Universal Dependencies - English - GUM

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The prevalence of discrimination across racial groups in contemporary America:

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Results from a nationally representative sample of adults

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Introduction.

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Personal experiences of discrimination and bias have been the focus of much social science research. [1 - 3]

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Sociologists have explored the adverse consequences of discrimination [3 – 5];

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psychologists have examined the mental processes that underpin conscious and unconscious biases [6];

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neuroscientists have examined the neurobiological underpinnings of discrimination [7 – 9];

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and evolutionary theorists have explored the various ways that in-group / out-group biases emerged across the history of our species. [10]

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In many respects, researchers already possess a wealth of knowledge concerning the origins and consequences of discrimination and bias. [11]

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What also should not be lost in discussion of discrimination is the growing push to implement social policy aimed at reducing the occurrence of discriminatory practices.

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Mandatory diversity trainings in professional settings, for example, are intended to reduce bias in the workplace by increasing the awareness of employees regarding the challenges facing minority group members. [12]

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Indeed, the implementation of certain policies is rooted in the assumption that discrimination and biases are, at least to some appreciable amount, present in modern society.

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Even so, estimates of the prevalence of perceived discrimination remains rare (see [13 – 14]).

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At least one prior study by Kessler and colleagues [15], however, using measures of perceived discrimination in a large American sample, reported that approximately 33% of respondents reported some form of discrimination (see also, Gibbons et al. [4]).

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The current study seeks to build on this research by estimating the prevalence of discrimination experiences among a large, nationally representative sample of adults from the United States.

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Additionally, the analysis address the perceived reasons for reported discrimination experiences.

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Reason for discrimination.

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All respondents who indicated they were discriminated against — specifically, those who responded with sometimes or often to the perceived discrimination measure described above — were asked the following question:

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“What do you think was the main reason for these experiences?”

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Respondents were allowed to choose one response from 11 categories.

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For the present analysis, these responses were recoded into nine mutually exclusive categories capturing the following options:

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race / ancestry / skin color;

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gender;

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age;

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religion;

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height or weight;

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sexual orientation;

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education or income;

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physical disability;

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and other.

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The following categories from the original questionnaire were collapsed into one category for the analysis: race; ancestry or national origin; and shade of skin color.

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Additionally, because this question was only asked of respondents who reported prior discrimination experiences, the built-in skip pattern resulted in a large number of cases scored as missing (legitimate skip).

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Respondent race.

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Because a race variable is not available from the Wave 4 interviews, we use the racial category reported by the respondent during the Wave 1 interview.

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Wave 1 race — rather than, say, Wave 3 race — was used to preserve case counts.

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The logic is that (nearly) all Wave 4 respondents appeared in the Wave 1 sample, but not all would have been interviewed at Wave 3 due to differential patterns of temporary attrition.

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Respondents were asked to indicate their race from among the following categories: White; Black or African American; Hispanic; American Indian or Native American; and Asian or Pacific Islander.

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Respondents were provided the opportunity to select more than one race, and those who did were asked a follow-up question regarding which category best described their racial background.

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In the current study, those respondents who indicated more than one race were coded as “mixed race”.

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Demographic variables.

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To provide information on the analytical sample as a whole, two additional demographic variables are included.

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First, age is a continuous measure created by subtracting the year of the respondents' birth (obtained from Wave 1) from the year of the interview at Wave 4.

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Second, sex was dichotomously coded based on the self-reported sex of the respondent at Wave 4 (0 = female and 1 = male).

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Analytical plan.

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Our exploratory study included three basic steps.

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First, summary statistics of the study variables and racial categories were produced.

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Second, we examined the relative proportions of the two discrimination experience measures across each racial category.

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Finally, we assessed the distribution of reported reasons for discrimination across the racial categories.

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In order to examine potential bivariate associations, the adjusted F statistic (design-based F) was employed as it corrects for a complex sample design such as that used in the Add Health. [21]

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More specifically, when analyzing weighted sample data employing the svy suite of commands in Stata the conventional Pearson χ2 statistic test of independence is converted into “an Fstatistic with noninteger degrees of freedom by using a second-order Rao and Scott (1981 [22], 1984 [23]) correction”. [24]

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The p-value associated with the design-based F is thus more accurate (than the associated with the χ2 statistic) given the adjustments and calculations take into account the weighted nature of the data.

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This final step also included an examination of the relative distribution of racial categories across the various reported reasons for discrimination.

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As noted earlier, all analyses were weighted according to the survey weight provided by the Add Health research staff and standard errors were corrected for the clustering and stratification that defined the sampling strategy.

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Thus, all estimates reported here can be considered nationally representative of the United States.