A call for QuantCrit methodologies: Unpacking the need for a critical lens in school psychology research

Abstract

School psychology has heavily relied on quantitative methodology to create and sustain our knowledge of best practices regarding academic, behavioral, and mental health outcomes for students. Nevertheless, underlying assumptions of the neutrality of quantitative data have obfuscated how school psychology research has perpetuated oppressive ideologies and practices, which directly harm students from marginalized identities. This paper demonstrates the need for employing a critical lens when engaging in and consuming school psychology research that utilizes quantitative methods. One such framework is QuantCrit, developed in the United Kingdom, which intentionally integrates Critical Race Theory tenets into the development, analysis, and interpretation of quantitative data. We explore specific examples of the insidious ways that ‘presumed neutral’ quantitative approaches have led to the perpetuation of oppressive practices in the following key areas of school psychology research: (a) discipline disproportionality, (b) special education disproportionality, and (c) school accountability metrics. Furthermore, we provide recommendations for both utilizing and publishing quantitative research that moves school psychologists towards more equitable practices for children and families across the globe.

Keywords

QuantCrit discipline disproportionality special education disproportionality accountability measures international quantitative research

Introduction

As a discipline, school psychology has focused extensively on the use of quantitative methodologies to determine our evidence-based practices. In fact, a 3-year review of the top journals in school psychology indicated that over 78% of articles included quantitative methods to analyze their research questions (Grant et al., 2022). The use of quantitative methodologies is synonymous with positivist scientific philosophy (Park et al., 2020) and, given school psychology's focus on assessment, measurement and intervention efficacy, is thus vital to our field. This is not unique to school psychologists, as psychology has historically been and continues to be dominated by quantitative methodologies (Power et al., 2018). Within this context, it is critical to consider the (a) implicit assumptions, (b) inherent privileging of certain types of knowledge, and (c) limitations of the questions within quantitative methodologies (Zuberi & Bonilla-Silva, 2008). Such criticality can lead us to understand how statistics and quantitative methods have been created and used to perpetuate racism (Kulkarni et al., in press).

Quantitative methodologies encompass a broader approach to research than simply looking at specific analytic methods (e.g., regression, factor analysis). Though often unacknowledged, methodologies are influenced by the researchers’ positionality, understanding of how knowledge is constructed, value judgments about questions and topics, and approach to making sense of reality (See Walter & Andersen, 2016 for a detailed description of each of these facets). In their current form, quantitative methodologies stem from a post-positivist lens that centers on objectivity and neutrality (Sabnis & Newman, 2022). These assumptions (and others that will be further critiqued by applying a critical lens) are then imposed on the research process utilizing specific methods. Quantitative methods, therefore, are those that rely on the use of numerical data through mathematical, statistical, or computational techniques to make inferences about the way the world works (Walter & Andersen, 2016).

As we reckon with how our field continues to perpetuate oppression for minoritized youth through our practices and research (García-Vázquez et al., 2020), we offer an invitation to consider the use of a critical quantitative methodology, QuantCrit, as a way to move the field toward more equitable research practice. QuantCrit allows us to elucidate how current school psychology research replicates harmful practices using quantitative data as justification.

Tenets of QuantCrit

QuantCrit originated from the education field as scholars sought to integrate Critical Race Theory (CRT) tenets into a quantitative frame. There are five main tenets that QuantCrit scholars abide by in their research. The first tenet is the centrality of racism, both in the United States and in the global context. This tenet articulates that if we are not actively considering the ways racism shows up, we are inadvertently replicating dominant racial narratives in our work (Crawford et al., 2018). The second tenet calls into question a primary assumption of quantitative data – that numbers are objective and neutral. Instead, QuantCrit argues that numbers are not neutral and are instead influenced by our worldview, beliefs, and systems of knowledge (Lopez et al., 2018). The third tenet names the fact that racial categories have sociocultural meaning. Embedded in the ways we label races today is a history of seeing biological differences between groups of people. QuantCrit invites us to acknowledge that racial categories represent the racism that individuals experience in their daily lives, not any inherent biological differences (Gillborn et al., 2018). The fourth tenet notes that data cannot speak for themselves because data are often open to multiple interpretations. Therefore, we must center the perspectives of those most marginalized and historically silenced to truly unpack meaning in the data (Crawford et al., 2018; Walter & Andersen, 2016). The final tenet pushes researchers to question why we conduct research in the first place, recognizing that research is a political act and has the potential to move us toward social justice (Kulkarni et al., in press).

Quantcrit in an international school psychology context

QuantCrit's origins from a CRT framework are important to contextualize given the backdrop on U.S. soil, where slavery and racial capitalism are inherent to the country's foundations and current functions of educational systems (Gerrard et al., 2022). Although a criticism of CRT may be in its American origins and therefore its lack of international underpinnings (Gathii, 2021), its tenets are globally applicable, as the social constructs of race and racism are not unique to the U.S. educational context (e.g., Street et al., 2022; Warmington, 2012). Theories such as CRT, neo-racism (Lee, 2007), decolonization, intersectionality, and QuantCrit are thus apt for a global context, as they are expansive and continually evolving alongside social movements (Yao et al., 2018). For a field that is well-versed in data-based decision making (National Association of School Psychologists [NASP], 2020), such theories are thus crucial.

This paper looks at the following three areas of school psychology research through a QuantCrit lens: (a) discipline disproportionality, (b) special education disproportionality, and (c) school accountability metrics. These three areas of research were selected as entry points of common understanding in the field and can be viewed as methodological case studies. Additionally, each of these areas are directly related to harm that students experience within the education system. The purpose of this paper is not to problematize specific methods but rather to open up a conversation about issues in the broader methodological process (e.g., questions asked, data collected, interpretation, and recommendations). This paper is also not meant to be a primer for newcomers to critical approaches to school psychology. Instead, the authors invite readers to acknowledge any discomfort as part of the process of unlearning as we seek equity in the field of school psychology.

This paper is co-authored by six individuals who hold marginalized identities within academic spaces (please refer to author biographies for our positionality statements). The authors were all trained in predominantly white¹ institutions with quantitative coursework that advocates an objective stance. The writing of this paper was done through collaborative conversations among authors in a community-based approach to account for the insidious ways the authors may have internalized the neutrality of quantitative methodologies.

School discipline disproportionality

Discipline disproportionality refers to the pervasive overrepresentation of specific sociodemographic groups of students (e.g., race, socio-economic status, gender; Bottiani et al., 2018; Skiba et al., 2002) in exclusionary discipline relative to their representation in the overall student population. Discipline disparities have been documented consistently over the last 30 years; for example, Black students experience exclusionary discipline at three times the rate of non-Black peers in the United States, while Indigenous students are overrepresented in suspension and expulsion in Australia (Graham et al., 2022; Losen, 2015; Office of Civil Rights, 2014). Nevertheless, research has consistently shown that actual rates of student behaviors do not differ by race (e.g., Fabelo et al., 2011; Skiba et al., 2002). To understand the phenomena of disparate discipline, it is important to apply a QuantCrit approach to both the analysis and interpretation of data (Castillo & Gillborn, 2022; Kulkarni et al., in press).

Application of QuantCrit tenets to discipline disproportionality

Centrality of racism

Educational institutions are core pillars of society; they are central to maintaining and replicating existing systems and structures based in Eurocentric ideologies (Fasching-Varner et al., 2014). Researchers have specifically centered the role of anti-Black racism in the development and implementation of educational systems (Lorde, 1984; Shedd, 2015). As such, these institutions reflect and reinforce the dominant ideology of those in power (Lorde, 1984; Smith, 2013). Eurocentric normative behavioral expectations rooted in anti-Black oppression equate difference with deviance, reinforcing the role of educational institutions as arbiters of societal norms for expected behavior (Calais & Green, 2022). Preeminent school wide behavioral systems include procedures like creating and posting “three to five positive school-wide behavioral expectations” (e.g., Bradshaw et al., 2008). The presumption that there are specific behaviors that all students should (not) engage in irrespective of their individual needs, values, and cultural backgrounds, is grounded in tenets of white supremacy (Jones & Okun, 2001).

Beyond the creation of structures themselves, educators implement rules and consequences inconsistently and in ways that align with racial and cultural stereotypes, thereby perpetuating the racialization of discipline in schools (Picower, 2009). This serves to replicate historic and current stratified hierarchies and disparities. In fact, teachers report expecting Black youth to act in ways that would require escalation of enforcement in the United States (Kunesh & Noltemeyer, 2019). This expectation underlies differences in teachers’ behavioral responses starting from preschool (Gilliam et al., 2016). Similarly, teachers report being influenced by stereotypes related to Indigenous students in Australia (Riley & Pidgeon, 2018). Students recognize this differential treatment from teachers based on race, which leads to negative feelings towards school among minoritized youth (Leverett et al., 2022).

Teachers have been socialized to protect the hegemonic structures of whiteness through problematizing and punishing the behaviors of youth of color (e.g., Picower, 2009). Implicit bias serves as a powerful arbiter of responses to ambiguous behavior, as the conduit of racialized expectations which maintain systems of power (Skiba et al., 2011). Implicit bias is thought to influence discriminatory behavior through subconscious stereotypes, particularly when decisions are made without careful thought (Van den Bergh et al., 2010).

Numbers are not neutral

It is important to consider how numerical data are collected and analyzed, as this is foundational to our understanding of disparity. Calculations of discipline disproportionality are typically conducted by explicitly comparing marginalized groups’ experiences to the dominant (white) group, centering the dominant group experience as normative and only placing marginalized students’ experiences in relation to majority students (Cruz et al., 2021). This is problematic, as the reference group can obscure the experiences of marginalized individuals based on the setting. For example, in hypersegregated schools, schools with greater than 90% minoritized students, disparity risk ratios are often not calculated. Yet, recent calculations indicate that hypersegregated schools have higher average rates of overall discipline compared to non-hypersegregated schools (e.g., U.S. Governmental Accountability Office, 2016). Furthermore, these data may be under-representations of the true extent of the negative experiences of minoritized students, with underreporting of suspension data likely obfuscating the true extent of disparate experiences (Crenshaw et al., 2015; Losen & Martinez, 2020). When considering disproportionality data, explanations of differences in discipline experiences are crucial. Often, school or district teams may conclude that disparities in discipline are due to differences in race rather than acknowledging that these differences are due to racism and structural oppression (Castillo & Gillborn, 2022). Discipline disparities are real; however, differences in student behavior are not (Skiba et al., 2002). Assumptions regarding the neutrality in the quantitative data are problematic.

Girvan and colleagues (2017) highlight challenges of not thoughtfully engaging with calculations of disproportionality, including the fact that calculations of various metrics provide different information (e.g., high discipline environments vs. high disparity environments). Furthermore, there are a number of ways to calculate discipline disproportionality, including risk ratio, risk difference, risk indices, raw differential representation, days missed, and raw discipline rates; each of these metrics prioritize and highlight different aspects of discipline disparity and are sensitive to differences in reference group as well as number of students. This may impact the calculation of intervention effectiveness, overall impact, and stability (Girvan et al., 2017). It should be noted that each of these methods impact not only the calculations but also the interpretations. One clear example is the utilization of days missed (Losen et al., 2017) in addition to the often used risk ratio or risk difference metrics. The days missed metric provides information regarding the extent of the impact beyond simply the differential likelihood of experiencing suspension and helps quantify the extent to which students’ rights are violated as they experience greater losses of instructional minutes and opportunity due to longer suspensions for similar offenses (Losen et al., 2017). While it would be nice to imagine that simply selecting the “right” metric will alleviate these impacts, fundamentally, assumptions regarding the neutrality of data must be cautioned against. Scholars choose among these methods based on their priorities, convenience, and adherence to methods most represented in the existing literature, which reflects a legacy of centering whiteness (e.g., Sabnis & Proctor, 2021). When making decisions about both metric selection and comparison groups, researchers must be conscious of the impacts of the data sources and goals of analysis.

Categories are not natural

Racialized categories are key to the analysis of discipline disparity; however, the standardized structuring of racial and ethnic categories without attention to differentiating factors within each dataset and research question can obscure the experiences of marginalized groups (Grant et al., 2022). When researchers make the choice to disaggregate data, professional norms call for the use of broad racialized categories as sufficient. Instead, the intentional disaggregation of data with attention to the ways that racism and within-group heterogeneity impact the experiences of youth may support more accurate root cause analysis and appropriate structural change (Castillo & Gillborn, 2022). Research suggests that there are considerable inconsistencies in the likelihood of identifying discipline disparities in schools with large Latinx populations, with disparities reported in some settings (e.g., middle) and not others (elementary schools; Skiba et al., 2011). This is likely due to the failure of the overly broad category of “Latinx'’ to encapsulate the wide variety of ethnic and cultural groups throughout Latin and Central America, the Caribbean, and Mexico. This collapsing of diverse experiences into simple categories can obfuscate real differences in group experiences (Castillo & Gillborn, 2022). Castillo and Gillborn (2022, p. 8) suggest that it is important to avoid conclusions that reify racial categories as “a natural and fixed difference,” and it is essential to explicate the extent to which differences in discipline are due to racism rather than race. This is a trap which school personnel and school psychologists must avoid as we continue to center the systems of oppression which coalesce to harm minoritized students.

One poignant axis of categorization that is frequently overlooked in school research is that of colorism (Hunter, 2016). Anti-bias literature has revealed that bias and discrimination can be understood as a reaction to Afrocentric phenotypic traits and lead to differential outcomes on the basis of perceived proximity to whiteness (Hall, 2011). Critical theorists have called for disambiguation of the experiences of individuals from heterogeneous racial and ethnic groups in terms of skin tone stratification (Reece, 2019). With regard to discipline disproportionality, the categorization of youth by race and/or ethnicity alone likely obscures the diversity of within-group experiences. In schools, those youth with features more closely approximating whiteness (e.g., light-skinned, Anglo-coded facial features) are less likely than their more visible peers of color to receive out-of-school suspension (Hannon et al., 2013). Teachers’ implicit bias likely leads to reactivity to phenotypic traits, which would replicate differential treatment in other social structures, such as carceral systems (Pizzi et al., 2005). In sum, discrete race-based categories are inadequate for understanding the breadth and impact of school discipline.

Data cannot speak for itself

Discipline disparity has been used as a means to support the vilification of Black youth as conforming to stereotypes such as aggressive, dangerous, criminal, and non-compliant (Calais & Green, 2022). While initially touted as confirmatory evidence of racialized stereotypes by deeply problematic authors (whose names we do not cite)², subsequent work has consistently and unequivocally clarified that student rates of problem behavior do not differ by race (Skiba et al., 2002). The same data, indicating at least doubled rates of exclusionary discipline among Black youth, have been erroneously and harmfully interpreted as reinforcing social narratives of white supremacy. The presence of discipline disproportionality did not neutrally lead to the conclusion of racialized differences; the ubiquitous racist ideology that fundamentally shapes all of school psychology and education created these interpretations and must be rejected.

School discipline rates are multicausal; however, higher rates of discipline in schools with higher percentages of Black populations may reflect a more carceral approach in these schools (Shedd, 2015). Black students experience school environments that are more prison-like with harsher discipline rules, which reflect racialized attitudes regarding the need to control Black students rather than educate them (Shedd, 2015).

Hirschfield (2008) highlighted the parallels between the educational and criminal “justice” structures, particularly for students from minoritized groups. This approach, focusing on control and compliance rather than the growth of students, serves to further marginalize, exclude and harm Black students. More recent research by Shedd (2015) outlined the specific physical and psychological differences in the treatment of students based on racial background as tied to physical space. Black students are far more likely to attend schools that use material means of control that mimic prisons (e.g., metal detectors) and that employ police or security guards. These replications of the carceral prison system place students directly in harm's way (of police) as well as acclimatize them to the injustice system and the treatment outlined by society at large (e.g., imprisonment), which is just slavery by another name (e.g., Fasching-Varner et al., 2014).

Special education disproportionality

Special education can be defined generally as specialized instructional services tailored to support students with disabilities in academic settings (Rix & Sheehy, 2014). It is a broad term and is implemented differently across the globe depending on a country's legislation (Cooc & Kiru, 2018). For example, in the United States the Individuals with Disabilities Education Act (IDEA) governs the provision of special education for students with disabilities, and the identification of disability does not depend on medical diagnoses. Other countries, such as India, have legislation regarding services for disabled students that requires 40% of their schooling to occur outside of the general education setting and a medical diagnosis as evidence of a disability (The Rights of Persons with Disabilities Act, 2016). Additionally, implementation of special education law and inclusion of disabled students in general education settings is variable and is dependent not only on the legislature but also access to schooling itself (Byrd, 2010).

Disproportionality can be defined as either the under or over representation of a particular group, specifically minoritized individuals, in special education (Sullivan & Proctor, 2016). Despite extensive research on the topic, it continues to be controversial, with scholars observing that conclusions and policy recommendations drawn from studies can be contrary, variable, and often confusing (Kramarczuk Voulgarides et al., 2017). For example, recent reviews have highlighted that the interpretation of results can be driven by the theoretical perspective of the researchers (Cruz & Rodl, 2018), type of sample, and indeed, even statistical analyses chosen (Skiba et al., 2016). Internationally, given the heterogeneity in educational policy around the world (Kohli, 2019), complex socio-cultural phenomena unique to each geographic area contribute to over and under representation in special education. Within this context, disproportionality can be a multifaceted phenomenon that quantitative data, by itself, cannot fully explain.

For example, in some countries, due to lack of access to special education in rural areas, as well as barriers to schooling itself, it is more likely that urban families and families of higher socio economic and caste status gain access to special education services, leading to under-representation of marginalized children (Bruce & Venkatesh, 2014). In Eurocentric or colonizing countries, this pattern is often reversed, and over-representation of marginalized children in special education occurs, especially in soft disability categories like emotional disturbance and specific learning disability (Cooc & Kiru, 2018). QuantCrit provides readers and researchers an important framework within which to situate special education literature.

Application of QuantCrit tenets to disproportionality in special education

Centrality of racism

When exploring special education disproportionality, it is essential to understand the ways in which ability and race intersect. Critical disability studies, or DisCrit, draw on the social conceptualization of disability, which situates social arrangements (e.g., built environment, elusive communication norms) as privileging non-disabled people and disadvantaging those with disabilities (Sabnis & Bueno Martinez, 2021). The authors of DisCrit also took inspiration from Intersectionality Theory (Annamma et al., 2013), which provided a blueprint for their subsequent mapping of how racism and ableism intersect in the lives of racially minoritized disabled people. DisCrit holds that racism and ableism are mutually constitutive (Annamma et al., 2013; Sabnis & Bueno Martinez, 2021).

In the context of special education disproportionality, this tenet suggests research and practice must recognize race and disability as mutually influencing. DisCrit also holds that whiteness and ability are treated as property in which both whiteness and ability bring benefits to individuals who hold those identities. Per the U.S. Department of Education (2018), children of color with IEP's have poorer postsecondary school outcomes than children of color in general education. Of note, oppressive systems, such as economic differentiation between communities of color and predominantly white communities, have been cited as contributing causes for these differences in academic outcomes (Cramer et al., 2018). Thus, children of color who are erroneously identified for special education services are being further marginalized within the school system—both by race and the social identity of disability.

Numbers are not neutral

Two schools of thought have primarily emerged to explain the source of special education disproportionality: practice-based explanations and sociodemographic-based explanations (Kramarczuk Voulgarides et al., 2017). This tenet highlights that the datasets used in these studies are not entirely objective and are a reflection of the systemic bias that exists in our schools (Gillborn et al., 2018). Quantitative methods, by virtue of being positivist, do not strip data of subjectivity. The assumption that complex mathematical models make data neutral has led to particularly controversial explanations of results. For example, when a child's race or their parent's education or socioeconomic status are found to predict disproportionality, these variables are often framed as causes and precursors of negative educational outcomes, thereby implying a need for more intensive services provided by special education protections (Sablan, 2019).

The subjectivity of data can be illustrated by considering how disproportionality can be associated with the same variable in opposing ways, especially in an international context. For example, sociodemographic variables, such as higher socioeconomic status, can predict over-representation in India and Kenya but under-representation in the United States (Bruce & Venkatesh, 2014). Thus, explanations and, by extension, statistical models that claim to separate out sociodemographic variables (e.g., race, caste, gender) as causes of educational outcomes like disproportionality are ignoring systemic confounds like a country's educational policy and cultural history.

Categories are not natural

Decades of critical study and investigation have led scientists from numerous disciplines to conclude that, rather than a biological descriptor with genetic backing, race is a social construct (Zuberi & Bonilla-Silva, 2008). Thus, QuantCrit leads us to consider whether the categories (e.g., race, nationality) we use are natural and neutral or if they are attempts to reify human perceptions of the world around us. The application of QuantCrit tenets might lead one to conclude that special education disproportionality is more a function of racism than it is of race; yet careful considerations of racisms’ implication in special education (e.g., adultification of Black children, mental health effects of the model minority myth) are rarely explored in the school psychology literature, with the exception of scholarly contributions from three generations of Black scholars in the field (Proctor, 2022).

More broadly, any study on disproportionality must frame the problem within the local context (Cooc & Kiru, 2018) as well as the historical underpinnings of categories chosen to be represented. For example, though South Asian students are underrepresented in special education both in the United States (Sullivan et al., 2020) and in England (Dyson & Gallannaugh, 2008), such underrepresentation is heavily impacted by the immigration history of South Asian families to these countries (Gabel et al., 2009), thus changing the way their race, and thus their experiences with racism, intersects with the education system. Simply collecting demographic information for disaggregation purposes does not allow a social scientist to draw broad, generalizable conclusions about the implicit bias, anti-Blackness, and white supremacy that influences special education referrals (Crossing et al., 2022). Unfortunately, without accounting for racism and the harms and traumas with which it is associated, much of the nuance cannot be captured, analyzed, or reported accurately (Crossing et al., 2022).

Data cannot speak for itself

Given that QuantCrit encourages eschewing context-free, atheoretical perspectives on educational outcomes (Gillborn et al., 2018), it can be especially useful in international contexts. For example, more recently, and with renewed vigor, scholars have decried the unstated omnipresence of whiteness (e.g., white norms, white supremacy, white epistemologies) as an obstacle to the advancement of studying racism in the social sciences (Buggs et al., 2020). Congruent with the conversation in discipline disproportionality, this could mean de-centering the majority group (e.g., white students) as the comparison in quantitative studies and highlighting the heterogeneity of outcomes within the marginalized group (Castillo & Gillborn, 2022). This is especially important in an international context, as samples from low to middle income countries in the global south are rarely published (Nielsen et al., 2017), leading to an understanding of disproportionality from primarily a Western point of view and erasing the vast diversity in educational settings across the globe. Additionally, this tenet urges researchers to highlight the voices of marginalized populations rather than make them objects of study (Castillo & Gillborn, 2022). A nuanced, systems-level consideration of racism in disproportionality might involve interviews with decision-makers or affected families. For example, a special education disproportionality study can utilize mixed methods and include narratives of the marginalized populations it aims to study (e.g., Cruz et al., 2021). All of these data collection opportunities should be chosen via a systems-level decision-making process with a focus on generating counternarratives to enrich quantitative data (Crossing et al., 2022; Proctor, 2022).

Accountability metrics

Since the enactment of the U.S.’ No Child Left Behind (NCLB) Act in 2001, countries across the globe have followed suit in seeking to hold schools accountable through the use of high-stakes testing and accountability metrics. Student achievement (and ultimately school effectiveness) was defined primarily in terms of student academic attainment, with particular emphasis placed upon the achievement of criterion goals on standardized tests. Failure to meet these goals, known as Annual Yearly Progress (AYP), meant corrective actions, up to and including school closure. This approach has spread across the globe, with similar policies emerging in other countries; for example, in 2009 South Korea instituted a similar policy, “No Student Below Basic [Competency]” (NSBB), to promote competition between schools and incentivize academic improvement (see Lee & Kang, 2019 for a direct comparison of the U.S. and South Korean policies). Similar to NCLB and the use of high-stakes testing to measure accountability in schools, international policies have provided specious evidence around improving school capacities and addressing inequities in educational opportunities (Lee & Kang, 2019). Though NCLB has since been replaced by the ESSA in 2015, test-based accountability systems continue to drive educational agendas globally (e.g., in Qatar and Finland; Arbuthnot, 2017). Despite the varied educational and cultural contexts in which testing can occur internationally, measurement and myopic focus on student performance alone seem to be misguided attempts at improving educational attainment (Arbuthnot, 2017; United Nations Educational, Scientific and Cultural Organization [UNESCO], 2017).

Accountability metrics are only part of the international picture. Since 2010, half of the world's countries have been able to provide progress regarding national education plans and budgets (UNESCO, 2017), begging the question of accessibility/capacity for different nations’ data collection and progress monitoring. Though global shifts in neoliberal practices to demonstrate “achievement”–and thus, accountability–are not new, there have been more recent shifts in how accountability in education is addressed on an international level. In 2015, the United Nations Sustainable Development Summit adopted a new global education goal, seeking to “ensure inclusive and equitable quality education and promote lifelong learning opportunities for all” (UNESCO, 2017, p. 3). In response to this goal, however, it is clear that “not all accountability methods are currently helping” to achieve goals of educational equity (UNESCO, 2017, p. 14). Instead, these metrics may target and punish the marginalized communities that accountability policies were meant to uplift. As implementation of these assessment mandates develop over time, critics have highlighted the need to move beyond overreliance on test scores and move towards a more inclusive definition and measure of “student success.” However, many approaches that have been proposed or implemented lack critical quantitative nuance and thus reinforce existing ideas regarding ability and the acceptability of existing structures of inequity.

Application of QuantCrit tenets to accountability metrics

Centrality of racism

One of the key concerns with current accountability metrics is that they exist within a color-evasive framework. Their creation emerged from the desire that all students should be receiving high quality education, which would be demonstrated by students’ performance in school. If students were struggling, the cause of that struggle was connected to the actions of teachers and administrators (Verger et al., 2019). Diem and Welton (2020) further note that this approach also stems from an individualistic stance in that schools are seen as independent actors that are positioned to address student needs. This connection between student achievement and school performance does not take into account how structural forces impact students’ educational outcomes. Using a QuantCrit lens, we can identify the structural racism that impacts our current education system (Darling-Hammond, 2007). By maintaining a color-evasive perspective, one does not see how racist education policies have directly contributed to the lack of educational opportunities for marginalized youth (Diem & Welton, 2020; Watkins, 2001).

Ignoring the impact of racism on students’ achievement has dire consequences. Accountability metrics have been weaponized against schools with high percentages of Black and Brown children through the infiltration of business models in the education system, resulting in the removal of the local community from educating their children (Dixson et al., 2013). These metrics are in alignment with a neoliberal framework that espouses that competition is more effective than collective engagement and that the market system can override systemic inequalities (Au, 2016). This enactment of the cultural belief in meritocracy masks the structural advantages of the more privileged. Nevertheless, across the U.S. and international contexts, school privatization has not led to meaningful changes in test scores (Carnoy, 2017). While there are examples of successful charter schools, these do not impact the majority of children who cannot access them. For example, many of these schools selectively admit students, limiting the number of children with disabilities and “non-desirable” school traits enrolled (Chapman & Donnor, 2015). Buras (2014) coined the term conscious capitalism to describe how the privatization of schools is framed as a tool to increase equity for students without naming how it serves to reify deficit narratives, segregation, and ongoing economic inequality.

Another way accountability metrics have been weaponized concerns the types of curricula students have access to in “underperforming” schools. In these settings, instruction tends to be teacher-centered and focused on rote learning (Au, 2016). Student achievement data have been used to promote deficit thinking in educators and policymakers when working with marginalized communities (Delpit, 2012). Teachers often feel a push to engage in pedagogy that centers the acquisition of discrete skills without holding space for the broader goals of education to build critical and competent global citizens (Brill et al., 2018). This narrowing of the curriculum serves to reify race and class-based differences in expectations for learning.

Numbers are not neutral

Along with the research on discipline and special education disproportionality, there is also an assumption that the numbers gained for accountability assessments are neutral. In fact, numbers and statistics have often been used to perpetuate a white supremacy agenda (Zuberi & Bonilla-Silva, 2008). For example, publishing the accountability rankings for schools has been described as a way to offer parents choices in the selection of a school for their children (Verger et al., 2019). Theoretically, parents could engage in a market-based education system, allowing them to use data to make informed choices about where their child attends school. In reality, only well-resourced parents actually have such choices, which leaves marginalized families and communities in schools that have limited resources (Power & Frandji, 2010). Even if all had access to equitable options, accountability metrics would continue to promote capitalistic promise and neoliberal veneer of choice because of the non-neutral ways that such data are currently collected, analyzed, and communicated.

Growth metrics have also been used to systematically ignore contextual factors in traditional accountability metrics. Within this process, schools are deemed effective if they demonstrate growth from previous years’ student achievement scores (Betebenner, 2011). Schools that demonstrate high levels of change in student achievement are lauded for their institutional effectiveness. On the surface, growth metrics seem to promote progress and process over outcome; however, they are simply another way to enforce productivity requirements and continue to stress benchmarks for proficiency gains as a measure of student success, regardless of nuanced contexts. Centering student achievement allows for the focus to remain on marginalized school communities as at fault (e.g., students, teachers, families) rather than addressing the ultimate causes, including structural inequalities such as economic inequities, segregation, and inequitable resource allocation.

Categories are not natural

The use of accountability metrics was founded on the relative ease of connecting academic outcomes to teacher and school performance. Though these two variables are mediated and moderated by a variety of demographic variables, many times data are only examined in light of a few demographic variables. While understanding student outcomes is a complex process, educational policymakers use simplistic accountability data to make decisions about curriculum, resource allocation, and school viability (Diem & Welton, 2020). Restricting interpretation of data to categories without considering context and other methods of data collection (e.g., counterstories, multiple methods) calls into question their utility for informing the aforementioned decisions. Quantitative data in and of itself is not harmful; rather, the lack of a critical lens around historical and contextual nuances when categorizing numbers can have dire implications for marginalized populations in particular.

Value-added analyses have been suggested as a way to address the limitations of these traditional accountability metrics, but they continue to perpetuate similar issues.³ Value-added analyses predict student scores based on their age, social background, and previous academic achievement and reward teachers based on their contributions to a student's academic achievement. If students’ actual scores are higher than what is predicted, then the school has demonstrated effectiveness (Amrein-Beardsley, 2014). The decision to control for external variables is limited in scope because it does not account for how these external variables interact with school performance and student achievement. Such statistical control of the context that schools are situated in gives a false idea that data are meaningful apart from the context in which they are collected (Power & Frandji, 2010). Regardless of the type of analyses and constructs measured, if data are examined in a vacuum devoid of context, they continue to perpetuate harm caused by biased decision-making processes, which are steeped in current practice (Tatum, 2017).

Data cannot speak for itself

Accountability metrics have reflected the dominant (i.e., racist; Gillborn et al., 2018) narrative of what education is supposed to value and thus measure; these metrics speak on behalf of white values characterizing them as factual, important, and objective indicators of how students and schools are performing, thereby perpetuating the marketization of education (Power & Frandji, 2010). Most importantly, accountability metrics do not seem to address the “elephant in the room” that racism permeates through numbers and results—not separately or as a categorical variable. These metrics cannot stand on their own or to justifiably group student and school performance through numbers gathered on academic proficiency. Thus, through this tenet of QuanCrit, it can be argued that accountability measures themselves reflect racist assumptions that achievement and proficiency in academic subject matters are what educational systems should inherently value and report on. However, such measures are clearly steeped in white assumptions that may actually be counterproductive for uplifting the very populations that accountability metrics claim to serve. These value-laden assumptions in academics parallel insidious behavior and ability assumptions that are inherent in our education system.

As previously mentioned, not all countries nor educational entities have the realistic capacity nor governmental support to collect quality data beyond what is valued by historically oppressive and dominant forces. Further, each country's unique cultures and contexts carry different historical weights and effects. Finland, for example, may show promising data around discipline outcomes and practices; however, is it fair to compare data from Finland and the U.S. when Finland's historical legacies of racial, migrational, cultural, and linguistic trauma differ vastly from those of the U.S. (whose population is more heterogeneous)? The numbers themselves do not reflect on such contexts, necessitating data collection that moves beyond test scores and white research questions. Instead, it is critical to examine who is asking the questions around data collection and for what purpose. More specifically, CRT and QuantCrit would seek to collect data that tell a counterstory to mainstream narratives of accountability metrics. Instead of measuring what has been deemed valuable since the colonial schoolhouse, what would it look like to measure that which is valued by those whose voices are the most stifled?

Conclusions

School psychology has a strong focus on the utilization of evidence-based practices; however, the field needs to address the assumptions of equal application of practices across settings, sociodemographic groups, and cultural groups. Researchers are increasingly calling for culturally responsive practices in the application of intervention (e.g., making adjustments to increase the cultural relevance of existing practices to minoritized groups [e.g., Black to Success, Heidelburg & Collins, 2021]). Yet, it's important to call out the extent to which systemic structures influence thinking about the very disparities they intend to correct.

Social justice orientation

A social justice orientation threads all four of QuantCrit tenets, however, the fifth tenet specifically reminds us that all research is inherently political (Gillborn et al., 2018). The research that we create and consume has the potential to support institutional power structures in replicating oppression. This tenet is salient across all three of the case studies presented in this paper. As Foucault articulated, institutions gain power and authority in their decision-making on the basis of knowledge construction that determines what is deviance (Sugarman, 2014). This is especially relevant in the case of special education disproportionality, given that education policy is often driven by research (e.g., Green, 2019), and context-free, uncritical approaches to disproportionality stand to harm marginalized students the most (Voulgarides et al., 2017). QuantCrit presents an alternative to causal theories that conclude that special education disparities are due to artificially constructed categories like race (blaming within-child deficits) and instead implicates racism.

Within discipline disproportionality, it is not sufficient to merely discuss discipline rates but rather we must contextualize these numbers in the backdrop of existing and interlocking systems of oppression (Crenshaw, 1989). Researchers evaluating the effectiveness of interventions to address discipline disparities have often focused efforts on methods of changing or shaping student behavior (Jain et al., 2014), usually focused on the implementation of school wide behavioral systems such as PBIS [Positive Behavior Intervention Systems] (Losen, 2015), restorative justice (Davison et al., 2022), or behavioral modification strategies. However, this implies that these disparities are somehow due to the behavior of the students rather than the behavior of adults in the context of systems. Thus, interventions touted as “universally effective” or evidence-based practice are first and foremost methods of control, focused on putting students more in line with established behavioral expectations. When considering targets of intervention, an uncritical lens fails to contextualize the data and instead assumes that decreasing overall discipline rates will change differential outcomes for Black students, ultimately replicating systems of oppression by failing to question them. A critical lens must be taken when using or interpreting data related to discipline disparities, as failure to understand or appreciate systemic factors may lead to focus on the wrong actors (i.e., students rather than adults). Therefore, utilizing a version of PBIS that critically considers the context of children's lives and centers the relational connection between these children and the school adults invites us to move beyond prescribed behavioral norms into new ways of engaging in these relationships (Corcoran & Edward Thomas, 2022).

One way to embody a social justice orientation in QuantCrit is by centering the voices of marginalized individuals and challenging hegemonic narratives through the use of counterstories. Within an accountability metric framework, Perrelli & Vaccaro (2022) elucidate a counterstory that centers the lived experiences of the students, staff, and faculty in a school deemed “underperforming.” Their analysis demonstrates a mismatch between the accountability metrics and the perspective of school community members in understanding school success. By centering experiential knowledge, the authors elucidate the ways the school serves to advocate, challenge, and support students and families in the midst of the structural inequalities around them (Perrelli & Vaccaro, 2022). A critical analysis of accountability metrics demonstrates that schools, in and of themselves, have a small impact on student achievement. Instead, we will only see long lasting changes in student achievement if we address the structural inequalities inherent in our society (Power & Frandji, 2010).

Lastly, a social justice orientation places a responsibility on researchers to introspect on their own positionality and how it influences the questions they want to answer. School psychologists often describe social justice as both a process and a goal. If the goal of social justice in school psychology is to rebalance scales tipped in favor of those with power and privilege, utilizing the principles of QuantCrit in our research must become an important part of our process.

Recommendations

In this paper, we introduce the idea that incorporating qualitative and mixed methodologies is not the only means of achieving critical research. Indeed, many scholars in the field of school psychology position qualitative and mixed-methods approaches as an additive process to quantitative inquiry. While mixed-methods research is designed with the intention of incorporating aggregate quantitative analysis, qualitative methodologies arose and exist on their own. It would be misleading to suggest that qualitative methodologies somehow exist for the purpose of supporting quantitative research. While psychologists often use qualitative studies this way, they can, and arguably should be able to, exist on their own rich and inductive merit. Lastly, there are many instances wherein a strictly quantitative approach is ideal or necessary (e.g., secondary data analysis, statistical modeling). In these instances, QuantCrit stands as an excellent option for pursuing critical research.

Nevertheless, although QuantCrit can offer much in helping the field move towards a more justice-oriented lens, it is also important to recognize the limitations of this methodology. While a QuantCrit approach may reduce the harm created towards minoritized groups, it may not truly reach solutions that center and celebrate different types of knowledge. Using quantitative data alone has the potential to depersonalize the ways oppression is manifested and thus miss the nuance and complexity of systems (Grant et al., 2022) even when using a critical approach. An anti-oppressive framework toward research pushes us to move beyond aggregated data and into the lived stories of those who are minoritized.

This paper has unpacked how a color-evasive use of quantitative methodologies reifies and perpetuates ongoing oppression for marginalized communities. Using a QuantCrit framework encourages researchers to be aware of how our social locations impact the types of questions we ask, the statistics we use, and the interpretations that we make. It also emphasizes centering the voices of marginalized communities throughout the research process as opposed to simply having them be the research subjects. There is no one way to engage with QuantCrit, instead we can use the tenets as guidelines towards a more robust and intentional practice. The following table outlines ways to engage in a QuantCrit framework along with exemplar articles to guide future work (Table 1).

Table 1.

Recommendations and examples of QuantCrit practices.

Tenets	Typical Practice	QuantCrit approach	Example papers
Centrality of Racism	Relying on an ahistorical viewpoint. E.g., ignoring how enslavement, racism, and white supremacy continues to impact the lives of all children. Centering of middle-class, white European values as the norm.	Acknowledging how racism impacts all variables of interest. Socio-ecological contextualization of variables even when not the primary research question. Focusing on the community of interest independent of their relation to the majority group.	(Kulkarni & Sullivan, 2022). (Pérez Huber et al., 2018)
Numbers are not neutral	Large or kitchen sink statistical models that do not account for how independent variables are theoretically connected to each other and the outcome. For example, ignoring how socioeconomic status, academic outcomes and race are historically connected due to enslavement and racism. Pretending that an “all else equal” model that controls for a multitude of variables when examining the effects of a single factor like race represents reality, when it actually reflects an artificial environment devoid of any historical context or real world implications (Sullivan et al., 2020).	Highlighting the importance of descriptive data to inform policy. There is not always a need for complex statistical models to inform policy. E.g., odds ratios from child count data can be more informative about special education disproportionality than many regression models. Choosing your denominator or comparison group carefully. For example, when studying discipline disproportionality consider how hyper segregation in states/counties could impact suspension rates and bias estimates. Including interaction variables (e.g., race x gender) in statistical models when theoretically justified to represent intersectional identities.	(Campbell-Montalvo, 2020). (Wilson et al., 2017).
Categories are not natural	Treating race as a biological characteristic in statistical models - e.g., controlling for every variable that has historical associations with race due to enslavement and racism (e.g., SES, achievement, teacher ratings of behavior), and interpreting race as a within person characteristic independent of these.	Interpreting race as a social construct. i.e., interpreting racial disparities as resulting from racism, rather than only within child deficits caused by their racial identity. Disaggregating data of minoritized groups seen as a monolith - e.g., Asian Americans, Native Americans. Seeking insight from communities of interest to ensure appropriate categorization.	(Kulis et al., 2016). (Hall, 2018).
Data cannot speak for themselves	Uncritical conceptualization of research questions and interpretation of results. For example, ignoring the role of white supremacy in the history of policing and student resource officers. Using a deficit centered lens when discussing communities of interest. Being opaque about limitations of your dataset and generalizations. For example, making current policy recommendations based on datasets that are 20 years old, relying on parent recall of frequency of suspensions as the primary outcome measure when examining discipline disproportionality. Using large sample sizes to find significant effects, yet not reporting effect sizes.	Contextualizing results within socio-political history of the communities of interest. E.g., acknowledging the historical purpose of special education being to exclude children of disabilities from mainstream education, linking redlining to school segregation and academic outcomes/disparities. Always providing effect sizes and confidence intervals around main effects. Engaging in scientific journalism that provides an accessible version of your study to the public. Being transparent about the limitations of measures in the dataset. Avoiding causal interpretations of observational data.	(Cruz et al., 2021). (Capers, 2019).
Social Justice Orientation	The assumption that one's own identities do not impact what we choose to study and how we go about it. Deficit framed research questions and interpretation of results.	Positionality statements and a critical introspection of how one's identity impacts all aspects of the research process. Research questions that center systems and adults in power (e.g., schools, teachers) rather than within child deficits (behavior). Asset based research goals.	(Yu et al., 2021). (Stiefel et al., 2023).

Researchers must be intentional about understanding the broader sociocultural contexts in which their work is situated and seek to address the deficit narratives inherent in a globally racialized society. Similarly, as consumers of school psychology research, we should be critical of quantitative studies that lack any conversation about how structural inequalities impact the study's conceptualization of educational outcomes. Consumers can also look for research that is asset-based and provides counter narratives to traditional deficit-centered thinking. We propose using QuantCrit as a framework that can support both school psychology researchers and consumers in moving towards policies and practices that promote equity and change.

Footnotes

Author’s note

Marie L. Tanaka is currently affiliated with San Diego Center for Children in San Diego, CA, USA.

Declaration of conflicting interests

The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The authors received no financial support for the research, authorship, and/or publication of this article.

ORCID iD

Stephanie D’Costa

Notes

Author biographies

Stephanie D'Costa My identity as South Asian, cis-woman, immigrant influences the ways I engage and conceptualize research. I currently teach in the counseling department at St. Mary's College of California. I also practice school psychology at Oakland Unified School District. I am on a journey to address structural oppression and vision liberating futures.

Stephanie Grant I am a Louisiana Creole, African American, cis-gendered woman. My intersecting privileged and marginalized identities influence my work and my role in dismantling systems of oppression. I work as an Assistant Professor at Xavier University of Louisiana, a Historically Black College (HBCU) and identify as a school psychologist.

Tara Kulkarni In the spirit of self-reflexivity, I acknowledge that my identity and experiences as a cis-gender, brown, south Asian woman in academia have shaped my theoretical orientation towards research and practice as a school psychologist. I am currently an Assistant Professor at California State University- Monterey Bay.

Adrianna Crossing I am my ancestors’ wildest dreams. As a highly educated Black American, queer person, I move through life with a complex array of privileges and barriers, all of which influence my research and practice. I recently joined the faculty at Northeastern University, where I teach in the School Psychology and Public Health programs.

Miranda Zahn I am an educated white cisgender woman living in the rural Midwest. I teach in the School Psychology program at the University of South Dakota and practices in school mental health in the Wausa, Nebraska school district through Nebraska's Educational Service Unit #1.

Marie L. Tanaka I am a trespasser on stolen land. I am a cisgender, Japanese-Korean woman, and first American-born “citizen” in my family. I am not living with a physical disability. I seek to critically examine the systems that have allowed me to both benefit from unearned privileges and suffer from structural oppression.

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