The Magnifying Effect of Privilege: Earnings Inequalities at the Intersection of Gender, Race, and...

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Stephanie J. Nawyn, Linda Gjokaj

Feminist Formations, Volume 26, Issue 2, Summer 2014, pp. 85-106 (Article)

P bl h d b Th J hn H p n n v r t PrDOI: 10.1353/ff.2014.0015

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©2014 Feminist Formations, Vol. 26 No. 2 (Summer) pp. 85–106

The Magnifying Effect of Privilege: Earnings Inequalities at the Intersection of Gender, Race, and Nativity

Stephanie J. Nawyn and Linda Gjokaj

Feminist concerns about the epistemological problems of quantitative methods have resulted in an underdevelopment of quantitative approaches that could contribute to existing intersectional theory. Further, feminist scholars commonly consider the effects of gender as it intersects with race or class, but relatively little of this research has included nativity (being either an immigrant or native-born to a society). This article addresses these shortcomings by examining patterns of earnings inequality at the intersection of gender, race, and nativity, comparing cohorts of African-born Black and white immigrants to their US-born counterparts over multiple time-points. Further, the depressive effects of gender are large enough so that while there are dif-ferences in women’s earnings across race and nativity, nearly all groups of men still earn more than nearly all groups of women. The article’s results demonstrate that privilege has a magnifying effect, with the advantages conferred from one privileged status increasing the effects of other privilege statuses, which become larger over time. These findings contribute to how feminists understand privileges and oppressions emerging from the intersections of gender with other social statuses, and how such intersections shape economic inequality.

Keywords: African migrants / earnings gap / economic inequality / feminist research methods / gender inequality / intersectionality

In this article, we argue for the utility of quantitative analysis for understand-ing the intersecting effects of gender, race, and immigration status, or nativity (that is, whether someone is native born or foreign born), on earnings. Most

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intersectional analyses utilize qualitative methodologies, but we propose that it is also useful to use quantitative methods to understand intersecting relationships. In doing so, we argue that scholars can better compare differently oppressed or privileged groups by identifying macro-level patterns of inequality among groups. Specifically, our research shows that one privileged status magnifies the positive economic outcomes of other privilege statuses. Thus, greater dif-ferences in earnings can be seen in the intersecting status of privileged groups compared to oppressed groups. Because of this, intersecting statuses produce greater differences in earnings among different groups of men than among groups of women.

This study fills some important gaps in the literature on gender and inter-sectionality. First, little research exists on the intersecting effects of gender, race, and nativity, so we know relatively little about how these statuses work in tandem with one another to shape economic opportunities for migrant women and men. Second, gender is often treated as a control variable in studies of immi-grant earnings, without adequate explanation of how gender organizes labor-market outcomes (Curran, Shafer, Donato, and Garip 2006; Hondagneu-Sotelo 2003; Hondagneu-Sotelo and Cranford 2006; Nawyn 2010; Nawyn, Reosti, and Gjokaj 2009). Finally, feminist scholars have not fully explored the possibilities for using quantitative data analysis for theorizing intersectional inequalities. By examining the complex interactions of gender, race, and nativity quantitatively, we can see how these statuses form a system of relations that can produce large gaps between multiple privileged groups and oppressed groups, thus illustrating the importance of comparing multiple groups located differently in what Patricia Hill Collins (1990) called the “matrix of domination.”

We examine African-origin immigrants to the United States in our analysis because this group has large enough numbers of white and Black migrants to allow us to make within-group racial comparisons using multivariate regressions. We use a cohort analysis to follow groups of US- and African-born individuals over time. Our results indicate that race/nativity intersections produce differ-ent earnings trajectories for women than for men, with the magnifying effects of privilege producing greater differences in earnings over time. We conclude with suggestions for integrating these findings into intersectional theorizing.

The Intersectional Effects of Privilege and Disadvantage

The term intersectionality was originally coined by Kimberlé Crenshaw (1989) and largely developed through a phenomenological focus on women of color, such as through multiracial feminism (Zinn and Dill 1997) and Black feminist theorizing (Collins 1990). Scholars use intersectional theory to explain the complex and uneven ways that relations of race, gender, and class—as systems of oppression—produce inequalities; intersectional theory contrasts with addi-tive theories, which suggest that the inequality emerging from racial, gender,

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and class subordination results in the sum of their constituent effects. For example, Crenshaw’s (1989) originating piece on intersectionality examines the difficulties that Black women face in proving they are the targets of workplace discrimination because, often, the discrimination they face is due to both their race and gender, while anti-discrimination law does not recognize “compound classes” (142). Thus, making comparisons to the experiences of white women or Black men is insufficient for understanding the discrimination, violence, and other types of unequal treatment that Black women experience as Black women (Crenshaw 1991). The theoretical logic of intersectionality is now broadly used to examine different kinds of intersecting statuses of inequality, incorporating axes of inequality like sexuality (Andersen 2005; Weber 2001) and examining the experiences of people other than Black women (Bilge 2010; Hancock 2009; Zambrana and Dill 2009).

Intersectionality is also a methodological approach that critiques positivism and incorporates values, emotions, beliefs, and ethics (Collins 1990, 218). In the minds of many feminist scholars, this makes intersectionality incongruent with quantitative methods. For example, Nikol Alexander-Floyd (2012) argues that Black feminist scholars originally presented intersectionality as an alternative to the positivist research that subjugated Black women and Black women’s ways of knowing, and she critiqued scholars who identified their research as intersec-tional but go beyond Crenshaw’s (1989) original foci. For example, Alexander-Floyd takes Leslie McCall (2005) to task for her focus on “complexity,” which, she argues, further subjugates the knowledge of Black women by reducing power inequality to mere difference between categorical groups (white women, Black women, Black men, and so on). She finds McCall’s claim that quantitative analysis can be used in a post-positivist way unconvincing because it fails to live up to the original theoretical underpinnings of intersectional theory; that is, according to Alexander-Floyd, McCall creates separate, distinct categories of gender, race, and class in order to understand wage inequality, which “opens up space for research that is not focused on marginalized communities in general or women of color in particular” (12), and, therefore, excises the political project of intersectionality.

Conversely, there are many feminist scholars who do not view quantitative research methods as inherently antithetical to the political projects of femi-nism (Apodaca 2009; Bilge 2010; Hesse-Biber, Nagy, and Leavy 2007, 32–35; McCall 2005; Reinharz 1992, 76–94), and who, in fact, see great potential for using quantitative methods in intersectional research. Recent examples of intersectional analysis include: Gary K. Perry’s (2009) mixed-methods study of how college students’ occupational stereotyping is shaped by a job candidate’s gender, race, and class; Gerry Veenstra’s (2011) study of the intersections of race/ethnicity, gender, class, and sexual orientation and self-rated health; and, of course, McCall’s (2001, 2007) studies of wage inequality at the intersection of race/ethnicity and gender. Other studies have examined the intersection


of race and gender only (leaving out class), including Catherine Harnois’s (2009) of the likelihood of women from different race or ethnic backgrounds to embrace feminist principles, and Harnois and Mosi Ifatunji’s (2011) of how interpersonal racial discrimination is also gendered. These scholars use the utility of quantitative methods to examine the relationships among people differently located within a matrix of domination, which is a unique feature of intersectionality. Harnois’s work in particular focuses on relationships among groups of people with different levels of social power, recognizing that while singular measurements of race, class, and gender are an unavoidable artifact from quantitative analysis, intersectionality requires an interpretive lens that focuses on the inequality experienced by marginalized groups, rather than simply a focus on the “main effects” of race, gender, or class.

Scholars have critiqued intersectionality as a theory for its ambiguity, a characteristic that Kathy Davis (2008) has argued has been central to its suc-cess. Attempts to more properly specify the process of intersectional inequality have included an elaborate metaphor for the production and consumption of sugar as a way in which race/gender/class intersections are produced through human activity and integrated into individuals’ identities (Ken 2008), and a typology of intersectional theoretical and methodological orientations (Choo and Ferree 2010). These attempts focus on the processes of intersectional rela-tions, using qualitative data to go beyond mere hierarchies to describe the complex dynamics among race, gender, and class. We agree that this is critical to forwarding intersectionality’s development as a useful theoretical and analytic tool. But quantitative data analysis is better suited for identifying the macro effects that intersecting systems of inequality have on quantifiable outcomes, such as earnings; quantitative methods also allow us to compare multiple groups more easily than is possible using qualitative or interpretive techniques. By using quantitative analysis, we can provide some specification to the different outcomes of groups that are oppressed and/or privileged in different ways, and answer the question of how much inequality exists among differently oppressed groups of women. Therefore, while we conceptualize gender as a complex set of relations that cannot be fully encapsulated in a binary variable, we argue that using a comparatively crude quantitative measure of gender (that is, a binary sex category as a proxy for gender) within an intersectional analytic framework allows us to see the macro-level effects that intersecting relations of inequality have on women’s lived experiences.

The reification of categories of race, gender, and class inherent in much quantitative data is, of course, a problem for feminist scholars. However, while some qualitative research seeks to unpack the categories themselves, other qualitative research assumes certain categories as a starting point for analysis. We argue that such categorization is not necessarily more problematic in quan-titative research than in qualitative research in which the category of Black woman, for example, is used to study the oppression of a particular group of


people and develop a political framework for their liberation.1 Furthermore, we argue that using survey data with these categories has meaning, in that pat-terns of inequality among categories emerge that reflect what we also find with qualitative data analysis. As Harnois (2005) argues in her analysis of survey data on feminist identification, quantified gender and racial categories can allow scholars to examine the differences among women, with intersections of those categories measuring groups that have identifiably different experiences from one another. Examining these differences among different groups of women is a central tenet of intersectionality as described by Crenshaw (1991), and differs from much nonfeminist quantitative research, which uses categories merely as control variables, without attention to how the categories form groups of women and men with distinct types of oppression and privilege, and that does not attend to the oppression of women of color specifically.

We adopt an approach similar to McCall’s (2005) intercategorical approach, using categories of race and gender (and, in the case of our research, nativity) to examine patterns of economic inequality, while recognizing that those cat-egories are socially constructed and shifting. McCall’s intercategorical approach differs from nonfeminist quantitative methodology in three ways. First, the focus is comparing inequalities among groups, rather than merely using a binary or interactional variable to “control” for among-group variation. Second, it embraces a theoretical assumption that the categories being compared are socially constructed and historically shifting, and are imperfect measures of people’s qualitative experience within the matrix of domination. Finally, there is a political goal of ameliorating gender inequality, particularly, since this is intersectional research, for women marginalized by race, class, or other systems of oppression. McCall’s 2005 article “The Complexity of Intersectionality” can be read as proposing the intercategorical approach as the best method for studying intersectionality (this is, in fact, Alexander-Floyd’s [2012] interpretation). We argue, instead, that the intercategorical approach provides one method that is best for certain research questions, but it cannot address all questions of inter-sectional knowledge. Additionally, we do not want to downplay the concerns that some feminist scholars have regarding quantitative methods, as there are probably fewer differences separating positivist and feminist approaches to quan-titative analysis compared to the differences between feminist and nonfeminist approaches to qualitative or narrative analysis.

But, there are no research methods that are without feminist dilemmas,2 and all methods require the kind of critical feminist consideration that we have tried to exemplify in our approach. Nira Yuval-Davis has argued that intersec-tionality needs to be used more frequently in theories of social stratification (2011); in her work, she has pushed intersectional analysis to incorporate a more global framework of social inequality by including citizenship and national belonging (2009). We hope that our application of intersectional analysis in wage inequalities responds to some of her critiques of the field.


Wage Inequality and the Intersection of Nativity with Gender and Race

The intercategorical approach was adopted by Emily Greenman and Yu Xie (2008) in their examination of the intersecting effects of gender and race on earnings. They found that gender disadvantage was smaller for racial minorities than for white people, while racial disadvantage was smaller for women than for men. Thus, the effects of privilege were magnified so that privilege in race led to a larger positive effect of gender privilege, and vice versa. Other research on the effects of gender and race intersections on earnings has found similar patterns of larger earnings gaps among more privileged groups (Cotter, Hermsen, and Vanneman 1999; Kilbourne, England, and Beron 1994).

But few studies have analyzed nativity as it intersects with either gender or race. What work does exist suggests that migration has differential effects on the earnings of migrants from privileged versus disadvantaged groups. This scholarship shows that nonwhite immigrants experience a greater earnings deficit because of their immigrant status than white immigrants do (Stewart and Dixon 2010), and that immigrant women experience greater earnings disadvantage because of their nativity status than immigrant men do (Avalos 1996; Sullivan 1984). The literature on earnings inequality provides different kinds of explanations for these wage gaps, but the most common explanation is differences in human capital. Human capital models generally include measures of educational attainment and years of experience in the labor market, with age being the most-often-used proxy when direct measures are not available. Scholars have found that education accounts for most of the difference between immigrant and US-born women’s earnings, but it explains little of the gap in earnings between immigrant and US-born men in the United States (Avalos 1996; Schoeni 1998).

African Immigrants and Economic Assimilation in the United States

Large-scale voluntary migration from Africa to the United States is relatively new. Most voluntary Black migrants during the early 1900s came from the Caribbean (Reimers 2005), but after US migration policy liberalized in the mid-1960s migration from Africa increased, and it more than tripled between 1980 and 2005 (Kent 2007). By 1980, most new African arrivals were Black, shifting the African immigrant population from majority white in 1980 to majority Black by 1990 (Djamba 1999).

Extant research on African immigrant economic assimilation (most of which has focused on men) generally finds that Black African immigrants’ economic outcomes converge toward those of Black US-born people rather than toward white US-born people. Studies examining African immigrants’ human-capital characteristics find that African immigrants have high levels of education (Butcher 1994; Dodoo 1997; Portes and Rumbaut 2006; Poston 1994)


and occupational status attainment (Butcher 1994; Portes and Rumbaut 2006) compared to US-born Black people. However, after controlling for human-capital variables, Black African immigrant men earn less than Afro-Caribbean immigrant men and about the same as Black US-born men (Butcher 1994; Dodoo 1997; Kposowa 2002; Portes and Rumbaut 2006). Explicit examinations of racial differences found that Black African immigrants earn less than white African immigrants, even when human-capital and demographic variables were considered (Dodoo and Takyi 2002; Kollehlon and Eule 2003). Black African immigrant men experience more earnings disadvantage from job queues com-pared to many other nonwhite immigrant groups (Model and Ladipo 1996), while white African immigrant men have an earnings advantage over white US-born men (Moore and Amey 2002; Nawyn 2012). These studies indicate that African nativity provides an advantage for white African immigrant men though not for Black men, and that racial stratification in the United States remains a key determinant of the earnings of Black African-born men.

Comparable research that focuses specifically on African immigrant women is sparse. Research on African immigrant women in the United States (Arthur 2009) and in Canada (Musisi and Turrittin 2006) indicates that Black African immigrant women have high levels of human capital, but are often employed in lower-paying industries and face significant racial discrimination. However, this same research also shows that Black African immigrant women place a strong emphasis on education and are quickly becoming part of the Black middle class. Research in Canada shows that African immigrant women working full-time earn more than full-time-employed Canadian-born women, most likely due to African women’s higher levels of human capital (Laryea and Hayfron 2005). But Suzanne Model and David Ladipo (1996) found that Black African immigrant women in New York City experience the most earnings disadvantage compared to other minority groups, including US-born African Americans. So, despite their high levels of human-capital and immigrant selectivity, Black African immigrant women are likely to be among the most disadvantaged in the US labor market once human-capital variables are controlled.

Research Question and Theoretical Proposition

Based on these findings, we ask the question: How does privilege and disadvan-tage vary at the intersection of gender, race, and nativity between African- and US-born Black and white women and men in the United States? We argue that it is critical to analyze not just oppression, but also privilege in order to fully understand how intersecting inequalities shape outcomes, such as earnings. We theorize that privilege has a magnification effect, meaning that privilege is structured in such a way that having privilege in one area (such as gender or race) produces additional privilege in others (such as nativity).3 Conversely, multiple statuses of disadvantage will produce smaller effects in earnings, so


that there will be smaller differences among multiple disadvantaged groups, even when those disadvantages come from different statuses of inequality. For example, white men experience more privilege related to their gender than men of color; white African men experience more advantage from their immigrant status than Black African men; white women experience less privilege related to their race than white men; and Black African women experience less privilege from their immigrant status than white African women.

Empirically, this predicted dynamic will result in groups with multiple disadvantages clustering together near the bottom of the earnings distribu-tion, with larger differences among groups with multiple privileges. This will also appear as lower earnings for all women compared to men. Therefore, after controlling for human capital, women overall will have more similar earnings to one another than to men, and the differences in earnings among women will be smaller than the earnings differences among men. Finally, we expect that differences in earnings will increase over time, so that, as we follow cohorts of privileged groups, the earnings advantages will accumulate and thus become larger over time.

Methods

This article uses the Integrated Public Use Microdata Series (IPUMS) decen-nial census data from 1990 and 2000, and American Community Survey (ACS) data from 2009, made available by the Minnesota Population Center (Ruggles et al. 2008). We selected US-born people and people who were born in a country in sub-Saharan Africa who do not have American parents. The people selected were between 25 and 64 years old, were not enrolled in school, and were employed either full- or part-time at the time of the data collection, with an income greater than zero. To limit the complexity of the racial analysis, we selected people identifying as either non-Hispanic Black or non-Hispanic white, excluding people identifying with more than one race. Gender is mea-sured by sex category (male or female). Individuals self-identified their sex, race, and nativity based on fixed choices determined by the US Census Bureau’s categorizations.4

We constructed four age cohorts (25–34, 35–44, 45–54, 55–64) and five migration cohorts (entry into the United States before 1970, during the 1970s, 1980s, 1990s, 2000s), drawing from methods used by Dowell Myers and Cyn-thia Cranford (1998) and Richard Alba (1988).5 We also include measures for educational attainment and the number of typical hours worked per week (measures of human capital). The dependent variable is logged annual earn-ings, adjusted for inflation (in year 2009 equivalent dollars). We ran regres-sion models using these independent variables to predict earnings, focusing particularly on the three-way interaction of race, gender, and nativity. We then ran regressions separately by gender to examine the effects of the time


Table 1. Weighted Frequencies of Nominal and Ordinal Variables % NAfrican 3.63 885,173Black 14.10 3,437,624Female 46.60 11,357,908Education Less than high school 8.67 2,113,873 High school diploma 30.02 7,317,689 Some college 31.20 7,605,434 Bachelor’s or higher 30.10 7,336,957Age 15–24 8.07 1,966,590 25–34 24.70 6,021,189 35–44 27.60 6,727,358 45–54 24.86 6,058,336 55–64 14.47 3,526,927Migration cohort pre-1970 4.49 39,729 1970–79 13.07 115,699 1980–89 26.03 230,371 1990–99 32.80 290,310 2000–09 23.47 207,743

variables. These methods allow us to see how race and nativity affect earnings within gender over time.

Results

Table 1 presents the weighted frequencies of nominal and ordinal variables, and table 2 shows the weighted means and standard deviations of continuous variables. These frequencies use US Census Bureau weights and therefore show the estimated number of people within the full population. African immigrants represent a relatively small proportion of the overall population (3.63 percent). Because of the race and gender distribution of African immigrants, the overall sample has a greater percentage of Black people (14.10 percent) and a lower per-centage of females (46.60 percent) than the general US population. Education levels are high, with over 60 percent having at least some college education. Most of the African immigrants arrived in the United States during the last two decades. The average usual number of hours worked is 41.19 hours, and the average earnings is $47,566.

There is great diversity in the race and gender of migrants coming from different African countries. Such diversity is not possible to include in quan-titative modeling, which is why we group all migrants under the category of


Table 2. Weighted Means and Standard Deviations of Continuous VariablesMean S.D.

Usual hours worked per week 41.19 10.75Adjusted yearly wages 47,566 48,902Logged yearly wages 10.41 0.93

Table 3. Country of Birth for African Migrants, by Sex and Race

Country of birthMen Women Total

White Black White BlackCameroon 9 182 4 123 318Eritrea 8 185 8 126 327

Ethiopia 81 1,084 67 794 2,026

Ghana 20 1,190 10 705 1,925

Kenya 64 318 58 243 683

Liberia 32 475 29 462 998

Nigeria 73 2,571 43 1,323 4,010

Senegal 17 157 7 44 225

Sierra Leone 15 320 8 259 602

Somalia 8 194 5 114 321

South Africa 1,275 74 821 73 2,243

Sudan 55 154 21 44 274

Tanzania 40 46 21 38 145

Uganda 17 110 8 93 228

Zimbabwe 153 62 85 52 352

Other African country* 643 1,397 473 782 3,295Total 2,510 8,519 1,668 5,275 17,972

Note: *Includes respondents who did not specify a specific African country.

African-born. However, it is informative to see from which countries Black and white African migrants originated. We display the distribution of African countries of birth by sex and race (table 3). The largest number of white migrants come from South African and Zimbabwe, while the largest number of Black migrants come from Ghana, Nigeria, and Ethiopia. All countries send more men than women.

Next, we performed linear regressions using variables for African nativity, Black race, and being female to predict earnings. These results are depicted in table 4. A nonfeminist interpretation of these results would be to focus on the main effects of race, class, and gender, which show a much larger effect of gender than of race or nativity. However, doing so can be misleading. We can see from the third model in table 4 that the three-way interaction of gender, race, and nativity is statistically significant, which indicates that Black


Table 4. OLS Regression Models Predicting Logged Annual Earnings (in 2009 equivalent dollars) (N = 254,711)

Model 1 Model 2 Model 3

African 0.16 0.34 0.38Black –0.26 –0.43 –0.42Woman –0.50 –0.54 –0.54Black African –0.14 –0.20African woman –0.13 –0.22Black woman 0.36 0.34Black African woman 0.14Constant 10.67 10.68 10.68 Adjusted R-squared 0.0811 0.085 0.085

Notes: p < 0.001. Earnings are in 2009 equivalent dollars. N = 254,711.

Figure 1. Logged annual earnings for African- and US-born men and women by race and nativity.

African-born women experience an increase in earnings that partially cancels out the disadvantages of being Black and female.

However, this interpretation is typical of a positivist approach and can be misleading. Simply looking at the size, direction, and statistical significance of the coefficients does not provide a clear picture of the earnings differences among various groups defined by gender, race, and nativity. In order to clarify how these significant interactions affect earnings for the different comparison groups, we graphed the actual logged earnings for each group, shown in figure 1. In this figure, we can see that, overall, men of all races and nativity groups


earned more than all women, with the exception of white African-born women, who earned about the same as Black US-born men. (The average earnings between white African-born women and Black US-born men was not statisti-cally significant, indicating that their earnings are essentially identical.) There are clear advantages for white African-born men, who have much higher logged annual earnings than white US-born men. Conversely, white African-born women, while having the highest earnings among all groups of women, do not experience the same racial and nativity advantages; in fact, the nativity gap between white African-born men and white US-born men (0.18) is larger than the gap between white African-born women and white US-born women (0.11). The nativity gap between Black women (0.07) was also smaller than the nativity gap between Black men (0.12), indicating that Black African-born women were less advantaged by their nativity status compared to Black African-born men. The racial gaps between women were also smaller than they were for men. The gap between white and Black US-born women was 0.07, but the gap between white and Black US-born men was 0.40. The gap between Black and white African-born women was 0.11, but the gap between white and Black African-born men was 0.46. Thus, we found support for our prediction that the racial and nativity gaps would be larger among men than among women, and that, overall, women’s earnings would be lower than men’s.

These results are informative, but do not take into account educational levels and hours worked, the age distribution, or year of arrival distribution for immigrants. These factors are important to include in order to parse out the effects of the uneven distribution of age and educational attainment of these groups, as well as how these effects might accumulate over time. As a result, we next ran full regression models that included our variables for education, hours worked, and age and migration cohorts. We ran each regression separately by year in order to more clearly see the effects of gender/race/nativity intersections across time.

We found that after including the control variables, the interaction between being Black and African-born was negative and statistically significant for men, but not significant for women. This indicates that the race and nativ-ity intersection has a significant effect on men’s earnings, but does not have an effect on women’s earnings. The complex nature of these analyses is best illustrated by graphing the different earnings trajectories over time, shown in figures 2 and 3.

In these graphs, we estimated the earnings for the 25–34 age cohort in 1990, and followed this same cohort in 2000 (when it was now the 35–44 age cohort), and in 2009 (44–53).6 For immigrants, we graphed the earnings of the migrant cohort 1980–89 in order to follow the earnings trajectory of the most recently arrived African immigrants in 1990, compared to US-born persons within the same age cohort. By following the same age and migration cohorts over time, we are able to see the interactional effects of gender, race, and nativity as people age


through the labor market, and we eliminated the depressive effects of African immigrants’ overall wages that newly arrived immigrants create.

In figure 2, we see that Black and white African-born women start out in 1990 with lower earnings than Black and white US-born women, but their earn-ings rapidly increase over the next ten years to actually overtake the earnings of US-born women. The slope of earnings over time for white African-born women is particularly steep, and by 2009, they are earning a great deal more than Black African-born women and all US-born women. Among the US-born, Black women have slightly lower earnings than white women in 1990, and the effects of racial disadvantage continue over time, so that by 2009, the gap between white and Black US-born women has increased. Thus, among women, there are clear privileges associated with nativity, but these privileges only appear as African-born women spend more time in the labor market. Race differences also start out very small though increase over time, creating significant racial gaps by 2009.

In figure 3, we see a different picture among the men. While there are dif-ferences in earnings between African- and US-born men in 1990, as migrants age through the labor force, their earnings converge with US-born men within their racial group, and race becomes the more dominant predictor of earnings. White African-born men have significantly lower earnings than white US-born men in 1990, but their earnings rise rapidly during the next decade and the dif-ference between the two groups becomes statistically insignificant by 2000 and 2009. Conversely, Black African-born men’s earnings rise steeply between 1990

Figure 2. Predicted earnings over time of age cohort 25–34 in 1990 for women by race and nativity (migration cohort, 1980–89; MC = 3).


and 2000, becoming statistically identical to Black US-born men’s earnings in 2009, although they never catch up to those of white men.

Therefore, we found additional support for our prediction that racial dif-ferences would be larger between men than between women. However, among men, there is no benefit to being African-born once variables like age, year of migration, and education are taken into account. The higher observed earn-ings that we saw with white African men in figure 1 is likely a result of having higher education and more experience in the labor market. When controlling for these variables, we do not see differences in men’s earnings over time by nativity; race is the defining status of inequality.

Our findings regarding Black African women’s earnings over time fits the model of African nativity as a source of privilege, but diverges from past studies in which Black African immigrant women are the most disadvantaged in the US labor market. After controlling for human-capital variables, Black African-born women moved from earnings similar to white US-born women (as depicted in figure 1) to surpassing white and Black US-born women. This indicates that Black African-born women experience some sort of advantage conferred by the intersection of their gender, race, and nativity that accounts for their higher earnings than what would be predicted by their human capital. Therefore, we actually see larger nativity advantages among women—with both white and Black African-born women earning more than US-born women—than we see for men.

Figure 3. Predicted earnings over time of age cohort 25–34 in 1990 for men by race and nativity (migration cohort, 1980–89; MC = 3).


Discussion

Our analysis generally supports our theoretical argument that privilege has a magnifying effect. There were significant gender, racial, and nativity earnings gaps between Black and white African- and US-born men and women: race gaps were larger among men; gender gaps were larger among whites; and nativity gaps were larger among white men and smallest among Black women. These findings demonstrate how privilege derived from one social status increases the privilege derived from other social statuses. Despite the fact that narrative analysis has demonstrated that gender and race are different systems of relations that produce vastly different life experiences (for example, the oppression expe-rienced by white US-born women is different from that experienced by Black US- or African-born women), the oppression from those systems of relations produce relatively similar outcomes in earnings across all women. Conversely, with groups that are multiply privileged (namely, white men, either US- or African-born), we see large advantages in earnings.

However, after controlling for education, hours worked, and time in the US labor market, the patterns of inequality diverged by gender. Racial gaps among men remained prominent, but nativity gaps disappeared over time. Among women, privilege derived from being white and African-born continued to significantly shape earnings trajectories, so that by 2009, white African-born women experienced sizeable advantages in their earnings. Surprisingly, Black African-born women, while still earning less than white African-born women, earned more than both white and Black US-born women. Therefore, our model of intersectionality in which privilege has a magnifying effect holds true for observed earnings (what people actually earned), but controlling for human capital accounts for the magnifying effects of nativity privilege for men and increases the nativity privilege for women.

Overall, these findings suggest that the intersection of race and immigrant status operate very differently for women and men. Black African men gain some benefits from their gender, as they had higher predicted earnings than most groups of women. But after controlling for human capital and time in the US labor market, their earnings are identical to Black US-born men, and both groups are disadvantaged compared to whites. By comparison, Black African immigrant women have predicted earnings that are higher than white and Black US-born women, with Black US-born women experiencing the most disadvantage in earnings.

As Margaret Andersen (2005) argues, adding different statuses to the classic gender/race/class intersection can be useful, but it is imperative for researchers to keep in mind how these statuses shape inequality differently than do gender, race, and class. Our findings suggest that nativity is an example of a system of relations that organizes the labor market in ways that can benefit otherwise oppressed groups. We hypothesize that the relative advantage that Black


African immigrant women experience in the labor market is related to the specific labor-market opportunities provided by the structure of African labor migration to the United States. Gender structures the specific labor flows that draw women and men to other countries (Donato and Tyree 1986; George 2005; Hondagneu-Sotelo 2001; Parreñas 2000). The kinds of jobs that Black African immigrant women come to the United States to perform may be giving them some earnings advantages over US-born women in the labor market, provid-ing them with opportunities to outperform what would be predicted by their human capital and race.

Additionally, the particular labor flows into which African immigrant women enter might be selecting Black and white African women in such a way that they outperform US-born women, while the labor flows into which African men enter might reproduce the racial stratification of the male labor market in the United States. This would explain why we found that Black African immi-grant men experienced a racial disadvantage, while race and nativity together produced a more complicated picture for women. Future research that examines the relationships among race/gender/nativity intersections and occupational status would further refine our understanding of how these systems of relations structure individuals’ economic opportunities. Additionally, future research should examine how the educational credentials of African-born men and women affect their earnings in the US labor market—specifically, in terms of foreign versus US-based credentials, and credentials in various disciplines. But overall, these findings suggest that scholars cannot assume that either privilege or oppression is connected to nativity for both women and men, even those from the same region. Thus, additional axes of power cannot just be added to the classical race/class/gender intersections without careful consideration of how they might be differently shaped by gender.

Our findings demonstrate the benefits of conducting quantitative analysis to study intersectionality, as long as such analysis uses a feminist lens. We found clear evidence that having multiple privileged statuses produced a magnification effect, and that differences in earnings among disadvantaged groups were much smaller than the differences among privileged groups. Most striking were our findings on how the effects of race/nativity intersections affected the earnings of men as compared to women. While nearly all groups of men earned more than nearly all groups of women, gender also interacts with race and nativity in ways that together confer benefits to some groups (for example, Black African immigrant women), but provide little benefits to others (Black African immi-grant men). So, while quantitative analysis has not traditionally been a common method used to analyze intersectionality, it clearly has potential for better understanding the effects of multiple privileged and/or disadvantaged statuses within a feminist epistemological framework. Insofar that it also demonstrates some commonalities in the experience of differently oppressed groups (that is, similar depressive effects in wages), quantitative analysis might also be useful


in a political project intended to bring together disparate though still marginal-ized peoples to challenge wage inequality. However, we would caution against the assumption that merely demonstrating how different forms of oppression can leave people similarly situated economically would be enough to develop a broad-based coalition to challenge multiple forms of oppression.

Additionally, our findings exemplify the utility of quantitative methods for using comparisons in intersectional research. For an issue such as wage inequality, which is arguably an important component of oppression, com-parative analysis must be done in order to determine the extent and nature of marginalized women’s earning disadvantages. Oppression does not exist without privilege; thus, while intersectional feminist research should focus on marginal-ized women, some research questions require comparisons to privileged women and men in order to determine how oppression is affecting marginalized women. Therefore, we argue that quantitative analysis like what we have performed here can be a useful component to intersectional theory.

In this article, we used only one outcome, so other outcomes, both eco-nomic and noneconomic, should be examined to determine if the pattern of privilege magnification we have identified is consistent across different out-comes. If other quantifiable outcomes demonstrate the same pattern of privilege magnification, then that will tell us more about how intersecting inequalities shape marginalized women’s life outcomes. And, while it is difficult to conduct complex multivariate analysis with migrants from specific African countries, there is great diversity among African migrants that could be explored among the countries sending the largest numbers of migrants. Such exploration could help us better disentangle the very different outcomes for African immigrant women and men. Additionally, more qualitative research into the migration, educational, and occupational experiences of Black African-born women would be useful in order to understand why racial oppression does not have the same effects on their earnings as it does for Black US-born women and Black African immigrant men.

Stephanie J. Nawyn is an assistant professor of sociology at Michigan State Univer-sity. Her research and teaching areas of expertise are in gender and migration, with a focus on forced migration and the ways that structural inequalities inhibit incorpora-tion. She was a Fulbright Fellow at Istanbul University during the 2013–14 academic year, and has published numerous articles in journals such as American Journal of Public Health; Gender & Society; Journal of Contemporary Ethnography; and American Behavioral Scientist. She was the coeditor (with Steven Gold) of the Routledge International Handbook of Migration Studies (2013). She can be reached at [email protected].

Linda Gjokaj is a visiting assistant professor at Oakland University in Michigan. Her research interests are immigration, gender, and families. She has published in


Journal of Contemporary Ethnography and has chapters in Advances in Gender Research, Diversity in Families, and the Routledge International Handbook of Migration Studies. She recently defended her dissertation, “Albanian Immigrants and Ethnics: Problems of Continuity and Change,” which explores and reexamines the meaning of ethnic distinction and ethnic categories in the everyday lives of one white immigrant and ethnic group. She can be reached at [email protected].

Notes

1. See Julia S. Jordan-Zachery (2007) for an argument on the usefulness of catego-rization in intersectional feminist research.

2. See Judith Stacey’s 1988 feminist critique of ethnography as an example.3. We are careful not to argue that the effects are multiplicative, as we agree with

Candace West and Sarah Fenstermaker (1995) that mathematical metaphors are often misused in intersectional research.

4. While it is possible that individuals, particularly African immigrants, would not self-identify themselves racially given an open-ended response option, the categoriza-tions offered by the US Census Bureau reflect the racial structure prominent in the country at the time of the survey, and thus the categories that individuals chose from the given list can be interpreted as how they see themselves placed (perhaps by others) in that racial structure.

5. In order to keep the age cohorts consistent, we coded the 2009 age cohorts so that they were nine years (rather than ten) apart from the 2000 age cohorts.

6. To keep human-capital variables consistent, we estimated the earnings for people with college degrees working forty hours per week.

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