(Re)building Our Understanding of Race Measures in Education

(Re)building Our Understanding of Race Measures in Education

Copyright: © 2023 |Pages: 23
DOI: 10.4018/978-1-6684-6898-2.ch006
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Abstract

Race categories were historically created as a tool for oppression, but in more recent decades, researchers have continued the tradition of using these categories as a tool of justice. However, research has shown that scholars consistently take for granted the meaning of the race categories that are so often used in research, going so far as to separate racism from race. This chapter explores the sordid creation of race categories, their evolving use over time, and the more modern conceptions of race group membership. The ways that QuantCrit and validity measures can help us better understand the race categories are also explored. Finally, the chapter concludes with recommendations for measures that might be used in addition to the race categories for researchers aiming to examine quantitative data split by race.
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Introduction

There is a long history of social exclusion in human societies (Peace, 2001). Oftentimes, marginalization, a state of being resulting from consistent social exclusion, occurs based on some identity group membership (Peace, 2001). When marginalization is systematized throughout a society, it becomes worthy of a new moniker, systemic marginalization. The phrase systemic marginalization was rarely mentioned in the literature before the 1990s, with a few dozen articles mentioning the term in the 1990s. By the 2010s, a few hundred articles mentioned the term, with some focusing solely on documenting the ways a particular identity group is systemically marginalized (such as Geronimo, 2010). Since 2010, this concept appeared in a few thousand articles.

The research on systemic marginalization provides critical insights to practitioners of diversity, equity, inclusion, and justice (DEIJ). Namely, this research shows how oppression happens systemically, disrupting the common misconception that oppression occurs in isolated, individual ways. Instead, these works bring to light evidence demonstrating how oppression in education is pervasive and reflective of the larger problems that permeate our society.

There is a longstanding trend of racial disparities in education. There are notable differences in the outcomes data for key measures from primary school through college, such as grades, engagement in science and math, enrollment at elite institutions, retention, and graduation. Racial disparities in higher education are also associated with later employment and earning disparities (Museus et al., 2015). Differences in outcomes split by race warrant a call for action to improve racial outcomes in higher education, but only when they are interpreted in a way that suggests there is a problem the people in power can solve. This brings us to recognize the importance in the ways people interpret racial statistics.

The ways in which educators interpret statistics is of critical importance, because leaders have the power to either make change or reinforce the status quo. Of course, change is only made when leaders perceive that a problem exists that can be solved. Deficit framing occurs when an interpretation of data puts the blame on marginalized people, and therefore denies systemic racism (Bonilla-Silva, 2018). Consider how the “achievement gap” is a common phrase for describing differences in student outcomes statistics by race group, and yet this phrase implies a deficit on the part of the student rather than the system (Ladson-Billings, 2006). Moreover, many people believe that the past is in the past, and that current societal systems no longer oppress members of certain racial groups (Bonilla-Silva, 2018). White people in particular have been found to minimalize racial disparities (Teranishi, et al., 2009). The ways in which white people view racial disparities is particularly problematic because education in many predominately white countries is dominated by whiteness. Consider how in the U.S., as of the 2015-16 school year, 80% of teachers were white, compared to 49% of students who were white (NCES, 2019a).

Given a history of colonialism and the domination of whiteness, it should be no surprise that there is a persistent socialization of whiteness which is characterized by unconscious social training discouraging the acknowledgement of race and racism (Frankenberg, 1997; McLaren et al., 2000). Scholars have long lamented the lack of progress in racial justice. For example, over the past sixty years in the U.S., since the civil rights movement, some scholars posit that momentum was lost as the focus shifted from racism and reparations to demographic compositions and one-off interventions such as diversity courses (Ladson-Billings & Tate, 1995). The majority of white people have little incentive to help, as members of the dominant group, and many white people have been shown to only intervene when it also benefits them (Delgado & Stefancic, 2017). However, one approach gaining in popularity and showing promise as a framework for helping all people use racial statistics to their fullest potential, while reducing the amount of deficit interpretations in the profession, is Quantitative Criticalism, or QuantCrit.

Key Terms in this Chapter

Racial Essentialism: The belief that race is a biological phenomenon in humans.

Face Validity: Experts judgment about a measure’s ability to capture the desired phenomenon.

Marginalization: A state of being resulting from consistent social exclusion.

Predictive Validity: A variable’s ability to predict a future outcome.

Construct Validity: The extent to which interpretations are an accurate reflection of the underlying meaning in the data.

Reflected Race: How others perceive an individual.

Race: A social construct based on a variety of definitions and contexts that groups people.

Theories: A research-based explanatory framework that provide a systematic description, explanation, or prediction of an observed phenomenon.

Criterion Validity: The relation of a measure to a gold standard measure.

Convergent Validity: Whether a measure correlates with other measures of similar phenomenon and also does not correlate with measures of unrelated phenomenon.

Concurrent Validity: A variable’s ability to predict a present outcome.

Attribute: A state of being based on experiences.

QuantCrit: A framework for interpreting racial statistics to their fullest potential that is aimed at reducing deficit framing.

Proxy Variable: A variable used in the place of another, when the direct measure of the phenomenon is unavailable.

Content validity: Whether the domain of a concept as measured represents the domain in reality.

Deficit Framing: Interpretations of data that centers the blame on marginalized people.

Systemic Marginalization: When marginalization is systematized throughout a society.

Critical Theories: Theories that aim to liberate and satisfy the needs of the people experiencing the phenomenon of interest.

Discriminant Validity: When a measure addresses a distinct concept.

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