RACE AND THE SOCIAL SCIENCES

In light of a series of recent incidences involving communities of color, especially the African American community, phrases such as “lives matter,” race matters,” “social justice” and the like accent the continued significance of race in the United States. Its significance affects everyday life experiences, social status, opportunity structures and outcomes, power and influence, health status and many other aspects of social and political life (Jones, LaVeist, and Lillie-Blanton Reference Jones, LaVeist and Lillie-Blanton1991; Omni and Winant Reference Omi and Winant1994; Williams Reference Williams1997). Social science scholars, having explored the social construction of race through both a macro perspective as well as through individual viewpoints and experiences, show how politics and power relations shape the racial order at all levels of society (Bonilla-Silva Reference Bonilla-Silva1999; James Reference James2001). In addition, political states can have interests in how the deployments of racial categories are accompanied by their associated hierarchies to serve the state's interests (Delgado and Harris Reference Delgado, Stefanic, Omni and Winant2013). In more authoritarian states, dominant groups tend to maintain and police racial boundaries through social closures and use of force. Concepts of outsiders and insiders, otherness, phenotypes, racism, discrimination, ideology are associated with the notion of race and the use of different categorical distinctions (Arrighi Reference Arrighi2007; Cerulo Reference Cerulo1997).

This paper represents a “meta- analysis” of social science empirically driven studies and examines how, in these studies, race is represented (i.e. conceptually, categorically, and dimensionally). This research also analyzes the characteristics of the principal investigator(s) (PI) and the period in which the studies were conducted. The central questions that will be explored are as follows: What is the manner in which race has been measured over time (1950–2012)? What has been the scope of race elements that extend beyond the categorization of specified racial groupings? That is, beside “what race are you,” were the other items that attempt to capture the meaning and context of racial status in a person's “everyday” life experiences? Do personal characteristics of the PIs (i.e. race/ethnicity, gender, discipline, etc.) affect the nature and scope of dealing with race? Has a broader set of race-related properties increased over time in which surveys have been conducted? To reiterate, the way race has been measured including (or as well as) the breadth or scope of race-related measures is the central foci of this “meta-analysis.”

EXPLORING “RACE” IN THE SOCIAL SCIENCES: AN INTRODUCTION

Much of the current social science literature dealing with race treats it as a social construction involving self-identification (allegiances and identities) and a perception of racial “belonging” by self and others. It also acknowledges that social structures and policies, which categorize racial groups with delineable “traits” (i.e. one drop rule, quantum blood, etc., Ford and Kelly Reference Ford and Kelly2005; Garcia Reference Garcia, Gomez and Lopez2013; Hirschman, Alba, and Farley Reference Hirschman, Alba and Farley2000; Snipp Reference Snipp2003; Williams, Lavizzo-Mourey, and Warren Reference Williams, Lavizzo-Mourey and Warren1994) does shape the meaning and use of race. For the most part, race has been viewed as an immutable, constant, and “steady state” of being so that one's social status, common experiences, social interactions patterns, etc. are strong predictors of a variety of outcomes (Laveist Reference LaVeist1994; Anderson Reference Anderson2006). These outcomes have included socio-economic status, income levels, attitudes (i.e. efficacy, trust, in-out group demarcations), health status and access, political representation, well-being and stress, incarceration and many other domains (Saperstein Reference Saperstein2012; Johnson Reference Johnson2011). At the same time, the categorization of racial groups is associated with social stratification, power, prejudice, discrimination, and inequities. In essence, the categorical variable of race (represented by specific racial groupings) and individuals’ placement of themselves into these categories incorporates a multitude of meanings, nuances, and relationships (Cobas, Duany, and Feagin Reference Cobas, Duany and Feagin2009; Hans and Martinez Reference Hans and Martinez1994; Krysan and Lewis Reference Krysan and Lewis2004).

An earlier work by Williams (Reference Williams1994) reviewed the concept of race in the journal Health Sciences Research. He examined ways in which race had been conceptualized and used in the health services research literature from 1966 to 1990. He limited the inclusion of articles to empirical research in which human populations were the focus. A major conclusion of this analysis was that “race is routinely used in health…Race needs more careful attention to its conceptualization and measurement…” (Williams Reference Williams1994, 268). He goes on to state that using race as an “afterthought” or in an automatic and atheoretical manner, or both, “avoids informing others how racial differences are built within societal institutions and can perpetuate the distortion of racial realities” (Williams Reference Williams1994, 268). As I had noted earlier, a “race variable” serves as an unrefined indicator of a variety of distinguishing groups’ histories and particular conditions of “everyday” life that bear on social status and opportunity structures. In any discussion of race as a concept, Williams’ examination of research design of empirical studies indicated a major overlap between race and socio-economic status. At times, these concepts are used interchangeably, yet they are not interchangeable and are not surrogates.

The scope and inclusivity of measures that capture the fuller impact and meaning of race have been relatively absent in most social science empirical research (López and Gomez Reference López and Gomez2013). Our discussion will begin with the conceptualization of race by introducing the following eight components: first, race is a social construct based on social and political context rather than any essential biological difference between groups (Garcia Reference Garcia, Gomez and Lopez2013; Sanchez and Ybarra Reference Sanchez, Ybarra, Gomez and Lopez2013); second, individuals have considerable agency in placing themselves within racial categories (for example, racial identity); third, racial self-identification is a cognitive dimension of one's self-concept and is a developmental process fourth, the individual does not “choose” racial identity or group membership in isolation and, in fact, is heavily influenced by a host of externalities (Vargas et al. Reference Vargas, Winston, Garcia and Sanchez2016) including social interactions, historical context and patterns, legal status and constraints, and other factors (Bruch and Loveman Reference Bruch and Loveman2011; Jones et al. Reference Jones, Truman, Elam-Evans, Jones, Jones, Jiles, Rumisha and Perry2008; Owens, Robinson, and Smith-Lovin Reference Owens, Robinson and Smith-Lovin2010); fifth, race is dynamic, meaning that the understanding and/or expression of one's race can change over time (Saperstein Reference Saperstein2012; Saperstein and Penner Reference Saperstein and Penner2012); sixth, race is an element of multiple social identities in which the “constellation” of self includes race among other salient social identities (Bratter and Gorman Reference Bratter and Gorman2011; Harris and Sim Reference Harris and Sim2002; Woo et al. Reference Woo, Austin, Williams and Bennett2011; Frank, Redstone, and Lu Reference Frank, Akresh and Lu2010); seventh, physical features (phenotypical characteristics) (Telles and Murguia Reference Telles and Murguia1990). serve as a basis for racial classification, both by the individual and particularly in terms of how others identify her or him (Hochschild Reference Hochschild2011) and finally; that there is a “separate but related” notion of race and ethnicity (Garcia Reference Garcia2009; Saperstein Reference Saperstein, Gomez and Lopez2013; Saperstein and Penner Reference Saperstein2012), which can serve as inter-sectional concepts or perhaps inter-changeable concepts (Garcia Reference Garcia, Gomez and Lopez2013).

Williams concluded that while health researchers have been paying more attention to the conceptualization and measurement of race (Cooper and David Reference Cooper and David1986; Jones, LaVeist, and Lillie-Blanton Reference Jones, LaVeist and Lillie-Blanton1991; Krieger, Sidney, and Coakley Reference Krieger, Sidney and Coakley1998; Miller Reference Miller1987; Osborne and Feit Reference Osborne and Feit1992; Wilkinson and King Reference Wilkinson and King1987; Williams, Lavizzo-Mourey, and Warren Reference Williams, Lavizzo-Mourey and Warren1994), there is still ambiguity in its definition and conceptual clarity. A growing body of literature suggests that both the concept of race and operationalization of this concept are problematic in contemporary health research. In other social science disciplines, race is primarily represented as a categorical variable and controls for other complementary variables (i.e. class, national origin, gender, income, etc.). However, this type of analysis tends to isolate the effects of race with covariates (Sanchez and Ybarra Reference Sanchez, Ybarra, Gomez and Lopez2013; Saperstein, Penner, and Light Reference Saperstein, Penner and Light2013). The goal of this discussion is to generate dialogue concerning the complexities involving race and the need to broaden measures and indicators. This “race project” chronicles the development of race as a variable in many social science surveys since the 1950s.

RACE: A DISCUSSION ABOUT BEING MULTIFACETED AND COMPLEX

One direct consequence in understanding a more complete conceptualization of race that an individual selects her/his racial group, therefore making self-identification the “gold standard” for racial classification. Based upon the concepts of self- and social identity (Cerulo Reference Cerulo1997; Owens, Robinson, and Smith-Lovin Reference Owens, Robinson and Smith-Lovin2010), individuals “place themselves” within established racial categories based on criteria the individual chooses. Self-identification is “determined” by a varied range of factors. For example, there is cognitive research conducted by the Census Bureau in which follow-up interviews were performed after a person had filled out the census short form (de la Puente and McKay Reference de la Puente and McKay1995). Individuals were asked why they selected a specific racial category on the form and often their answers reflected notions of physical features and/or colorism, ancestry, societal cues, public policies, and other external cues. Due to the reliance on preset categories, the underlying meaning or interpretation of an individual's racial identification is difficult to know, yet the end result is a count of how many persons fall within a certain pre-determined racial category.

Latinos have complicated this classification process more than other groups because a substantial portion of this community does not place itself into the current racial categories established by the Office of Management and Budget Directive 15 (OMB 1997). The revised standard has five categories for data on race: American Indian or Alaska Native, Asian, Black or African American, Native Hawaiian or Other Pacific Islander, and White. There are two categories for data on ethnicity: “Hispanic or Latino” and “Not Hispanic or Latino.” Almost two-fifths (36.7%) of Latinos marked the “some other race” option in the 2010 decennial census (Humes et al. Reference Humes, Jones and Ramirez2011, 6). Interpretations cover the gamut of explanations from respondents’ “confusion as to the meaning and use of race in the United States” to a desire to categorize themselves as a distinctive race in this country. This pattern reinforces the intersection of race and ethnicity and ways to differentiate these concepts by both researchers and the general public (López Reference López2017; Espiritu Reference Espiritu1992).

The contextual and situational nature of race can generate a response as to one's identity based upon homeland experiences (Garcia Reference Garcia2003). That is, if the race question were to be asked outside the United States, the understanding and descriptions of racial options would be different and would apply across geopolitical borders. Many social science surveys separate race and ethnicity into two distinctive concepts, while others combine race and ethnicity as configuring social groups and/or racialized groups.

The 1995 Current Population Survey conducted a race and ethnicity supplement section to explore interpretations of race, ethnicity, and national origin (Browne and Odem Reference Browne and Odem2012; Flores and Telles Reference Flores and Telles2012; Massey and Denton Reference Massey and Denton1989; Tucker and Kojetin Reference Tucker and Kojetin1996). There was significant confusion among the respondents as to whether race and ethnicity were different or interchangeable (McKay et al. Reference McKay, Stinson, de la Puente and Kojetin1996). Among some foreign-born interviewees, comments about the race question suggested their response would have been different had they been answering the question in the home country rather than as a resident of the United States. For example, a Peruvian-born individual indicated that his answers would be different if he was still living in Peru as opposed to having lived in the United States for over 10 years (Bates et al. Reference Bates, Acevedo-Garcia, Alegría and Krieger2008). This introductory discussion about the conceptualization and measurement of race serves as a critical context from which to explore social science survey research and its developments over time.

RACE, SOCIAL STRUCTURES, AND POLICIES

In our discussion of the complexities and multi-dimensionality of race, the development of critical race theories (CRT) (Delgado and Harris Reference Delgado, Stefanic, Omni and Winant2013) contributes to the themes of this paper. Generally, CRT correlates race, racism, and power as inter-related concepts and practices. This larger perspective takes into account economics, historical accounts, context, group status and membership, self- interests, feelings and attachments, and unconscious biases and attitudes. The expansion of conceptual development had its origins in legal studies, but has permeated the fields of education, politics, ethnic studies, and radical feminism. This strand also extends our notions about race beyond the individual and inter-personal experiences.

There are basic tenets of CRT that include the following: (a) racism is an ordinary, everyday experience; (b) among persons of color there are psychological purposes and material effects, which produce less incentive to eliminate the privileged advantages for non-persons of color; and (c) the development of the products of “social construction” of social thought and relations that are invented to manipulate and marginalizes persons of color. CRT incorporates an institutional legacy, and multiple levels of societal arrangements by which race is defined and experienced. In this manner, conceptualization and measurement of race is not confined to an individual's “isolated” sense of self. This perspective moves away from a focus on individual agency and achievement with minimal attention to social structures and biases.

A definition developed by the Lawrence et al. (Reference Lawrence, Sutton, Kubisch and Fulbright-Anderson2004) defines structural racism as “a system in which public policies, institutional practices, cultural representations, and other norms work in various, often reinforce ways to perpetuate racial group inequity. It identifies dimensions of our history and culture that has allowed privileges associated with ‘whiteness’ and disadvantages associated with ‘color’ to endure and adapt over time.” White privilege has given “included groups” the access to advantages that excluded groups have not had (Simms and Waxman Reference Simms and Waxman2016).

In this wider context, the concept of structural racism and white privilege are inter-twined. That is, white Americans have acknowledged that persons of color have race-related disadvantages and take the form of “additional baggage” that accompanies them over the course of their lives. At the same time, there is a reluctance to grant “male and white privilege” (McIntosh Reference McIntosh1988), but a greater recognition that “structural racism” can and has played a part of racial inequalities and lived experiences. White privilege has given “included groups” the access to advantages that excluded groups have not had (Simms and Waxman Reference Simms and Waxman2016).

A challenge for researchers (among others) is that once these structures are in place, actively thinking about race, privilege, or discrimination are connected to these privilege systems in which disadvantage people of color usually is not part of the measurement and analytical frames. For example, historical discriminatory processes regarding housing segregation downgraded people of color to communities with less desirable housing, lower housing appreciation, lower wealth accumulation, low savings, and access only to poorly resourced schools, which limits their status and opportunity for mobility (Simms and Waxman Reference Simms and Waxman2016). The consequences of housing segregation can lead to lesser access to higher education and postsecondary training for persons of color and hindering competition for better job opportunities. As a result, these structural disadvantages also hamper future generations from moving up the economic ladder. But many research approaches focus upon the individual experiences of persons of color and do not integrate concrete measures of social structures and practices into a multi-level analysis.

Some studies have sought to create a direct measurement of racial subordination in terms of power relations or institutional racism. The desire is to find a way to tap into this dimension, representing the underlying basis for the existence of racial categories that stems from power, control, status, access, and inequality. Structural racism represents a macro-level system, social forces, and institutions, ideologies, and processes that interact with one another to generate and reinforce inequities among racial/ethnic groups (Williams Reference Williams1999; Williams and Mohammed Reference Williams and Mohammed2013; Paradies Reference Paradies2006). Studies such as Gee and Ford (Reference Gee and Ford2011) and Harrell et al. (Reference Harrell, Burford, Cage, Nelson, Shearon, Thompson and Green2011) identify four forms of racism: structural (i.e., poverty, and underemployment); cultural (i.e., devaluing non-dominant cultures); institutional (i.e., institutions of mobility like schools, labor markets), and individual (i.e., discrimination and prejudice). The work of Gee and Ford (Reference Gee and Ford2011) isolates three domains from which structural racism operates. They include social segregation (primarily residential segregation) and its outcomes (i.e., quality of schools, access to labor markets); immigration policy (i.e., bases for admission, criteria for citizenship, selected punitive/restrictive policies); and “intergenerational drag” (i.e., the persistence over time of limited or downward intergenerational mobility). Analytically, the inclusion of structural racism strongly suggests the use of multilevel modeling to incorporate the different individually relevant factors as well as structural/contextual components.

RACIAL DISCRIMINATION

I have characterized the conceptualization and measurement of race as primarily a categorical variable, a set classification scheme, and primarily static in nature with racial categories stemming from an individual's own sense of self and placement within group categories. This discussion of multifacetedness includes additional dimensions of race that should be part of the race concept and provide more effective and accurate measures. Race has to do with differential treatment, unequal status, and differential power relations.

For example, health disparities research treats race as a complex and multidimensional construct that includes institutional and internalized racism and examines how these dimensions affect health outcomes and usage. Obviously, race impacts other important sociopolitical phenomena (CQ Researcher 2014; Ford and Kelly Reference Ford and Kelly2005; Lin and Kelsey Reference Lin and Kelsey2000; McClain and Stewart Reference McClain and Stewart2013); therefore one cannot talk about race without talking about discrimination and racism (Bonilla-Silva and Biaoccho Reference Bonilla-Silva, Biaoccho, Zuberi and Bonilla-Silva2008; King and Williams Reference King, Williams, Amick, Levine and Walsh1995; Viruell-Fuentes Reference Viruell-Fuentes2011). In the field of political science, a variety of measures have linked racial identity to experiences of discrimination and racism. These include the concepts of group affiliation, affinity, and “linked fate” that political scientists (Dawson Reference Dawson1995; Masuoka Reference Masuoka2006; Sanchez Reference Sanchez2006) believe serve to heighten racial group membership and affect life chances, health outcomes, and political behaviors (Braveman Reference Braveman2012; Camara et al. Reference Camara, Burford, Cage, Nelson, Shearon, Thompson and Green2011; Chae et al. Reference Chae, Nuru-Jeter, Lincoln and Francis2011; Fiscella et al. Reference Fiscella, Franks, Doescher and Saver2002).

Experiences with discriminatory behaviors and attitudes as well as perceived discrimination toward one's racial group have been shown to vary significantly with “White” versus non-White racial status (Ahmed, Mohammed, and Williams Reference Ahmed, Mohammed and Williams2007; Kinder and Sanders Reference Kinder and Sanders1996; Williams et al. Reference Williams, Mohammed, Leavell and Collins2010). Questions that measure racial/ethnic discrimination have been either a “one- or two-stage” protocol (Shariff-Marco et al. Reference Shariff-Marco, Breen, Landrine, Reeve, Krieger, Gee, Williams, Mays, Ponce and Alegría2011). The one-stage discrimination item places race and ethnicity as the basis for experiencing unfair treatment or discrimination. The two-stage discrimination items asks about any experiences with discrimination and then follows up as to the respondent's understanding about the bases of such behavior. If race/ethnicity is seen as the primary factor, this serves as evidence of racial discrimination.

The structure of these discrimination questions can affect the level of reporting of discrimination and indication of multiple acts of discrimination. These measures serve to differentiate between the types of behaviors and attitudes more common to a specific racial group. For example, Latinos might be more prone to cite discriminatory behaviors/attitudes regarding having an accent and not being viewed as smart as others while African Americans might cite experiencing poor treatment in public spaces and experiencing reactions of fear on the part of others (Shariff-Marco et al. Reference Shariff-Marco, Breen, Landrine, Reeve, Krieger, Gee, Williams, Mays, Ponce and Alegría2011). There remains a number of measurement issues about items capturing discrimination such as wording use, language of the interview (Ahmed et al. Reference Ahmed, Mohammed and Williams2007; Lee and Pérez Reference Lee and Pérez2014), and the reliability of items across different racial and ethnic groups. Another important element regarding discrimination is the distinction between perceived versus actual experience. Some research indicates that the linkage between these two aspects is modest and each produces independent effects as to attitudes, behaviors, and health status (Borrell et al. Reference Borrell, Kiefe, Williams, Diez-Roux and Gordon-Larsen2006; Williams Reference Williams1999).

SKIN COLOR/PHENOTYPES

Social scientists have found that phenotype, skin color in this discussion, is part of the racial formation of a groups’ status and some (Hochschild and Weaver Reference Hochschild and Weaver2007; Prewitt Reference Prewitt2005) have proposed skin color as a “better” surrogate to capture how race is viewed in American society. As a result, capturing race involves the concept of colorism and the effects of skin color on social status, opportunity structures, and inequality. For example, many social outcomes for African Americans, especially those who are darker skinned African Americans, on average, make less money (Bowman, Muhammad, and Ifatunji Reference Bowman, Muhammad, Ifatunji and Herring2004; Hersch Reference Hersch2006; Keith and Herring, Reference Keith and Herring1991), living in more highly segregated areas (Massey et al. Reference Massey and Martin2003), and even having a more difficult time garnering votes when running for office than African Americans with lighter skin color (Terkildsen Reference Terkildsen and Damore1999). In short, skin color serves to pattern significant marginalization among African Americans (Allen, Telles and Hunter Reference Allen, Telles and Hunter2000; and Hunter Reference Hunter1998).

In the case of Latinos, skin color also has effects on social outcomes. For example, Murguía and Telles (Reference Murguía and Telles1996) find that darker skinned Mexican Americans receive lower earnings than their lighter skinned co-ethnics. Similarly, Morales (Reference Morales2008) finds that skin color can lead to Latinos being segmented within labor markets, with darker skin Latinos being stratified into lower-waged sectors of the labor market. Examining the impact of skin color on occupational prestige, Espino and Franz (Reference Espino and Franz2002) found that skin color magnified lower prestige for Latinos of Mexican and Cuban origin, but not for Puerto Ricans (McGovern Reference McGovern2017). Specific to political equality, Tafoya (Reference Tafoya2004) found that a U.S.-born Latino's “whiteness” was clearly and consistently associated with higher social status, higher levels of civic participation, and a stronger sense of social acceptance. Finally, scholars have compared the impact of phenotype across different countries (Montalvo and Codina Reference Montalvo and Codina2001; Perreira and Telles Reference Perreira and Telles2014; Telles, Flores, and Urrea-Giraldo Reference Telles, Flores and Urrea-Giraldo2015; Uhlmann et al. Reference Uhlmann, Dasgupta, Elgueta, Greenwald and Swanson2002) and found greater degrees of social and economic inequality for darker skinned individuals.

The inclusion of skin color as an indicator of race produces measurement challenges with differing approaches. Most commonly, the respondent is placed in a skin tone category (ranging from lighter to darker skin ratings) based on her/his self-report or the report of an external observer. The respondents’ basis for such self-assignment (as well as confirmed by a third party) is usually based on the individual's experiences, self-concept, social identity/ies, social networks, and other external influences. The skin color measure is usually self-reported on a five-point scale continuum from very light to very dark. Social meaning and value in U.S. society places a more positive value on being lighter skinned so scores on seldom are distributed over the full range of the scale (Garcia Reference Garcia1991a; Reference Garcia1991b; Hutchings, Jefferson, and Yadan Reference Hutchings, Jefferson and Yadan2015).

To measure skin color as a race indicator, another approach has been for the interviewer to assign the respondent's placement on the skin color scale. This resulted in “race-of-interviewer effect” in which interviewers perceive greater variations in the skin tones of same race respondents than among different race respondents (i.e., Black interviewers categorizing White respondents as lighter than their White interviewer counterparts and vice versa; Hill Reference Hill2002). More recently, Chan et al. (Reference Chan, Ehrlich, Lawrence, Moshell, Turner and Kimball2005) have included both self-reported skin “phenotype” as well as readings from a narrow band reflectance spectrometer. The primary purpose of this approach was to make “precise” measures of skin color to be used in the evaluation of patients and expand the clinical information collected (Chan et al. Reference Chan, Ehrlich, Lawrence, Moshell, Turner and Kimball2005). At the same time, the accuracy and precision of a reflectance spectrometer fails to capture the social meaning, status, and context from which skin color and race as a social construction are interconnected.

Social science scholars such as Gravlee, Dressler, and Bernard (Reference Gravlee, Dressler and Bernard2005) find that ascribed skin color (rather than self-placed skin tone rating) is more important in predicting health outcomes than the more “objective” clinical measure of reflectometer-determined skin color. These findings have potential implications for skin color measurement and begin to move towards the more structural/societal aspects of racism that Dressler et al. (Reference Dressler, Oths and Gravlee2005) and others (Gee and Ford Reference Gee and Ford2011; Williams and Mohammed Reference Williams and Mohammed2009) note as having greater impact on health outcomes. Capturing “measures of skin color” represents some serious challenges for survey researchers as to how to implement measures/items to fit into a survey format. This discussion of skin color focuses on the social construction of race; not only how the individual self-identifies racially, but how others do the same. Thus, the source of information about one's skin color is an important element measuring skin color.

RACIALIZATION

Our discussion of race and its multi-dimensional layers has seen greater inclusion of the concept of “racialization.” One of the conceptual and measurement challenges is differentiating this concept as a process versus end stage or category. That is, what constitutes racialization (i.e. on what bases, what are societal and political processes, group status, etc.) and the categorization of a group as racialized? We can use the following as a working definition of racialization: the process of the creation of a new racial category in which considerations of class, phenotype, religion, legal status, nativity, and “otherness” in a hierarchical racial and social order are the operating characteristics (Vidal-Ortiz Reference Vidal-Ortiz2004; Grosofoguel Reference Grosofoguel2004). In a U.S. context, Omi and Winant (Reference Omi and Winant1994, 64) see racialization as an extension of racial meaning to a previously unclassified relationship, social practice or group. This reflects a process of racial formation such as the Latin Americanization as part of the American racial categories (Bonilla-Silva Reference Bonilla-Silva2004). In addition, discussion of racialization suggests that racial meaning is given to numerous forms of differences that could include ideology, cultural traits, religion, without the need to rely exclusively on phenotypical differences (Miles Reference Miles1993). Finally, racialization represents a process of creating new racial categories. In doing so, there is a real need to understand how groups are “rejected” from whiteness and how race and racism changes a dependency on social and racial context (Selod and Embrick Reference Selod and Embrick2013).

While the exploration of racialization focuses upon a process by which groups (based upon a variety of aggregations) are “created” into new categories the general notion of race is the primary reference; racial categories represent racial hierarchies (Bashi Reference Bashi1999). That is, racial ideologies and the racialization process is instructed by status and power differentials and functions as an expediter and a byproduct of the intersection of race and class stratification (Cole Reference Cole1999). Thus the inclusion of racialization as part of the multi-dimensional “view” of race reinforces the complex relationship of categories, categorization processes, institutional structures and practices along with the individually based sense of who they are and the social context in which they experience their daily lives.

RACE AS DYNAMIC

As I mentioned early in this paper, an important dimension of race involves the dynamic nature of racial identification (Saperstein Reference Saperstein2006; Saperstein and Penner Reference Saperstein and Penner2012), its development, and multi-racial identity (Bratter and Gorman Reference Bratter and Gorman2011; Masuoka Reference Masuoka2008). In the case of the former, longitudinal studies (Saperstein and Penner Reference Saperstein and Penner2012) have noted that respondents have changed their racial identification over time. Some associated factors have to do with a change in status or situation (i.e. going on welfare, incarceration, unemployment, inter-marriage, etc.). There is a racialization process in which ascribing stereotypes and characteristics to groups outside of the extant racial categories (i.e. immigrants, religious groups, etc.) are associated with race and racial inequality resulting in individuals constantly creating and renegotiating their everyday interactions. Saperstein, Penner, and Light (Reference Saperstein, Penner and Light2013) propose that an individual's race is best conceptualized as a set of propensities rather than a single mutually exclusive category and that these propensities change over time and across contexts.

An overall thread in discussing additional dimensions to capture race is the understanding of race as fluid, complex, and inter-related with other concomitant attributes and socio-demographic “traits” (i.e. class, language, nativity, etc.) and cultural qualities. Netting the breadth and scope of race presents serious challenges for researchers in terms of conceptualization and measurement, but it also provides added opportunities to understand an important range of socio-political and economic conditions and outcomes.

The discussion of how race is conceptualized points to the necessity of providing breadth to the concept of race and its measures. The extent that race goes beyond categorical groupings enables researchers to treat and measure the fuller meaning and consequences of race. Relying on a limited scope of race, primarily in categorical terms, serves as a “research-based forum” to assess and extend the theoretical and empirical development of this significant concept and its realistic “lived experiences.”

This discussion speaks to the need to expand the scope of what we mean by race, how we understand, and how we measure race in order to encompass its fullness in everyday experiences and consequences. It is this broader discussion regarding race within the social sciences that marks the crux of what I refer to as “the race project.” This project represents an unusual attempt to chronicle and systematically analyze the scope, content and producers of empirical social science efforts. The examination of social science studies that have included race as a variable enables me to view how race has been used, who have designed these studies, and any trends over time of broadening the measures of race.

The next section outlines the protocols used in establishing the Race Project database, coding schemes, augmenting information from the ICPSR meta-data pages, and the variables created. Again, the scope of this effort lies with an inspection of the race-related variables in each study, characteristics of the PIs, and contributing factors affecting the scope of race-related items in each of the studies.

RACE PROJECT PROTOCOLS AND RACE-RELATED TERMS

The crux of this analysis deals with the inclusion of race used in studies in the ICPSR study collection. ICPSR is the world's largest social science data archive and celebrated its 50th anniversary in 2012; it continues to expand its data collection in a wide range of the social and behavioral sciences, both domestically and internationally. ICPSR maintains a data archive of more than 500,000 files of research in the social sciences. It hosts 16 specialized collections of data in education, aging, criminal justice, substance abuse, terrorism, and other fields. One should note the distinction between files, series, and studies. The former refers to each data file (i.e. adult survey, child survey, cohort one, etc.) while series refers to reoccurring surveys (i.e. American National Election Surveys, PSID, Health and Retirement Survey, etc.). Finally, studies refer to a specific study with a primary content focus (i.e. Juvenile Recidivism; New York Health Interview Study; etc.). Over time, ICPSR has developed research-related tools so that researchers can search its collections from a variety of filters. This project utilized a search variable engine that identified studies, which include “keyword” variables.

For this project, the key criteria for the selection of specific studies were the use of “race” as the keyword. A compiled list of studies that were identified was generated (see Appendix). The original list was reviewed to remove studies in series for which the survey instrument was the same across administrations. As the researcher, I worked with four University of New Mexico doctoral students to serve as coders for the identified studies. A small grants award from the University of Michigan enabled me to fund their time on inputting the study- related information. Consulting other ICPSR IT personnel, the variable search function that had been implemented only covered about 60% of the total collection. A year later, working with Michigan's Undergraduate Research Opportunity Program, an undergraduate was approved to add additional studies to the variable search engine. As a result, a total of 255 studies represent the Race Project (See Appendix).

Our earlier discussion of race and the social sciences centers on the conceptualization of race, its measures and use by social science researchers. In order to analytically explore the “treatment” and measurement of race, the coding schema attempted to “capture” critical information about the funder, PIs, race-related items and the intersection of these major components. Since the criteria for inclusion of the selected studies was the inclusion of a race variable, this study was interested in the range of race-related items that could be found in addition to the “traditional race variable.”

The search protocol included the following search terms: discrimination, racism, racialization, skin tone, skin color, racial, and ethnicity. If the study included any of these additional race-related terms, the coders would then create a string of information such as question wording, type of response categories, number of response categories, and source of the information (i.e. respondent or interviewer). The range of race-related items went from a single item to as many as 38. In the case of the latter the questions were asked of both the respondents and others with a series of follow-ups. For example, if the question dealt with a discriminatory experience, there could be follow-ups regarding occurrence of incidence, context of incidence, racial/ethnic characteristics of the “perpetrator, etc.”

Additional data that was collected about the selected studies included the PIs, year of the selected study, period the study covered, and funding organizations. With each identified study, the ICPSR study number provided important information based from the “meta- study page.” Explicit inputted variables included the name of the study, year(s) covered, names of the PIs, funders, scope of the study, cross-sectional or longitudinal study, and other information about the survey design, sample characteristics, and related literature publications.

Our coding effort was expanded by adding additional information about the PIs. This included the following: gender, race/ethnicity, discipline, and year of Ph.D. The expansive range of the web enabled our team to find this kind of information. Each coder was assigned a grouping of studies to include all of these elements of the race project. Faculty researchers served as the quality control reviewers and protocols were established so that ambiguities as to the appropriateness and veracity of the information were checked by at least two other coders. An Excel database was formatted to record all of the collected information. Subsequently, the excel spreadsheet was imported into SPSS data file as both string and numeric variables. The existence of multiple categories (i.e. up to 18 Principal Investigators, incidence of up to 38 search terms, up to 14 funders per project) resulted in a very wide file and the study was the primary organizing structure.

Initially, the database was formatted as an excel spreadsheet so that information about each selected study was submitted “horizontally” and multiple race-related items, multiple numbers of PIs, multiple funders, and associated characteristics of PIs were recorded on additional lines. The conversion of the excel database into a SPSS file resulted in the creation of several numeric variables for many of the string variables. The initial file structure created several challenges, which were eventually overcome in order to conduct the resultant bivariate analysis.

RACE PROJECT PROFILES AND CONTENTS

As a result of filtering the ICPSR collection via its variable search engine, a total of 257 studies (as mentioned earlier) were included in the race project. Of the studies that are series (i.e. conducted periodically over time using the same core module(s), a represented administration was selected for inclusion. At the time of the initial “pass” of the ICPSR collection, the variable search engine only covered about three-fifths of the entire collection. In the fall and winter of 2013–2014, an additional “pass” was conducted to add the other studies now linked to the variable search engine.

The description of the key variables in the database represents the major foci of this analysis. The first observation is the expansion of race-related terms/concepts in social science surveys since the 1950s. For example, in the 1950s, the typical racial category would have been “white” and “other.” In subsequent decades, “Black” and various other labels became more the standard as other racial categories were added. It should be emphasized that the primary scope of this race project deals with the greater of inclusion of race-related items beyond a categorical racial variable.

The next dimension dealt with the researchers, their background, discipline training, and period in which their studies were conducted. The inclusion of race-related questions, especially multiple ones, would be influenced by the researchers’ conceptualization of race. In this case, when they were trained (year of Ph.D.), their discipline, and such background characteristics as gender and race/ethnicity could affect how their research orientation is reflected by these experiences and characteristics. As a result, my analysis will examine the coded studies along these dimensions in relation to the number(s) of race-related items in the studies.

In Table 1, I present some basic “profile” information about the race project studies. Chronologically, the more contemporary period of 2000 and beyond represents almost two-fifths of the database. The 1960s (14.0%) and 1990s (22.4%) constitute the other two decade periods with the most studies including race as a variable.

The included social science studies ranged from those that covered a gamut of topics to those more specialized with specific targeted content areas. A review of the study description enabled me to categorize the central focus of the studies. It should be noted that in addition to ICPSR's general archive (which covers a diverse range of social science studies); its collection also includes several topical archives (which are more content specific). As a result, the frequencies in some of the content areas are driven, in part, by the topical archive's sponsor and their requirements for data deposit. The area of criminal justice (i.e. incarceration, sentencing, juveniles, recidivism, etc.) has the greatest number of studies (20.4%) followed by public opinion and politically oriented surveys (15.3%). In the latter, organizations such as television networks, major newspapers, and the American National Election surveys are major drivers for this category.

Sociological studies (i.e. lifestyles, values, etc.), and health content surveys (i.e. health status, conditions, access, utilization, etc.) were the second largest category of studies. The rise of health-related studies are more marked since the 1990s. Interestingly, studies that focused primarily on race and ethnicity constituted the fourth highest number of identified studies (11.8%). Experientially, the scope of studies that would expectantly fall under the social science “umbrella” is well represented, with the possible exception of economics.

The ICPSR meta-data page includes who were the funders of the study, and how many funders supported each study, so that the next additional information in Table 1 reflects that information. For the most part, each of the funded studies was supported by one or two funding sources (combined 60.8%). If one was to examine the changes in the number of multiple funders per project, especially among foundation-based organizations, the economic cycles of the nation's economy might be an important consideration. In time of economic downturn, foundation portfolios can be less robust. It should be noted that among the identified studies, a significant portion were funded and investigated by federal agencies and the study was conducted by their own research personnel. Consideration of this aspect of the selected studies affected my characterization of the PIs. That is, the agency conducting the studies did not identify specific PIs. In any event, the nature of funded research lends itself to additional discussions about funding strategies, funders’ research priorities and investigators’ research focus.

While support for social science research is vital, it is the PIs who design, conduct and analyze the socio-political and economic phenomena. Table 2 provides some background information about the PIs that could affect the use and measurement of race variables in their studies. Of the 255 studies in this database, slightly less than one-half of them were conducted by governmental agencies or public interest organizations, which had no specific PI(s) identified. Of the remaining studies, a total number of 313 researchers were involved. Representation by discipline indicated that sociologists constituted more than one-third (36.2%), followed by psychologists (22.8%), and then political scientists (17.3%). The mean number of PIs per study was 3.4. An examination of the racial and ethnic background of the PIs, as well as the other background information, was retrieved by exploring other sources. The vast majority of the PIs, 283, were white representing 82% of all PIs. Latinos (8.4%) and African Americans (6.1%) constituted the largest racial/ethnic groups of the remaining PIs. Note that it was uncommon to find the clusters of racial/ethnic PIs as part of the same project and whose focus was on a minority-related community and topics. The gender distribution of PIs is nearly a two-to-one ratio with males representing 64.7% of all PIs. Some additional information about the PIs and funding sources is presented in Table 3.

While information regarding the PI's disciplinary training can provide some important context by which the manner of race is examined, the period a PI received his or her training can shape their theoretical and analytical orientations to research questions and topics, which include race as a variable. With the context and analysis focusing on race as a variable, there is an established body of literature that notes the development of the conceptualization and treatment of race since the 1960s. We were able to locate not only PI's disciplines, but also their year of their Ph.D. degree. The modal decade was 1970–1979 as 29.1% of the Ph.D.s were awarded during this period, followed by the period of 1980–1989 (24.9%). As a matter of fact, over three-fourths of the PIs received their degrees since 1970.

In Table 3, the type of funders supporting each of the selected studies is presented. The most frequent funder was the Department of Justice (n = 116), followed by private foundations (n = 96). Many funding organizations initiate specific “request for proposals” on particular research areas. It is difficult to recreate that element, but clearly governmental agencies have been a major source of funding of social science research.

Finally, the last descriptive table (Table 4) focuses on the actual type of race-related terms found in each of the studies. Our earlier discussion about the structure and protocols to conduct this race project require each selected study to have a race variable. At the same time, the development of social science research that includes race as a variable has grown to view race as multi-dimensional, dynamic, and relational. In the case of the latter, one's racial/ethnic identity is not solely the function of individual choice, but geographical location, others’ perceptions and stereotypes, and social situations that influence racial identity.

Generally speaking, the “race” question, in these surveys, is phrased “what is your race” or “how would you describe your race”? What has changed over the time period of these studies is the range of categories used. That is, surveys in the 1950s would generally have included only the options of “white” and “other.” The 1970s and beyond began to include “white”, variant labels of African Americans (i.e. Negro, black, Afro-American, etc.) (Hirschman, Alba, and Farley Reference Hirschman, Alba and Farley2000; Snipp Reference Snipp2003). The 80s introduced racial categories beyond the Black/white paradigm with the inclusion of “some other race” and later, designations of Asian and Native Americans, and finally Latinos/Hispanics. The Office of Management and Budget Directive 15 established the predominant racial categories used for all governmental surveys and information gathering on race and ethnicity.

While the inclusion of a race variable in each study was a prerequisite for inclusion into this study, our exploration of race did not end there. We noted other “race-related terms” to include additional variable searches. They included ethnicity, racialization, racism, discrimination (perceived and actual), skin tone or color, and some other race. Table 4 shows the frequency of other race-related terms. Ethnicity is the most frequent term, followed by racialization/racism. In many cases, the race question is combined with ethnicity providing the option of answering what is your race/ethnicity OR your race or ethnicity. Williams (Reference Williams1994) had noted earlier that race and ethnicity were used interchangeably in the articles he analyzed in Health Services Journal. The racialization/racism questions were asked largely in terms of perceived differences by race and its impacts on life chances or the extent of racism in American society. The well-establish concept of linked fate (Dawson Reference Dawson1995) is associated with these concepts of racialization and racism. Williams and Mohammed (Reference Williams and Mohammed2009) also introduced the concept of internal racism, which involves the internalization of racial inferiority by individuals of the racially marginalized group.

The other frequently used race-related term is racially based discrimination. In most instances, the discrimination question will ask the respondent if he/she has experienced discriminatory behaviors in general or in specific contexts (i.e. at work, public accommodations, school, etc.). In some cases, the discrimination question includes race as part of the discrimination experience OR a two-part sequence, which includes experiencing discrimination and then the respondent's assessment of the basis for such treatment (i.e. race, gender, class, language, immigrant, etc.).

The inclusion of “some other race” appears to be an attempt to capture information from individuals who do not find themselves “fitting into” the more commonly used racial categories (Grieco and Cassidy Reference Grieco and Cassidy2001; Logan Reference Logan2003). A distinction for studies that include the “some other race” option is whether an open-ended response is allowed and recorded (Garcia Reference Garcia, Sanchez, Sanchez-Youngman, Vargas and Ybarra2015). Finally, the most infrequent race-related terms are phenotypical characteristics, most likely skin color or skin tone. While only three such studies include skin color or tone, this researcher is quite aware of the growth of substantive focus on this dimension of race/ethnicity (Hochschild Reference Hochschild2011; Perreira and Telles Reference Perreira and Telles2014; Tafoya Reference Tafoya2004).

This race project may serve as an impetus to discuss the range of race-related terms that could be considered in order to understand and examine the construction of race and its relationships to a variety of socio-political and economic statuses/conditions. The results in Table 4 still demonstrate that if race is a variable within a study, the preponderance is a single item (42.0%). Another 15.7% of the studies have two race-related items. We did find one-fifth of the studies to have six or more race-related terms (one study had 37 items). We have found that when studies have greater numbers of items (usually more than three), the other race-related items/terms include racism, racialization, discrimination and the like. In addition to the respondent's answers, the question battery also derived information from other members of the household.

Tables 1–3 establish a portrayal of the characteristics of the race project studies, the researchers who conducted the studies, and the range of race-related terms used. The last two tables represent the “intersection” of characteristic of the PIs and the range of race-related terms in their studies. In the previous tables, it was noted that PIs who received their Ph.D.s in the 1970s and 1980s were more represented in the race project studies. In addition, women and minority researchers were underrepresented and there were more sociologists. Do these descriptive characteristics carry over into a “broader” inclusion of race-related variables?

If we examined when the PIs received their Ph.D.s, proportionately, those recipients during the 1980s (50.8%) had five or more race-related items, followed by Ph.D. recipients of the 2000s (47.8%) and those from the 1970s (35.9). In terms of the absolute inclusion of the numbers of race-related items, those researchers who received their Ph.D.s in the 1970s were 78, and followed by the 1980s Ph.D.s (63). While not exactly a linear relationship as one move through the decades, the pattern of adding more race-related items is evident.

Table 5 compares the period in which the studies were conducted and the frequency of the number of race-related terms used. It was not until the decades of the 1990s and beyond that more extensive use of multiple “measures” of race was evident in the social science surveys. During the 1990s, approximately one-third of these studies include four or more race-related items. This percentage increased to 42.5% since the 2000s.

We explore our bivariate comparisons a little further by examining some additional characteristics of the PIs (i.e. gender, race/ethnicity, and discipline) and the range of race-related items utilized. The two additional background characteristics are gender and race/ethnicity of the PIs. From the more descriptive tables, there was greater representation of males and non-minority group members among the researchers.

An examination of gender and range of race-related items shows virtually no differences. That is, female researchers used four or more race-related variables (42.1%) as opposed to their male counterparts using four or more (39.8%). The most noticeable differences lay with the race/ethnicity of the PIs. Slightly over one-third of the white PIs used four or more race-related variables. In contrast, over twice as many (percentage-wise) African American, Latino, and Asian American researchers used four or more race-related items. More specifically, 82.4% of African American, 73.9% of Latinos, and 100% of Asian American researchers used four or more items. Does this finding represent a greater saliency and attention that minority researchers give when including race in their survey projects? A partial explanation lies with a substantial number of minority researchers who were part of the same research project and race/ethnicity was one of the central foci of the study. At the same time, if race is a central focus, does this ensure a broader range of race-related variables being included? If so, is this pattern more the case for minority researchers? Overall, it is clear that from the small representation of minority researchers in the race project studies, race receives broader inclusion.

The last aspect of the researchers’ background deals with their discipline training. Two observations are discernable. The first is that researchers in the mainstream social sciences (i.e. Political Science, Psychology, and Sociology) are comparable in the percentages of race-related items in their surveys that include four or more items (42.3%, 38.6%, and 44.2%, respectively). On the other hand, what have been categorized as other social sciences and non-social science fields have almost one-half of their studies containing four or more items. Having taught several workshops involving the health field as well as methodological issues involving race and ethnicity for quite a number of years, the literature searches show a greater preponderance of citations from health-related fields, social work, and inter-disciplinary degree programs. In the conclusion section, I will expand on this point and others (Table 6).

THE RACE PROJECT: OVERVIEW AND PERSISTENT ISSUES

The ability to create a database of social science survey research has enabled this researcher to measure the use of race over six decades. An effort that represents a long, tedious, persistent, and focused endeavor, although slow, suggests that the process was able to gain momentum with the assistance of colleagues and graduate students at the University of New Mexico and the University of Michigan. While this statement may seem more like an acknowledgment, it represents an important element of social science related research that is seldom undertaken. For example, a similar research area is the matching of voter data with the geographic reference to their precincts over numerous elections and years. In both cases, the investment of time, comparability over time, and elements of data harmonization and verification can be too daunting and labor intensive to undertake or make it worthwhile. Nevertheless, such attempts have the possibility of assessing the patterns of dealing as in the case, with race in social science surveys, as well as directing some broader discussions about the meaning, conceptualization, and measurement of race and its corollary concepts.

As a result of this examination, some noticeable trends have arisen. Generally, studies that were conducted in earlier time periods were less sensitive to multiple race categories than those conducted more recently. The delineation of racial categories (i.e. African American, Asian, Native American, etc.) represents both the growing diversity of the American people, and the official OMB classification schema of racial categories. While this study did not explore the labels used to describe racial groupings, this aspect signifies another dimension of understanding race.

Many of the studies that are coded into this project's database involve the interviewer asking the respondent about their race. On average, the more recent the study, the more racial categories it recognized and listed. This could be the result of several factors, some of which go hand in hand. One is that the diversity of the country has increased overall, thus creating more diverse respondent groups that are accounted for by the conductors of research. Another is the fact that over the course of contemporary surveys, the problems that arise from non-response of the extant racial categorizations has gained more attention. Thus researchers have realized the need for inclusion of more racial categories in their interviews (as well as allowing for multiple responses). Currently the U.S. Census Bureau One is reconsidering a change in the race and ethnicity questions for the 2020 decennial census (U.S. Bureau of the Census 2017). For this round, the alternatives include the addition of MENA (Middle Eastern-North African) and the folding in of the Spanish origin (ethnicity) item into the race question so that Hispanic/Spanish origin would be one of the racial options.

On the other hand, when race has multiple responses and is used as an analytical variable, data reduction usually entails assigning the respondent into a primary race category. This is, most often, the result of the responded being asked what their “primary race” is. Several consequences of this approach are that the assumption of “primary race” is not context “dependent” and that individuals perceive themselves as being in a singular race categorization. Finally, the researcher is unable to determine on what basis a person puts him/herself into a racial category (i.e. self-image, phenotypical characteristics, group identity, perceptions by others, etc.). Clearly my discussion of the concept of race posits a more complex understanding of race and the breadth of measures necessary to “capture” what race is and means.

At the same time, surveys can include the protocol for the interviewer to make certain assessments about the race of the respondent (more so in face to face interviews). By asking the respondent how he/she perceives others placing him/her racially. These aspects of race can characterize the notion of racial identification as more than self-identification, which also includes institutional actions/policies that establish racial categories, and perceived racial classification by others. This perspective places the notion of race as contextual, interactional, and dynamic. Understanding race entails both measures of self-identified and socially assigned racial category(ies).

In addition to examining studies that included race as a variable, the race project collected information about the PIs. Since it is the researchers who design the studies and determine what items to include, the concepts and possible relationships to examine and what measures to include and construct. In the race project, several background characteristics were included (i.e. gender, race/ethnicity, discipline, and year of doctorate). Interestingly, year of receiving Ph.D. and more nuanced and numerous questions pertaining to race is not a linear relationship. That is, researchers trained in the 1970s and 1980s are more inclined to use multiple race-related terms. While there is some variation across traditional social science disciplines and greater use of race-related terms, a more noticeable pattern was evident among researchers from other than the more “prominent” social sciences and inter-disciplinary programs. This was much more evident among researchers in the public health fields. Overall, researchers in the less “prominent” social science fields and/or interdisciplinary training seem to incorporate a broader notion of what race involves and/or how race serves a more expansive focus of their research endeavors. One possible explanation lies with the longstanding tradition of treating race as a categorical variable in the “main” social science disciplines while more inter-disciplinary-oriented fields make the connections on the multi-dimensionality of race across situations, social structures, and contexts.

The most critical aspect of a researchers’ background is their racial or ethnic identification. That is, the proclivity to use multiple race-related items is much more the case for racial and ethnic researchers. It has been noted that there is a clustering of minority scholars engaged in specific projects. The synergy of minority researchers and the bases for collaborative ventures can also be a contributor for the broader inclusion of race-related items. The field of race and ethnicity has expanded in terms of greater numbers of articles that focus on race and ethnicity, a larger pool of researchers (minority and non-minorities), and organized sections in most social science associations. These developments can have the impact of legitimizing a previously “marginalized” sub-field and infusing more mainstream approaches OR encourage race and ethnicity researchers to push for more innovation.

The continued relevance of including race in social science research affords more opportunities to evaluate the conceptualization of race and the range of measures and dimensionality of race. This meta-analysis and focused discussion about the multi-dimensionality bases of race can be characterized by an excerpt from James (Reference James2001); “…there are those who study race and racial dynamics, and those who routinely use the concept of race in their studies. In the case of the former, …. RACE is seen as a profoundly social characteristic. The dynamism and fluidity of race is often used to better understand related social processes. …..Racial delineations … result from historical patterns of racial hierarchy imbedded in ongoing interactions…. In the case of the latter, …. those who use race or ethnicity in their research, as opposed to those who study race, tend to treat it as a primordial or fixed characteristic. ….treat race as a function of fixed differences between ‘populations’. ….race is conceptualized as a cause of myriad of social processes and distinctions” (James Reference James2001, 246–47).

As contemporary scholars attempt to understand race as a lived experience, more generated research and discussions can serve to advance social science research so that studies of race became more comprehensive (Ulmer, McFadden, and Nerenz Reference Ulmer, McFadden and Nerenz2009; Ver Ploeg and Perrin Reference Ver Ploeg and Perrin2004). At the offset of this paper, I highlighted David Williams’ (Reference Williams1994) review of race as a concept and measure(s) in a health journal. Health researchers have been paying more attention to the conceptualization and measurement of race (Cooper and David Reference Cooper and David1986; Jones, LaVeist, and Lillie-Blanton Reference Jones, LaVeist and Lillie-Blanton1991; Miller Reference Miller1987; Osborne and Feit Reference Osborne and Feit1992; Wilkinson and King Reference Wilkinson and King1987; Williams, Lavizzo-Mourey, and Warren Reference Williams, Lavizzo-Mourey and Warren1994). In the conclusion section of Williams’ article, he discusses how professional journals and their editors serve as active participants in the development of race and social sciences. He first suggests that editorials can educate the research community regarding appropriate and inappropriate uses of race. Second, since most researchers are responsive to directives from editors and editorial guidelines, their participation in research related discourse can affect current uses of the race construct. Third, minimally, editors can stipulate when researchers report whether race was assessed by respondent self-report, proxy report, extraction from records, or direct observation. Williams emphasized that in the studies reviewed, very few researchers bothered to specify how race was ascertained. Clarity and specificity of the meaning and choice of measure of race can have informative benefits to the researcher(s) as well as the readers. Finally, there is a need for more accurate definitions of racial and ethnic status as explanations for the differential impact of social phenomena and policy changes and system reform on population subgroups depends on these working definitions (Williams Reference Williams and Collins1995, 269–71).

For example, in the case of Latinos, aspects such as birthplace, country of origin, recency of immigration, language facility, and acculturation become important characteristics that should be part of the habitually considered (Hayes-Bautista and Chapa Reference Hayes-Bautista and Chapa1987; Yankauer Reference Yankauer1987). The understanding of race incorporates the historic and contemporary experiences of the particular population or group under study and places this social phenomenon in a larger context. We are starting to see more social science researchers factor in elements of a color-conscious society (Bonilla-Silva Reference Bonilla-Silva2013; Telles, Flores, and Urrea-Giraldo Reference Telles, Flores and Urrea-Giraldo2015) via skin color and other phenotypical “characteristics.” Darker skin color appears to have been established as a social characteristic predictive of opportunity structures and societal limitations.

In addition to analyzing the use of race in social science surveys, the results of the race project serve to accent the need for more thoughtful consideration of the conceptualization and measurement of race. The use of race primarily as a categorical variable in more or less an automatic and a theoretical manner, or both, has real restrictions on our understanding and explanation of how racial differences are embedded into societal institutions and can serve only to extend the misrepresentation of social reality or lived experiences. The need for a careful, purposeful, theoretically informed clarification of race is a significant challenge for social science researchers. Race is a complex “assortment” of distinguishing histories and specific life situations that bear on access, opportunities, differential treatment, and self-worth, which affects many facets of a person's “lived experience” as well as societal relationships and policies.

The challenge for researchers lies with dealing directly with these complexities and more theoretically “rich” ways to conceptually “frame” race and develop more extensive measures. At the same time, adding complexity would require greater conceptual clarity of race and multiple measures. This could produce a tension between parsimony of items/measures and limitations of time and costs. Yet, this phenomenon is an ever present “task” of social science efforts to operationalize concepts into valid and reliable measures. A corollary to this challenge lies with use of appropriate analytical techniques to “capture” the multi-dimensional scope of race. For example, the application of multi-level (hierarchical) models requires the specification of predictor variables from a multiple levels (fixed effects) while denoting which variables and key interactions to include. In addition, there is a need for the specification of correlation among responses from shared clusters (random effects) (Gelman Reference Gelman2006). Components of the multi-levels of the social processes of race would include the individual, their household, their neighborhood, state and federal polices and other levels that influence race. The purpose of this paper is to account for the measures of race in major social science surveys in the context of theoretical conceptualization of race and challenges researchers to “capture” race in both its meanings and implications for individuals and groups in “everyday experiences.”