacy groups (e.g., Long Island Opt-Out, Opt Out CNY group, United to Counter the Core, Stop Common Core in New York State, New York State Allies for Public Education, Rethinking Testing Group, National Center for Fair and Open Testing, Class Size Matters, and Network for Public Education), and pro-opt-out legislators (e.g., New York City Councilman Daniel Dromm and Capital Region Republican Assemblyman Jim Tedisco). Figure 1. The actor coalition network of the opt-out movement in New York. The movement opposition coalition is on the left; the movement advocacy coalition is on the right. Table 1. Results of Network Analysis of the Actor Coalition Network of the Opt-Out Movement in New York
In the actor coalition network, the node size represents how central an actor is in the network. The bigger the node is, the more central the actor is in the network. Each actors Freeman degree centrality Freeman degree centrality is displayed in Table 1. In the movement advocacy coalition, the opt-out parents have the highest degree (26.000), indicating they are the most central actors whose statements on the opt-out movement were shared by many other actors (e.g., pro-opt-out parent teacher associations, teachers unions, pro-opt-out teachers, and pro-opt-out advocacy groups). Specifically, the opt-out parents had the strongest tie (tie strength = 4) in the network, represented by the thickest tie in Figure 1, with pro-opt-out parent teacher associations. That is, opt-out parents and pro-opt-out parent teacher associations concurrently made the largest number (4) of the same statements in the actor coalition network. These four statements include: Statement 4 (High-stakes standardized testing does not accurately reflect learning or student achievement), Statement 6 (Opting out of standardized testing is an act of civil disobedience), Statement 10 (Standardized testing is so profitable), and Statement 11 (Parents right to opt out of standardized testing should be protected). By contrast, in the movement opposition coalition, the New York State Education Department had the strongest tie with anti-opt-out school administrators (tie strength = 3). That is, the two actors made the same three statements on the opt-out movement: Statement 7 (High-stakes standardized testing prepares students for their future), Statement 9 (Standardized testing is the only objective measure of student progress and thereby reveals inequity in education), and Statement 12s counterargument (The state's policy changes as a response to the opt-out movement are not lip service). The movement advocacy coalition (on the right) is clearly more densely connected than the movement opposition coalition (on the left), in terms of the number of actors, coalition density, and coalition connectedness (see Table 1). First, there are 15 actors in the movement advocacy coalition, but only nine actors in the movement opposition coalition. Second, the density of the movement advocacy coalition (0.173) is higher than that of the movement opposition coalition (0.097), indicating the actors in the advocacy coalition had more ties connecting the consensus view of the movement (i.e., the same statements) than those in the movement opposition coalition. Third, the connectedness of the movement advocacy coalition (0.350) is higher than that of the movement opposition coalition (0.150), denoting that the actors in the advocacy coalition were more closely connected to one anotherthrough their shared statements on the opt-out movementthan those in the movement opposition coalition. These network metrics indicate that the movement advocacy coalitions well-connected network structure stands in contrast with the opposition coalitions relatively fragmented network structure, explaining why the movement has gained traction and stayed relatively robust in New York to circumvent the movement opposition coalitions authority-based power over standardized testing. DISCOURSE COALITION NETWORK In the discourse coalition network (see Figure 2), each node represents a statement made by the movement actors. The bigger the node size is, the more central the statement is in the discourse network. The ties in the discourse coalition network represent that a pair of statements were made by the same actor. Therefore, the thicker the tie is, the more actors articulated the same pair of statements. Statement 4 has the highest Freeman degree centrality in the discourse coalition network (see Table 2), indicating that Statement 4 (High-stakes standardized testing does not accurately reflect learning or student achievement) is the statement that most frequently co-occurs with other statements in the Opt-out Discourse Data Set. Specifically, Statement 4 frequently co-occurs with Statement 3 (High-stakes standardized testing put excessive pressure on students and teachers), Statement 1 (Standardized testing is part of the punitive system imposed on students and teachers), Statement 6 (Opting out of standardized testing is an act of civil disobedience), Statement 10 (Standardized testing is so profitable), and Statement 11 (Parents right to opt out of standardized testing should be protected). Figure 2. The discourse coalition network. The dots denote the statements articulated by the policy actors. Table 2. Results of Network Analysis of the Discourse Coalition Network of the Opt-Out Movement in New York
The discourse coalition network in Figure 2 shows two competing discourse coalitions. On the left, there are Statements 2, 7, 8, 9, and 14 (visualized as the square nodes) that opposed the opt-out movement. The statements on the right (visualized as dots) are the ones that advocated for the movement. Like the actor coalition network, in the discourse coalition network, the movement advocacy coalition (on the right) is clearly densely connected, as evidenced by the numbers of nodes in each coalition and the network metrics of coalition density and connectedness (see Table 2). To elucidate how the statements were articulated by the movement actors to forge coalition ties with other actors, here I take a fine-grained look into the statements in the movement advocacy coalition and the opposition coalition, respectively. Discourse of the movement advocacy coalition. In the discourse of the movement advocacy coalition, the most central statement is Statement 4: High-stakes standardized testing does not accurately reflect learning or student achievement. This statement was articulated by most actors in the movement advocacy coalition (e.g., opt-out parents, pro-opt-out teachers, pro-opt-out parent teacher associations, Long Island Opt-Out, New York State United Teachers, Rethinking Testing Group, Network for Public Education, and Class Size Matters). For instance, a teacher said, I read some of the test questions, and Im, as an adult, not sure of what answer theyre looking for. Some of the readings are dreadful (Markowicz, 2018, para. 15). In Figure 2, closely connected to Statement 4 is Statement 1 (tie strength = 3): Standardized testing is part of the punitive system imposed on students and teachers. The strength (3) of the tie connecting Statement 4 and 1 indicates that three movement advocates articulated both statements: opt-out parents, New York State United Teachers, and Network for Public Education. The strong tie between Statement 4 and 1 indicates that three movement advocates supported the opt-out movement because they believed standardized testing does not accurately reflect learning or student achievement, and they were against the policy that linked student test scores with teacher evaluation. Statement 4 has the strongest tie (tie strength = 4) with Statement 3 (High-stakes standardized testing put excessive pressure on students and teachers) in the discourse network (see Figure 2). The tie strength (4) indicates that four movement actors articulated both Statement 4 and 3. These four actors are opt-out parents, Network for Public Education, Rethinking Testing Group, and Long Island Opt-Out. Both Statement 4 and 3 indicate that the movement aims not to participate in the high-stakes standardized testing, because the testing fails to accurately reflect learning or student achievement (Statement 4) and it puts excessive pressure on students and teachers (Statement 3). In fact, excessive pressure on students was the primary reason that Jeanette Deutermann founded the Long Island Opt-Out group on Facebook after her son suffered from test anxiety. Many educators said, the standardized tests unnecessarily humiliate students with special needs, pushing the children to lose their already wobbly self-esteem and hinder their learning (Finch, 2016, para. 8). Another strong tie in the movement coalition network is the one connecting Statement 4 and 11 (tie strength =3). The three movement advocates who articulated both statements are: opt-out parents, pro-opt-out parent teacher associations, and New York State United Teachers. Statement 11 (Parents right to opt out of standardized testing should be protected), in particular, is a response to Statement 8 (States should sanction the districts and schools with a high opt-out rate) articulated by the movement opposition coalition. New York City Councilman Daniel Dromm argued that the New York State Education Department has not done an adequate job of informing parents of their rights (Donachie, 2016, para. 3), even though the City Council approved a resolution on March 31, 2015, requesting the State Education Department to amend the Parents Bill of Rights and Responsibilities to include information about how parents can opt their children out of testing. The movement advocates claimed that education officials not informing parents of their right to opt-out contributed to the opt-out population skewing toward wealthy and White families. Further, Capital Region Republican Assemblyman Jim Tedisco wrote a letter to Regents Chancellor Betty Rosa, asking for her support for the Common Core Parental Refusal Act, which codified the parents right to opt their children out of tests (Willard, 2016). Moreover, the movement advocacy coalition considered the State Education Departments policy changes as minor, cosmetic changes and lip service (Statement 12). Responding to the opt-out movement, the New York State Education Department changed some policies, including imposing a four-year moratorium on using test results to evaluate teachers and principals, and reducing testing time from six days to four days (Hildebrand, 2018a). However, these policy changes were insufficient to restore trust and confidence in the system," said Jolene DiBrango, executive vice president of New York State United Teachers (Hildebrand, 2018b, para. 21). Lastly, the movement advocacy coalition framed the movement as an act of civil disobedience (Statement 6). Many opt-out parents and pro-opt-out teachers saw standardized testing as part of a corporate takeover agenda to wring profits from public education by charging districts for testing costs and selling student data to businesses (Taylor, 2016). A teacher who has proctored the exams many times said, The only people who benefit from the current test structure are the testing companies (Markowicz, 2018, para.14). The hashtag #TestingIsSoGreen was thus coined on social media (Statement 10). Therefore, opting out of standardized testing is a means to resist the flawed testing system in education. Discourse of the movement opposition coalition. In the discourse of the movement opposition coalition, the most central statement is Statement 8: States should sanction the districts and schools with a high opt-out rate. This statement has created glaring tensions where the two competing coalitions clashed. On the one hand, the U.S. Department of Education sent a letter to all state school officials in December 2015, warning of the potential loss of Title I funds and urging states to sanction local education agencies with a high opt-out rate by withholding funds and lowering school ratings (Strauss, 2016). The high opt-out rate was again addressed in the Department of Educations proposed regulations, which state: failure to meet the 95 percent participation rate requirement is factored in the States accountability system in a meaningful, publicly visible manner through a significant impact on a schools performance level or summative rating, identification for targeted support and improvement, or another equally rigorous, State determined action, thus providing an incentive for the school to ensure that all students participate in annual State assessments. (Elementary and Secondary Education, 2016, "200.15) In 2016, citing the high opt-out rate, the New York State Education Department kept 99 schools off the Reward School list, and 16 New York City schools were ruled ineligible for up to $75,000 in grants (Schools Miss Out, 2016). The schools loss of funding, according to the Regents Chancellor Betty Rosa, were unintended consequences. In 2018, the New York State Education Department proposed a plan to penalize districts with an opt-out rate over 5%. Under the proposed penalties, districts and schools with a high opt-out rate would not only be placed under public school registration review, which could eventually lead to school closure, but also have to set aside part of their Title 1 funding to improve test participation rates (Hawkins, 2018). After receiving about 2,000 comments from the actors in the movement advocacy coalition, the State Education Department rescinded some penalties in September 2018. In addition, some opt-out parents claimed that they and their children were harassed and intimidated for exercising their right to opt out of the state standardized tests (Statement 13). Yvonne Gasperino, founder and administrator of the Stop Common Core in New York State Facebook page, said harassment and intimation were in the form of favoritism & grade extortion, personal phone calls by some teachers trying to influence the parents decision, bribery via contests with monetary or other rewards, and exerting authority over the children who refused. & [as well as] children being reprimanded by some school officials for decisions their parents made on their behalf (White, 2016, para. 9). Responding to the central statements (Statement 3 and 4) in the movement advocacy coalition, the opposition coalition articulated Statement 9 (Standardized testing is the only objective measure of student progress and thereby reveals inequity in education) and Statement 14 (Standardized testing is necessary because it can hold schools accountable). The New York State Education Department and some civil rights groups unequivocally asserted that standardized testing was the only objective measure of student progress, holding teachers and schools accountable. For instance, New York State Education Commissioner MaryEllen Elisa said, the tests are the only objective measure to compare and measure student progress (Stoianoff, 2016, para. 3). In a press release announcing their opposition to the opt-out movement, 12 national civil and human rights groups stated, Our commitment to fair, unbiased, and accurate data collection and reporting resonates greatest in our work to improve education. The educational outcomes for the children we represent are unacceptable by almost every measurement. And we rely on the consistent, accurate, and reliable data provided by annual statewide assessments to advocate for better lives and outcomes for our children. These data are critical for understanding whether and where there is equal opportunity. (Leadership Conference on Civil and Human Rights, 2015, para. 3) Further, responding to Statement 6 (Opting out of standardized testing is an act of civil disobedience) in the movement advocacy coalition, the movement opposition coalition frequently used Statement 2 (The opt-out movement is so white) to frame the movement as White, affluent families irresponsible behavior. Long Islands Nassau and Suffolk counties, two of the wealthiest counties in the country, have consistently had more than half of students opting out of the state standardized tests (Franchi, 2016). Education Commissioner MaryEllen Elia articulated that its clear higher-performing students are the ones who are opting out (Breidenbach, 2017, para. 2), and its fair to assume the statewide improvement would be even better if all these kids had taken the tests (Filler, 2017, para. 4). By contrast, less than 4% of the students in New York City opted out of the state standardized tests (Zimmerman, 2018). Charter schools and schools in urban school districts had the lowest refusal rates in the state (Spector, 2018). Nationally, approximately two thirds of African Americans (67%) voiced their opposition to opting out (Phi Delta Kappa International, 2016). The movement was thus described as ridiculous, selfish, and more than a little hypocritical (Riseman, 2016, para. 15), depriving parents, schools and taxpayer of valuable information about how well (or badly) we are educating our kids (Riley, 2016, para. 1). The opt-out parents were deemed as inadvertently making a choice to undermine efforts to improve schools for every child (Taylor, 2016, para. 2) according to a statement by a civil rights group. DISCUSSION The opt-out movement in New York presents a unique case in a state that has consistently had the highest opt-out rate in the United States. This study conducted discourse network analysis to uncover the actor coalitions and discourse coalitions of the opt-out movement in New York. The actor coalition network reveals the movement actors and their coalitions. The discourse coalition network illustrates two competing coalitions and their points of contention in the opt-out movement. The findings of this study have substantial policy and methodological implications, as the movement actors translate their views and beliefs on the opt-out movement into substantive changes in education policy. POLICY IMPLICATIONS The opt-out movement has already led to some policy changes regarding standardized testing. The policy changes include (1) shortening state tests by cutting the number of questions, (2) removing test time limits for students, (3) reducing the number of testing days from six to four, (4) hiring a new testing company, (5) changing the Common Core State Standards to the New York State Next Generation Learning Standards, (6) having teachers review the tests, and (7) imposing a four-year moratorium on using test results to evaluate teachers and principals (Hildebrand, 2018b). Following the ACF, the policy changes are not dependent on one single policy actors decisions but on the interaction of actors coalitions. It is critical for the coalitions to seek and accumulate resources, thereby amassing power to make policies in their favor (Sabatier, 1998). Thus, one primary challenge for the movement advocacy coalition is to translate their views and beliefs on the opt-out movement into education policy. To overcome such a challenge, the movement advocacy coalition has already begun to amass influence and power in education policymaking. Some opt-out parents ran for school board and won seats on their districts boards of education. In one district, three Long Island Opt-Out-endorsed board members won school board elections in 2015 (Franchi, 2016). In addition to amassing power at the local level, the Long Island Opt-Out group was active at the state level by strongly supporting the election of Todd Kaminsky (D-Long Beach) to the state senate, who sponsored the bill that untethered teacher evaluation from standardized testing scores (Kaminsky, 2016). Jia Lee, a special education teacher and an opt-out movement advocate, ran for the United Federation of Teachers President in 2016 and lieutenant governor in November 2017 (Veiga, 2018). Notably, many of the movement advocates remained wary as the statewide moratorium on using test results to evaluate teachers and principals would expire in June 2019. On January 23, 2019, both houses of the state legislature voted overwhelmingly to eliminate the requirement of using state test scores to evaluate teachers in the state of New York (Lovett, 2019). In contrast to the movement advocates ongoing effort to grow their coalition, those who opposed the movement have amassed the power endowed by the Every Student Succeeds Act (ESSA) to strengthen the opposition coalition. While ESSA does require at least 95% of public school students to participate in annual state assessments of student achievement, it grants control to each state over how the 95% participation rate is factored into the statewide accountability system (ESSA, 2015). Further, ESSA states that Nothing in this paragraph [on assessments] shall be construed as preempting a State or local law regarding the decision of a parent to not have the parents child participate in the academic assessments ("1111.[b][2][K]). With the states having control over the consequences of opting out and the parents right to opt out, state education agencies may use threats and punishment to suppress the opt-out movement. For instance, in 2018, the New York State Education Department proposed a plan to force the districts with an opt-out rate over 5% to set aside part of their Title 1 funding to improve test participation rates (Hawkins, 2018). Such a proposed plan drew ire from the movement advocacy coalition and might harm students, because diverting Title 1 funds would deprive students, particularly minority students and students with low socioeconomic status, of equitable education. In short, the future of the opt-out movement depends on (1) how the movement advocacy coalition continues to amass power and influence in education policymaking, and (2) how the New York State Education Department exercises its power over ESSA implementation. METHODOLOGICAL IMPLICATIONS This study demonstrates a network analytical approach to examine qualitative data in education research. Grounded in the ACF, this study operationalized the measurement of coalitions from the network perspective. Conceptualizing the opt-out movement as network structures, this study considers the movement actors as the nodes which are connected by their views and beliefs on the movement. Most empirical studies grounded in the ACF focus on beliefs rather than network structures, whereas many network analysis studies on policymaking fail to provide sufficient information about the content of the analyzed policies (Ingold, 2011). In this article, discourse network analysis is a fitting analytical tool that not only uncovers the network structure of coalitions of the opt-out movement, but also reveals how views and beliefs became congruent and help forge coalitions among movement actors. The discourse network analysis performed in this study provides an alternative network analytical approach to studying the opt-out movement. In Pizmony‐Levy and Green Saraisky’s (2016) network analysis of the opt-out movement, the nodes were the opt-out related organizations in various states (e.g., FL Opt Out, GA Opt Out, and CA Opt Out), and the ties represent the organizations contacted the same survey respondent regarding opting out. By contrast, this study first constructed an actor-statement bipartite network based on who articulated what statements in the Opt-out Discourse Data Set. The actor-statement bipartite network was then converted into an actor coalition network and a discourse coalition network. In the actor coalition network, the nodes are the movement actors, and the ties connect the actors who articulated the same statements. In the discourse coalition network, the nodes denote the statements; the ties connect two statements if they were articulated by the same movement actors. Such a network analytical approach creates an added value for education policy research. The discourse network approach is particularly instrumental in explaining a policy output by identifying coalitions and their interactions within and across the coalitions. In this study, the movement advocacy and opposition coalitions voiced contested views and beliefs about standardized testing and the opt-out movement. The contested views across the coalitions, along with the consensus views within the coalitions, provide insight into education policymaking on standardized testing and the movement. LIMITATIONS AND SUGGESTIONS FOR FUTURE INQUIRY This study has four major limitations. First, the data collected for this study might not provide a full, comprehensive view of the opt-out movement in New York. The data sources for this study are press articles and archival documents, suggesting the movement actors and coalition ties identified in this study are notable enough to be documented by media and archival documents. It is possible that some movement actors and their coalition ties are missing from the Opt-out Discourse Data Set compiled for this study. If movement actors use private communication channels via emails, phone calls, and face-to-face conversations, then there is no way for the researcher to know that some major movement actors and their coalition ties might be missing. More diverse data sources are therefore recommended for future inquiry. Second, this study only examines the state of New Yorkthe state with the highest opt-out rate in the country. While New York represents a unique case, the opt-out movement in other states merits further investigation as well. The opt-out students in New York were disproportionately White and came from families with relatively high socioeconomic status (Pizmony‐Levy & Green Saraisky, 2016); however, other states might not share the same racial, socioeconomic pattern. In Ohio, for example, there was not much disparity in the opt-out rate between White, wealthy communities and communities of color and low-income communities (Neill, 2016). Thus, further studies on the opt-out movement in multiple states are highly encouraged. Third, this study offers only a snapshot of the movement. Future researchers are recommended to continue examining how the coalitions evolve over time as a response to policy changes about standardized testing and the opt-out movement. Fourth, this study, which is conceptually anchored by the ACF, uses network structure to detect coalitions based on the similarity of actors policy preferences. The findings only revealed what policy preferences were articulated what actors, but did not examine why a certain actor revealed a particular policy preference. Future researchers are encouraged to look into why different actors articulate the same policy preference and which ideologies are salient in driving the actors development of discourse. References Andrews, K. T., & Caren, N. (2010). Making the news: Movement organizations, media attention, and the public agenda. American Sociological Review, 75(6), 841866. https://doi.org/10.1177/0003122410386689
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Zimmerman, A. (2018, September 17). Regents support a new way of evaluating charter schools and soften penalties for schools with high opt-out rates. Chalkbeat. https://www.chalkbeat.org/posts/ny/2018/09/17/regents-support-a-new-way-of-evaluating-charter-schools-and-soften-penalties-for-schools-with-high-opt-out-rates/ APPENDIX List of Statements in the Opt-out Discourse Data Set Statement 1: Standardized testing is part of the punitive system imposed on students and teachers. Statement 2: The opt-out movement is so white. Statement 3: High-stakes standardized testing put excessive pressure on students and teachers. Statement 4: High-stakes standardized testing does not accurately reflect learning or student achievement. Statement 5: Test preparation sacrifices student learning time. Statement 6: Opting out of standardized testing is an act of civil disobedience. Statement 7: High-stakes standardized testing prepares students for their future. Statement 8: States should sanction the districts and schools with a high opt-out rate. Statement 9: Standardized testing is the only objective measure of student progress and thereby reveals inequity in education. Statement 10: Standardized testing is so profitable. Statement 11: Parents right to opt out of standardized testing should be protected. Statement 12: The state's policy changes as a response to the opt-out movement are lip service. Statement 13: School administration pressures parents to have their children take the standardized tests. Statement 14: Standardized testing is necessary because it can hold schools accountable. Statement 15: Sanctioning the districts with a high an opt-out rate harms students of color.
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