Still Searching for a True Race? Reply to Kramer et al. and Alba et al

Previous articleNext article FreeStill Searching for a True Race? Reply to Kramer et al. and Alba et al.1Aliya Saperstein and Andrew M. PennerAliya SapersteinStanford University Search for more articles by this author and Andrew M. PennerUniversity of California, Irvine Search for more articles by this author Corrections to this articleErratum for “Still Searching for a True Race? Reply to Kramer et al. and Alba et al.”PDFPDF PLUSFull Text Add to favoritesDownload CitationTrack CitationsPermissionsReprints Share onFacebookTwitterLinked InRedditEmailQR Code SectionsMoreTo conserve space for the publication of original contributions to scholarship, the comments in this section must be limited to brief critiques; author replies must be concise as well. Comments are expected to address specific substantive errors or flaws in articles published in AJS. They are subject to editorial board approval and peer review. Only succinct and substantive commentary will be considered; longer or less focused papers should be submitted as articles in their own right. AJS does not publish rebuttals to author replies.We wrote “Racial Fluidity and Inequality in the United States” (Saperstein and Penner 2012) with the aim of jump-starting a conversation about how race is best conceptualized in studies of stratification. Does assuming that people have static, often mutually exclusive, “races” help us understand disparities in the contemporary United States? Or are there inequality-sustaining mechanisms we might have missed by assuming a process of consensus through which racial categorizations are ascribed at birth and effectively fixed? That two teams of scholars took time to engage with our work is a positive sign that a much-needed conversation is happening. It is, of course, disheartening that Kramer et al. (2016) (hereafter KDH) and Alba et al. (2016) (hereafter AIL) come to the conclusion that we, at worst, misinterpreted our data and, at best, overstated our case. Nevertheless, we are grateful to have this opportunity to clarify our claims and intentions and to offer new evidence that returning to assumptions of rigid racial ascription is not the way forward.Our reply addresses the three main points of empirical critique across the two comments: (1) that a relationship between social status and racial categorization of similar direction and magnitude could be produced by measurement error; (2) that our findings are neither as common nor as generalizable as we claimed; and (3) that we did not adequately demonstrate that stereotypes, operating through what the interviewer does or does not hear about the respondent, are a key causal mechanism. We either provide evidence that directly refutes each point, explain why it results from a misreading of our argument, or both. In the process, we underscore our earlier findings with additional evidence of how social factors shape categorization: through selective processes of “ethnic attrition” as well as what interviewers knew about the respondents’ use of crack cocaine.First, a clarification on the scope of this debate: the details of our empirical analysis are not the only aspect of our article being subjected to scrutiny; also in question for both commenters is whether or not race and ethnicity should be conceptualized as stable individual characteristics. Given space constraints, we focus on the specific empirical critiques, but it is important not to lose sight of their theoretical foundations and implications. Although AIL and KDH give us credit for advancing a “sophisticated” and “provocative” thesis, we are not the first to conclude that recording these characteristics, and assigning individuals to categories, is a more complex task than racial commonsense and received practice would indicate. Thus, we encourage readers to weigh not only other empirical research that demonstrates the relationship between social status and racial categorization can run in both directions (Saperstein and Gullickson 2013; Saperstein, Penner and Kizer 2014; Young, Sanchez, and Wilton 2015; Simonovitz and Kezdi 2016) but also the broader body of theoretical work on the social construction of race and ethnicity.Can the Results Be Explained by Measurement Error?Both AIL and KDH raise concerns about how much of the racial fluidity we reported is “real” and how much is due to measurement error. AIL highlight this issue by dividing their descriptive statistics to show which respondents experienced one or two changes in racial classification compared to three or more. KDH claim that our original estimates for the effect of social status on racial categorization could result from introducing random variation alone.To counter these critiques, we begin with our preferred approach to potential coding mistakes in the data: we show that when we remove cases with classification discrepancies that might be considered “errors,” we get results similar to those we originally reported. We then consider the results presented by KDH (in their Table 1) and demonstrate that there is nothing in their approach that suggests our core finding can be attributed solely to measurement error. However, we also note that most discussions of measurement error assume the existence of an objectively verifiable value, as is the case for individual attributes like height or weight. To make an analogous assumption for race is problematic.Table 1. Predicting Racial Classification with and without Classification “Blips” BlackWhite Includes BlipsExcludes BlipsIncludes BlipsExcludes BlipsUnemployed.......34***.41***−.29***−.30***Impoverished.......35***.25*−.36***−.39***Incarcerated.......29+.27−.25**−.31**Received welfare.......15*.20−.13***−.15**Note. Data are from the 1979 NLSY. Each column represents a different model with specifications following from Saperstein and Penner (2012, Table 4), except that these models are limited to the years in which it is possible to identify blips in both current and lagged classification (1982–94).+ . P I)Self-identification model: Unemployed....76.85.37.02−.41−.59−.28.04 Impoverished....83.86.42.03−.59−.75−.35.00 Incarcerated....27.42.22.44−.55−.61−.30.05 Received welfare....25.53.24.48−.07−.41−.20.94Interviewer classification model: Unemployed....32 .33.54−.29 −.26.02 Impoverished....35 .36.61−.37 −.32.00 Incarcerated....32 .30.43−.33 −.28.07 Received welfare....18 .11.14−.12 −.11.26Note. Models include other status variables and controls from Saperstein and Penner (2012, Table 4). Cols. P(B I) report the proportion of the 1,000 replicates of the IV & DV models with coefficients of greater magnitude than the baseline results (i.e., how often does eq. [2] produce coefficients as large as the baseline model). In the interviewer classification models, we do not replicate the “IV only” (KDH) approach because the racial classification from a given survey year can be both an independent variable and a dependent variable.View Table ImageOur small change to their procedure has large consequences. Like KDH, when we introduce changes only to the independent race variable, we find results that are similar in magnitude or larger than the baseline coefficients. However, when we perturb both the independent and dependent race variables, this is no longer the case. The pattern of results in the baseline models is infrequently produced by the IV&DV model; for example, the IV&DV coefficient for unemployment is as large as the baseline coefficient just 4% of the time when predicting self-identification as white, and 2% of the time when predicting self-identification as black.12 Put simply, we show that their results can only be obtained if one makes the unfounded assumption that measurement error only affects race when it is an independent variable. Thus, although we cannot condone KDH’s approach to evaluating measurement error, we conclude that there is nothing in KDH’s critique to suggest measurement error is the only reason the relationship between social status and racial categorization appears to run in both directions.Who Is Really “At Risk” of Racial Fluidity?The critique that we overstated the case for racial fluidity raises questions about (1) how common such fluidity is likely to be and (2) how general is the relationship between status and racial categorization. We address each of these issues in turn. Both AIL and KDH assert that meaningful changes are less common than we suggested and, when they do occur, such changes are limited to people who are racially “ambiguous.” We do not disagree that categorical fluidity is observed more frequently in particular subpopulations, and we stated as much in “Racial Fluidity and Inequality” (p. 707). However, it is problematic to assume that either racial ambiguity or categorization as “Hispanic” (or “Latino”) is a static characteristic. Further, it is important to clarify it is not the level of categorical racial fluidity but rather the process through which social status influences racial perceptions that we propose to be more general.Significance of Fluidity not Primarily about FrequencyIn “Racial Fluidity and Inequality” we highlighted that more than 20% of the 12,686 NLSY respondents experienced at least one change in their racial classification. AIL get a lower estimate because they apply survey weights. Although we were careful to discuss the level of fluidity relative only to the sample, we acknowledge that we did not explicitly state that we were not using the NLSY to establish the level of racial fluidity as a population parameter. From our perspective, a “true” estimate of racial fluidity is about as meaningful a concept as a “true” measure of race. Even gauging whether there is a lot of racial fluidity, or only a little, depends on how stable one expects race to be.To us, the significance of racial fluidity stems not from its common-ness but from its utility for understanding processes of racial categorization. Fluid cases provide leverage that studying racially stable people cannot: they allow us to ask, what predicts being assigned to, or being removed from, a particular racial category? For this purpose, what matters most is whether a given sample provides enough variation to study the correlates of category assignment. That said, we recognize that establishing the magnitude and scope of racial fluidity is likely to interest many researchers and address these issues below.To weight or not to weightAs our aim was to exploit the repeated racial classifications to better understand predictors of categorization, the issue of weighting is most relevant for our multivariate analyses. We estimate coefficients for our key status variables using both the 1979 sample weight used by AIL and a customized panel weight. If anything, the evidence for our claims is stronger when we use the survey weights (see Table 3).13Table 3. Predicting Racial Categorization with and without Weights BlackWhite Unweighted1979 WeightsPanel WeightsUnweighted1979 WeightsPanel WeightsSelf-identification model: Unemployed....76***.79***.79***−.41***−.42***−.42*** Impoverished....83***.93***.93***−.59***−.65***−.65*** Incarcerated....27.37.33−.55*−.69**−.69** Received welfare....25.35.35−.07−.23+−.23+Interviewer classification model: Unemployed....32***.31***.31***−.29***−.27***−.27*** Impoverished....35***.51***.51***−.37***−.49***−.49*** Incarcerated....32*.39*.39*−.33***−.42***−.42*** Received welfare....18**.28***.28***−.12***−.21***−.21***Note. Data are from the 1979 NLSY. Model specifications follow Saperstein and Penner (2012, Table 4). Models predicting self-identification and classification use different panel weights, corresponding to the different survey years on which they draw.+ . P < .10.*. P < .05.**. P < .01.***. P < .001.View Table ImageHowever, in considering whether or not our estimates should have been weighted, it is important to recognize that the survey’s weighting schemes treat racial categories as fixed strata. Respondents are weighted differently depending on how they were classified by NLSY in 1978—which is not necessarily consistent with how respondents later identified themselves, were perceived by interviewers, or would have been recorded in the 1970 census (to which the weighted population distributions were pegged). So, if one qualified as “Hispanic” based on the survey screener, one would be assigned separately calculated “Hispanic” weights throughout.14 Yet, respondents also could self-report Hispanic origins in 1979, or answer “yes” that they were “Hispanic, Latino, or of Spanish origin” in 2002. The complexity of who counts more or less when the weights are employed is highlighted by the fact that just 467 (32%) of the 1,437 respondents who have “Hispanic” weights are consistently “Hispanic” across all three measures. Given this, and the fact that weighting did not affect our multivariate analyses, we present unweighted frequencies and model estimates throughout our reply.Fluidity and ambiguityAIL and KDH emphasize that the vast majority of Hispanics (as defined by the 1979 measure) have fluid racial classifications, and that these “ambiguous” cases account for a sizeable proportion of the overall fluidity in the sample. They also imply that much of the racial fluidity would be eliminated with a more appropriate set of ethnoracial categories. We disagree that a better measure of race would eliminate either fluidity or ambiguity; some cases will fit better in a given classification scheme than others, and this is true for all types of classification (Zerubavel 1991). Further, rather than thinking of racial ambiguity as a relatively fixed characteristic of the person being categorized, as AIL and KDH seem to, we think of racial ambiguity as the result of a confluence of factors from the individual’s own characteristics to the circumstances in which the categorization takes place. Neither people nor populations are always racially ambiguous; ambiguity (or lack thereof) is socially constructed and entwined with the classification scheme, such that different people will be “ambiguous” in different schemes.We illustrate that fluidity and the expectation of ambiguity do not always go hand-in-hand by comparing levels of racial fluidity in the NLSY across a range of individual characteristics likely to be associated with categorical ambiguity (or difficulty fitting particular individuals into U.S. racial classification schemes). This point can be seen most clearly in Table 4 among NLSY respondents who selected “origin or descent” categories in 1979 that might indicate multiracial heritage (e.g., black and Asian Indian); if anything, as a group, they are less likely to have fluid racial classifications over the course of the survey than those who report a single origin (or whose multiple origins do not cross racial boundaries).15 Racial fluidity is more common not only among people who report Hispanic origin in 1979 but also among people who were not born in the United States,16 and people whom we classified as changing their self-identification between 1979 and 2002. Yet some fluidity is present even among respondents who are non-Hispanic, U.S. born, and stably self-identified. Thus, racial fluidity and racial ambiguity should be treated as distinct analytical concepts, regardless of how related they might seem.17Table 4. Individual Ambiguity and Racial Fluidity % at Racial multiracial origins in not report multiracial origins in a Hispanic origin in not report a Hispanic origin in born in the United in the United between 1979 and did not Data are from the 1979 NLSY. are following Saperstein and Penner Table address AIL and KDH’s claims that the category the observed fluidity, we the NLSY to Add We find similar levels of change in racial classification between and 4 in Add as we do changes in NLSY Add more specific classification scheme, which or and or but did not include Although neither survey or as a AIL and KDH, we are that another for the classifications would racial “Hispanic” category might make some classifications more but could make other classifications less stable than they were when there were the between and black and or Asian and Hispanic are from with AIL and KDH that how the level of fluidity across is to understand processes of racial categorization, and the relationship between racial fluidity and ambiguity is important to we to focus our instead on the predictors of categorization because the question of whether or not status characteristics change with changing racial categorizations is what the social construction of race to broader issues of of in Racial and might seem that observed categorical racial fluidity could be in particular subpopulations, while the relationship between social status and racial categorization could be a more general This is by that the status factors associated with a change in categorization from to in one year (e.g., from can also help to explain why might being as in the Further, even if status racial perceptions for some observed racial categorizations can be more to changes in social demonstrate this, we discuss the of thinking of racial categorization in of continuous We then directly to critique by fixed effects models the between social status and racial categorization across a of We conclude this section by whether status factors also shape who as categorical change continuous of of each person in the United being assigned a race in a static, categorical we find it to think of as a of identifying or being classified in each category that represents the that they will identify or be seen as a particular category at a particular point in time (see “Racial Fluidity and We that status changes in social in the potential to these by a in one direction or the a change in a of categorization results in observed fluidity depends on a of other factors including the categories who is the and where the person being was in the distributions to begin It is in this sense of continuous of categorization, and how those are by status that we our results to be seen as to in best evidence of this comes from our work on the process of racial categorization et al. We our finding from the NLSY in an by that the same are racially differently depending on whether they are in or us to whether or not the status an effect on racial when the categorization In the even when individuals classified as white, their to the for a classification than it did when the same was presented in the in the when a was classified as average trajectories to the These results suggest that even when status do not change how people are racially classified in categorical they can an important in racial perceptions more specific in question the claim that the relationship between social status and racial categorization is a more general AIL their evidence of a relationship between social status and classification as based on models to people who in 1979 using either Hispanic origin categories or origin categories that racial (see Table We their conclusion across a broader range of subpopulations, including only the NLSY sample and only or AIL note issues of in their models, and we consider most of our models to be Nevertheless, the is to demonstrate estimates for the of racial categorization with status factors are consistent in direction and magnitude regardless of (see Table of Model Predicting Racial Categorization and or and or Hispanic or Hispanic or as Received as Received as Received as Received Data are from the 1979 NLSY. Each coefficient represents a different model predicting racial categorization using the relevant status variable and controls for in the year fixed and interviewer characteristics and The first model also a for prior racial (as and additional controls for whether the respondent reported a Hispanic origin in 1979, multiple in 1979, or was born the United Saperstein and Penner in the models account for the of fixed effect models account for the of or . P < .10.*. P < .05.**. P < .01.***. P < .001.View Table we estimate a of models with a common set of controls such as in which our key status factors are our models include respondent fixed We also show results for the sample with and without respondent fixed effects the and significance of the estimates can be compared across the range of model We do not expect all of the coefficients in Table to be given our original fixed effect model results (see “Racial Fluidity and where status factors were rather than we the sample into subpopulations, we have even less to than in our original analyses. However, there is to be by comparing estimates from these fixed effects models relative to estimates from models with less controls but more evidence our in Table can be in the relationship between unemployment and racial both self-identification and interviewer classification. all of fixed effects models, of estimates for the between unemployment and racial

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