Intersectionality at Work: Determinants of Labor Supply among Immigrant Latinas

Abstract

This article borrows from the intersectionality literature to investigate how legal status, labor market position, and family characteristics structure the labor supply of immigrant Latinas in Durham, NC, a new immigrant destination. The analysis takes a broad view of labor force participation, analyzing the predictors of whether or not women work; whether and how the barriers to work vary across occupations; and variation in hours and weeks worked among the employed. I also explicitly investigate the extent to which family constraints interact with other social characteristics, especially legal status, in shaping women’s labor market position. Results highlight that immigrant Latinas experience multiple, interrelated constraints on employment owing to their position as low-skill workers in a labor market highly segregated by gender and nativity, to their status as members of a largely undocumented population, and as wives and mothers in an environment characterized by significant work-family conflict.

Latin American immigration to the United States has grown sharply in recent years, with the number of foreign-born Latinos topping 21 million in 2010. As their numbers have grown the prospects for immigrants’ economic incorporation has become an increasingly pressing concern in popular, policy, and academic circles alike. While Latino immigration has long been disproportionately male, a growing number of married and unmarried women have not only entered the country in recent decades, they have also increasingly joined the labor force as well. Indeed, with stagnating male wages in the lower segment of the labor market and the growth of female headed households, women’s employment has become a progressively more important determinant of family economic well-being.

In spite of the importance of these trends, we still know relatively little about the forces shaping employment patterns among immigrant Latinas. Most examinations of immigrant incorporation into the labor market tend to focus on men, and our understanding of the forces that are unique to Latinas remain poorly developed. An important and growing body of work on intersectionality emphasizes that women’s outcomes are not a simple extension of the male experience, and that researchers must explicitly consider how the multiple dimensions of stratification are intertwined (Collins 2000; Crenshaw 1991). While we have made great strides in articulating how forces such as race, social class, and gender shape outcomes simultaneously, nationality and legal status have received far less attention. This is problematic for research on gender stratification and immigrant incorporation alike. Both labor markets and international migration are highly stratified by gender, and powerfully affected by family structures. More work is needed that examines how the intersection between family, the labor market, and immigration status shape the economic incorporation of immigrant women.

Accordingly, this paper examines the determinants of multiple facets of labor supply among immigrant Latinas in Durham, NC, a new immigrant destination. I examine how women’s position in three different institutional spheres structures their labor force participation: the larger political and legal structure, the economy, and the family. I argue that to fully grasp the employment position of immigrant women, it is necessary to take the broadest view possible of labor force participation, considering both whether women work for pay and, among working women, the number of hours and weeks worked. It is also essential to consider multiple aspects of immigration status, economic position, and family structure. Following an intersectionality approach I expect these multiple dimensions to not only cumulatively describe women’s market position but that their interaction will be central to immigrant women’s trajectories. For immigrant Latinas, it is particularly important to examine the nexus between family structure and other social positions, examining differences in the determinants of employment among married and single women and considering transnational dimensions of family life. Results highlight that immigrant Latinas face multiple and intersecting disadvantages owing to their position as largely undocumented entrants into the United States, their concentration in low-wage and unstable occupations, and the particular demands associated with family responsibilities in immigrant Latino communities.

Theoretical Background

Intersectionality theory marks an important advance in feminist scholarship as it moves away from a strictly gendered analysis to one that accounts for the multiple marginalized locations occupied by women from different class and ethno-racial backgrounds. The main argument is that the lived experience of oppression cannot be neatly separated into those due to gender, on the one hand, and race or ethnicity on the other. Rather, they are inherently and intricately linked and experienced simultaneously (Acker 2006; Collins 2000). Moreover, women’s outcomes are structured by the interactions between inequalities in multiple institutions; social class may predominate in the economic sphere but this is also affected by gender inequality in the family sphere.

One way the concept has been invoked is in comparative studies that examine the interaction between such factors as race, gender, and social class. In the field of women’s employment studies show that Latinas face considerable disadvantages compared to both non-Latino white men and women and Latino men (Blau and Kahn 2007; De Jong and Madamba 2001; Hall, Greenman, and Farkas 2010). While this research has made important strides in illuminating the source of inequality between Latinas and others, studies that include diverse populations necessarily lack the ability to delve more deeply into the forces that are unique to particular groups. Thus, these studies often fail to take nativity into account, and even when they do are extremely limited in the information they have available on the immigration experience itself. As such, our understanding of variation among immigrant Latinas remains limited. However, the intersectionality perspective can also be fruitfully applied in single group studies, to delve into the ways that multiple institutions interact to shape the conditions of specific disadvantaged groups (Choo and Ferree 2010). The emphasis on how different spheres of social life simultaneously undermine women’s economic position is especially salient to immigrant Latinas, among whom economic, political, and family characteristics intersect to undermine economic incorporation.

Immigrant women in the U.S. labor market

In recent decades, the United States, like other post-industrial economies, has undergone dramatic transformation of its employment structure. The heightened emphasis on free trade, de-regulation, and flexibility have contributed to rising inequality by skill, and to a substantial erosion of work conditions in the lower segment of the employment hierarchy. Non-standard work arrangements, such as on-call work, temporary help agencies, subcontracting, and part-time employment have all grown dramatically, both across and within industries, to the serious detriment of wages and job quality (Kalleberg 2011).

The declining fortunes in the low-skilled labor market have heightened the demand for immigrant labor. In fact, the share of all workers in the low-skill labor market who were foreign born rose from a mere 12 percent in 1980 (Enchautegui 1998) to 50 percent in 2010 (BLS 2011). Within this larger trend, the demand for female immigrant labor has also grown sharply. Globalization contributed to the exodus of U.S. manufacturing employment to low-income countries, but also to the downgrading of manufacturing that remained. In tandem with the explosive growth of service work and “caring” jobs in child- and healthcare, this has dramatically increased the demand for low-skill immigrant women’s labor (Myers and Cranford 1998).

As the concentration of immigrants in the low-wage market grows, the conditions prevalent in that sector will necessarily loom ever larger in their prospects for socioeconomic advancement. Human capital theory posits that the return to education, work experience, and skill raise the opportunity costs for non-work for highly educated and experienced women. They should thus be more likely to work than their otherwise comparable peers. However, the unique characteristics of the low wage labor market, particularly the segments where immigrant women concentrate, may constrain the role of human capital in shaping employment decisions. Immigrant women are highly segregated in a handful of occupations and industries that are characterized by low wages, small firms, and subcontractors (Catanzarite and Aguilar 2002), and even receive a lower return to skill than other workers (Blau and Kahn 2007). It is therefore important to evaluate whether and how human capital shapes employment decisions among immigrant Latinas, and how aspects of labor market position interact with other institutions to shape employment outcomes.

The legal environment and immigrant women’s work

Immigrant incorporation is also profoundly shaped by the legal and political context of reception. In recent years the consequences of lacking legal authorization to work have grown substantially. The 1986 Immigration Reform and Control Act (IRCA) initiated employer sanctions for the hiring of undocumented workers, and the 1996 Illegal Immigration Reform and Immigrant Responsibility Act (IIRIRA) heightened these sanctions and devoted considerably more resources to enforcement. These laws, and the increasingly harsh anti-immigrant sentiment more generally, have reverberated through the low wage labor market, transforming industries that rely heavily on immigrant labor. In these sectors, the need to insulate employers from the risks associated with hiring undocumented workers has hastened the shift to subcontracting and other forms of non-standard work arrangements, to the detriment of all who work in those fields (Massey and Bartley 2005). Indeed, in the increasingly bifurcated employment structure of more developed economies, it is increasingly nativity and legal status that determine the sorting of workers into the worst jobs (Hudson 2007); in 2005 it was estimated that fully 23 percent of all U.S. low-skill workers were undocumented (Capps, Fortuny, and Fix 2007).

While numerous studies have sought to identify the wage penalty associated with undocumented status (Donato et al. 2008; Flippen 2012; Hall et al. 2010), few, if any, have examined the impact of legal status on women’s labor supply. Because IRCA and IIRIRA were ostensibly aimed at preventing the employment of unauthorized workers, we might expect undocumented women to work at lower rates than their legal resident peers. However, while U.S. immigration law and enforcement patterns have failed to prevent unauthorized employment, they have nevertheless indelibly shaped the pattern of incorporation of undocumented workers. The laws have, in effect, created a differentiated set of workers who face unique structural limitations. It is therefore critical to consider not only the impact of legal status on women’s labor force participation, but also how its influence interacts with structural aspects of the low-wage immigrant labor market. That is, in addition to influencing whether or not immigrant women work, legal status could also shape labor supply indirectly, by funneling women into particular occupations or other employment conditions that undermine their ability to work full time, or in jobs with greater stability.

The family and immigrant women’s labor supply

And finally, the family is another social institution central to immigrant Latinas’ labor supply. Economic theory views labor force decisions as part of the allocation of time between work and leisure. Because women bear disproportionate responsibility for family reproduction, their labor supply decisions are also shaped by the demand for non-market household labor. A wide body of research has shown that women with children are less likely to work than those without children (Cohen and Bianchi 1999; England et al. 2004). The relationship between marriage and women’s employment is less uniform. On the one hand, if husbands encourage a traditional division of labor marriage could undermine women’s paid employment even over and above its association with childbearing. On the other hand, if husbands were to share in childrearing responsibilities, marriage could facilitate women’s employment outside the home. While it is important to recognize the tremendous diversity in gender norms and attitudes both within Latin America and the United States, Latinos are generally thought to be more patriarchal in their family orientations than other groups. For instance, while marriage appears either unrelated or even slightly positively predictive of women’s paid employment for non-Latino white and black women (Christopher 1996), the effect is negative among Latinas (Kahn and Whittington 1996; Read and Cohen 2007).

While prior studies are suggestive of important differences between Latinas and other women, the pan-ethnic label masks potential diversity in experiences across national origin groups. Countries in Latin American vary widely in their family and female employment patterns. In particular, the higher rates of non-marital childbearing and women-centered family arrangements in some Central American countries (Chant and Craske 2003) could contribute to important differences from Mexican women with respect to the relationship between family and market work.

Moreover, it is essential to recognize that the family does not shape women’s employment decisions in a vacuum, but rather its influence interacts with women’s position in other social fields, particularly larger economic and political structures. Immigrant women are concentrated in a handful of occupational niches in the United States, particularly in cleaning, food preparation, factories, childcare, and laundry. The conflict between work and family is likely to differ among occupations; in some jobs (particularly childcare) women are more likely to be able to bring their own children to work, while in others (such as independent house cleaning and laundry) work hours are more flexible and may end before school-aged children are home from school. Different occupations also vary in the extent to which they conflict with sex stereotypes, with work in food preparation and childcare potentially less challenging to patriarchy than work in factories or outside of immigrant niches. It is important to conceive of these decisions, whether or not to work and what kind of job to pursue, as jointly determined to assess the role of human capital, legal status, and family constraints in jointly shaping employment outcomes.

It is likewise critical to consider how family structure interacts with legal status to shape immigrant women’s employment. A burgeoning literature on the impact of migration on gender roles highlights the many obstacles that immigrant women face in translating their greater access to employment and wages into more egalitarian relations within the family. The precarious structural position of undocumented women and men in the U.S. economic and political system undermines women’s ability to leverage economic gains into less patriarchal family arrangements (Deeb-Sossa and Bickham-Mendez 2008; Hondogneu-Sotelo 1994; Menjivar 2000; Parrado, Flippen, and McQuiston 2005; Parrado and Flippen 2005; Schmalzbauer 2009). It is thus critical to examine the interaction between social positions to determine whether some of the apparent family constraints on women’s paid work in fact are tied to other dimensions of disadvantage.

Another important limitation of prior studies is that they fail to account for the transnational nature of family in immigrant households. Specifically, many immigrant women from Latin American left children in the care of other relatives in their countries of origin. The growing trend of migrant mothers globally is transforming the boundaries of motherhood in more traditional societies, to increasingly include economic provision for children (Hondagneu-Sotelo 1997; Parreñas 2005). Thus, while co-resident children in the United States are likely to present demands on their mothers’ time, potentially discouraging market work, non-resident minor children abroad could pose financial demands that encourage women’s work. To my knowledge no one has examined this possibility.

Overall, intersectionality holds the potential to augment our understanding of the social forces shaping immigrant Latina’s economic incorporation, and an in-depth analysis of the multiple and overlapping constraints on immigrant Latina’s employment likewise offers an opportunity to enhance intersectionality theory itself. This paper, which draws on original survey data collected in Durham, NC, takes an expansive view of women’s labor supply. The vast majority of studies on the subject are restricted to analyzing whether or not women work, and neglect considerable variation in the amount of work performed by working women. Here, I model not only whether women were working at the time of survey, but also the number of hours worked in a typical week and a measure of employment instability over the previous year. More importantly, I assess the impact of three different institutional sources of inequality on immigrant Latinas’ paid work - the larger political sphere, the low wage labor market, and the family – and the interaction between them. I show that the impact of legal status and family constraints on women’s work vary across occupations, as well as marked differences in the forces shaping paid work for married and single women. I argue that for immigrant Latinas, the intersection between family structure and legal status is critical for understanding employment outcomes. Implications for intersectionality theory are discussed.

Data and methods

The data used in the analysis come from an original, locally representative survey of Latino immigrants in the Durham/Chapel Hill, NC metropolitan area (for the sake of parsimony, referred to as Durham, where the vast majority of respondents live). Durham represents a valuable vantage point to study Latino immigrant incorporation. The area grew rapidly as part of the national shift in population from Rustbelt to Sunbelt states. The influx of highly educated workers attracted to growing job opportunities in the nearby Research Triangle Park, universities, and other large employers generated intense demand for low-skill service and construction labor. Employers responded by recruiting Latino immigrant laborers from more traditional receiving areas or even directly from Mexico, and a cycle of chain migration began that saw the Latino population surge from a mere 1 percent of the total population in 1990 to 11.9 percent by 2007 (Flippen and Parrado 2012).

The precarious position of Latino immigrants in Durham presented unique challenges for approximating a representative sample. Our study relied on a combination of Community Based Participatory Research (CBPR) and targeted random sampling to overcome these difficulties. CBPR is a participatory approach to research that incorporates members of the target community in all phases of the research process. In our case, a group of 14 community members assisted in the planning phase of the study, survey construction and revision, and devising strategies to boost response rates and data quality. In addition, CBPR members were trained in research methods and conducted all surveys. Finally, through ongoing collaborative meetings, they were also influential in the interpretation of survey results. It is difficult to overstate the wealth of culturally grounded understanding that they brought to project findings (for a detailed description see Berry et al. 2013).

At the same time, the relatively recent nature of the Latino community in Durham rendered simple random sampling prohibitively expensive. We therefore employed targeted random sampling techniques. Based on CBPR insights and extensive field work, we identified 49 apartment complexes and blocks that house large numbers of immigrant Latinos. We then collected a census of all apartments in these areas and randomly selected individual units for interview.² Using community members as interviewers helped achieve a refusal rate of only 9 percent, and a response rate, which also discounted randomly selected units in which contact was not made after numerous attempts, of over 72 percent. Data collection proceeded in stages. An initial survey, which included 209 women between the ages of 18 and 49, was conducted between 2001 and 2002. During 2006 and early 2007, an additional 910 women were interviewed, for a total sample size of 1,119. All interviews were conducted in Spanish, usually in the homes of respondents, with interviewers filling out paper surveys that included a mix of closed- and open-ended questions.

Analytic strategy

The analysis includes multiple aspects of women’s labor supply, including whether or not women engage in paid employment, and if so, how much they work. The first step is thus to assess the determinants of women’s employment, and whether family constraints vary across occupations. I thus model both a dummy indicator of whether or not the respondent was working at the time of survey and a second variable that combines labor force participation with type of occupation. The latter is comprised of seven categories: not working, working in food preparation, cleaning, childcare, laundry, factory, or other jobs. Models are estimated separately by marital status to assess its interaction with social class and legal status.

Second, because immigrant women often work less than full time I also consider variation in labor supply among working women. Specifically, I model the self-reported number of hours worked during a typical week, both among all women and separately by marital status. I also construct a multinomial variable that includes four mutually exclusive categories: not working, working less than 20 hours a week, working between 20 and 34 hours per week, and working 35 hours a week or more. This provides important insight into whether the barriers to immigrant women’s labor force participation produce the largest cleavages between working and non-working women, or whether the main differences are between those who are able to work full time and those who are not. Unfortunately, we did not collect data on the number of hours worked in the first round of surveys, so the sample for these analyses is restricted to the 910 interviewed in the second round of data collection.

The final dependent variable relates to weeks worked. This concept is seldom studied and yet captures a critical aspect of employment in immigrant occupational niches, which tend to be highly unstable. To aid in recollection the survey collected retrospective information separating the prior year into four seasons and asked separately for each whether there was a period of time that respondents were without work, and if so for how long. Responses were then summed to produce a yearly estimate. The survey also included an open-ended question as to the reason for being without work. Responses were coded as those related to childcare (including pregnancy), insufficient labor demand, illness or injury, and other reasons. I therefore model total weeks out of work during the previous year, total weeks out due to childcare, and total weeks out due to insufficient demand. Together these models gauge immigrant Latinas’ vulnerability to employment instability and assess the relative importance of family and labor market sources of instability. This information is not available for the entire sample, but rather was only collected in an employment supplement during the second wave that included 339 women. Once again, models are estimated separately for married and single women to examine the intersection between family structure and other constraints on employment stability.

Independent variables include national origin, age (and a squared term to capture non-linear effects), educational attainment, and work experience in countries of origin as rough measures of human capital. National origin is captured by a dummy variable indicating Mexican origin, with the reference category being Central American. Educational attainment is measured by a set of dummy variables distinguishing between those with 6 or fewer, 7 to 9, and 10 or more years of completed schooling, which correspond to primary, secondary, and above secondary education in Mexico. I also include a dummy indicator for whether women had ever worked in their countries of origin. Immigration-related characteristics include a variable capturing the number of years of residence in the Durham area, and English ability, which is measured by a dummy variable indicating whether the respondent reported being able to speak English well or very well (as opposed to “more or less” or not at all). Finally, a dummy variable for undocumented status reflects the response from a direct question on legal status.

To assess conflict between work and family I include two dummy variables indicate whether a woman is married and whether she has children living in the household. While these variables capture the daily demands for women’s family and childbearing responsibilities, the burgeoning literature on transnational families suggests that we should also consider the impact of non-resident children on women’s labor supply. I therefore also include a dummy indicator for having minor children (under the age of 18) who reside in their country of origin.

And finally, the analysis also includes five mediating employment characteristics on hours and weeks worked among employed women: occupation (described above), firm size (a dummy indicator of whether the respondent was working in a firm with ten or fewer workers at all locations), ethnic concentration (a dummy variable indicating employment at a majority Latino work site), and exposure to nonstandard work arrangements (a dummy indicator of working for a subcontractor). These characteristics have been shown to affect employment stability among men (Flippen 2012).

The statistical estimation varies according to the distribution of the dependent variable. For the analysis of employment where the dependent variable is a dummy indicator I estimate logistic regression models. For the analysis of working in a particular type of occupation or hourly worker category where the dependent variable is composed of mutually exclusive categories I estimate multinomial logit models with the reference category being non-working women. For the model of hours worked per week, which is a continuous variable, I report results from standard OLS models. For the models of variation in weeks without work per year, the large number of cases with zero values warranted negative binomial regression techniques. Comparisons across models estimated separately for single and married women capture the interaction between family considerations and personal, human capital, and immigration related determinants of women’s labor market position.

Descriptive Results

Table 1 presents descriptive results for the dependent variables in the analysis. Just under 58 percent of the sample was working for pay at interview, although there was dramatic variation in the extent of labor market engagement. While the average number of weekly hours worked was just over 35, it ranged from a mere 5 to 60 hours per week. Only 68.6 percent of working women reported working full time (at least 35 hours per typical week), while 21.4 percent reported working between 20 and 34 hours, and an additional10 percent reported working fewer than 20 hours per week. Employment instability during the previous year was also common, with 50.5 percent of working women reporting at least one non-work spell. Ranging from a few days to the better part of the year, the average working woman spent 8.9 weeks without work. The reasons given for being without work point to the importance of both family and labor market sources of instability. While roughly 5 percent of women listed illness or injury as the primary reason they went without work, over 35 percent listed childrearing obligations. However, and even greater share, 48 percent, attributed their time out of work to insufficient demand for their services.

Table 1.

Descriptive statistics

	Mean/Percent	s.d.
Dependent variables
Working at time of survey (%)	57.9
Hours worked per week among working (mean)a	35.6	(9.7)
<20 (%)	10.0
20-35	21.4
35+	68.6
Weeks out of work previous year (mean)b	8.9	(15.0)
% experiencing instability	50.5
Reasons for weeks out (%)
Family	31.2
Underemployment/lack of demand	54.1
Illness	7.3
Other	7.3
Explanatory variables
National Origin (%)
Mexican	70.2
Central American	29.8
Human capital
Age (mean)	29.8	(7.7)
Education (%)
6 years or less	43.6
7-9	26.8
10 or more	29.6
Worked in country of origin (%)	58.5
Immigration characteristics
Years in Durham (mean)	4.3	(3.5)
Good English (%)	7.1
Undocumented (%)	88.3
Family and household structure (%)
Married	80.4
Co-resident minor children	71.9
Non-resident minor child in country of origin	22.2
Employment characteristics
Type of Occupation (%)
Food	29.6
Childcare	5.4
Cleaning	31.9
Laundry	5.9
Factory	11.6
Non-niche	15.6
Subcontractor	8.6
Hispanic worksite	41.3
Small firm	33.3
N	1,119

^aThe analysis of hours work is restricted to 910 women interviewed in the second round of data collection

^bThe analysis of weeks out of work is restricted to 339 women interviewed in a supplement during the second round of data collection

Table 1 also presents human capital, immigration, and family structure characteristics for the sample. Slightly over 70 percent of women in our sample were born in Mexico. The rest herald primarily from Central America, including 17 percent from Honduras, 6 percent from El Salvador, and 4 percent from Guatemala. Like other new destinations, Latina immigrants in Durham are relatively young, averaging 30 years of age. They are also poorly educated, with 43.6 percent not advancing beyond primary school, an additional 26.8 percent completing between seven and nine years of education, and 29.6 percent finishing 10 or more years of schooling. More than 58 percent had prior work experience in their countries of origin. In addition, the vast majority is married or in a consensual union (80 percent) and has children in the household (71 percent). Moreover, a full 22.2 percent had at least one minor child residing abroad. Typical of a new area of destination, respondents are also very recently arrived, averaging a mere 4.3 years in the Durham area. Reflecting this recent arrival, only 7.1 percent reported speaking English well or very well, and the overwhelming majority, 88.3 percent, was undocumented at the time of interview.

And finally, the employment characteristics of women in the sample are also noteworthy. The occupational concentration of immigrant Latinas is extreme, with just over two-thirds working in three areas: cleaning (31.9 percent, which includes private house cleaning and work in hotels or offices), food preparation (29.6 percent), and factory work (11.6 percent). An additional 5.4 and 5.9 percent of women worked in childcare and laundry, respectively. Overall, a scant 15.6 percent of women worked outside of these Latino immigrant niches, in occupations as varied as retail, cosmetology, and construction.

Multivariate Results

While the descriptive statistics described above certainly contribute to the disadvantage of Latino immigrant women relative to other groups, they also demonstrate substantial internal variation. The next set of analyses investigates the social forces undergirding this variation.

Models of labor force participation and occupation

Table 2 reports results from binomial and multinomial logit models predicting the odds of working for pay among all women and by marital status, as well as of being in one of six employment categories relative to not working. Beginning with the pooled model of employment, results in column 1 indicate that Mexican women are significantly less likely to work than their Central American counterparts. Central American, particularly Honduran, women are more likely than Mexicans to have children outside of unions, to have left children in their countries of origin prior to migration, and to have migrated single as opposed to married. All of these factors could contribute to the differences observed across groups. Results also demonstrate surprisingly modest effects of human capital and immigration characteristics on the labor supply of immigrant Latinas. While age is positively associated with employment overall, education, prior work experience in country of origin, and time in the Durham area have virtually no effect. While speaking English well facilitates employment, legal status does not, at least net of other factors.

Table 2.

Binomial and multinomial logit models predicting employment, and employment in particular occupation relative to not working

	Working			Working in particular type of occupation (ref=not working)
		By Marital Status
	All (1)	Single (2)	Married (3)	Food (4)	Childcare (5)	Cleaning (6)	Laundry (7)	Factory (8)	Non-niche (9)
Mexican origin	−0.33** (0.16)	−0.26 (0.43)	−0.36** (0.17)	−0.08 (0.21)	−0.14 (0.41)	−0.36* (0.21)	−0.08 (0.41)	−0.72** (0.29)	−0.67** (0.26)
Human capital
Age	0.24 ** (0.06)	0.27 * (0.16)	0.19 ** (0.08)	0.21** (0.09)	0.38 ** (0.18)	0.24 ** (0.09)	0.26 (0.19)	0.19 (0.13)	0.31 ** (0.11)
Age squared	0.00 ** (0.00)	0.00 * (0.00)	0.00 ** (0.00)	0.00** (0.00)	0.00 * (0.00)	0.00 ** (0.00)	0.00 (0.00)	0.00 (0.00)	0.00 ** (0.00)
Education (ref = 10 years or more)
6 years or less	−0.13 (0.16)	−0.23 (0.50)	−0.12 (0.17)	−0.03 (0.22)	−0.69 (0.44)	0.04 (0.23)	−0.13 (0.40)	−0.09 (0.32)	−0.54 * (0.29)
7-9 years	−0.08 (0.18)	0.18 (0.53)	−0.12 (0.19)	−0.18 (0.24)	−0.17 (0.43)	0.21 (0.24)	−0.58 (0.50)	−0.04 (0.35)	−0.21 (0.30)
Worked in country of  origin	0.09 (0.13)	−0.20 (0.38)	0.13 (0.14)	−0.01 (0.18)	0.16 (0.36)	0.15 (0.18)	−0.05 (0.35)	0.30 (0.27)	0.04 (0.24)
Immigration Characteristics
Time in Durham	0.02 (0.02)	0.15 ** (0.07)	0.01 (0.02)	0.02 (0.03)	−0.10 * (0.06)	0.05 ** (0.03)	0.00 (0.06)	0.03 (0.04)	0.02 (0.04)
Good English	0.70 ** (0.30)	0.11 (0.66)	0.80 ** (0.34)	0.46 (0.40)	1.46 ** (0.64)	0.69 * (0.39)	−0.72 (1.09)	0.13 (0.61)	1.32 ** (0.40)
Undocumented	−0.26 (0.24)	−0.09 (0.58)	−0.39 ** (0.21)	−0.18 (0.32)	1.79 * (1.08)	−0.14 (0.31)	−0.64 (0.58)	−0.48 (0.40)	−0.58 * (0.35)
Family and household structure
Married	−1.08 ** (0.19)	- -	- -	1.20** (0.23)	−0.16 (0.53)	−1.02 ** (0.24)	−0.75 (0.46)	−1.11 ** (0.32)	−1.29 ** (0.28)
Co-resident children	−0.64 ** (0.16)	−1.03 ** (0.43)	−0.56 ** (0.18)	−0.59** (0.21)	−0.50 (0.40)	−0.67 ** (0.21)	−0.42 (0.42)	−0.50 * (0.31)	−0.99 ** (0.27)
Minor non-resident  children	0.37 ** (0.18)	0.64 (0.52)	0.33 * (0.19)	0.38 * (0.23)	0.31 (0.43)	0.46 ** (0.23)	0.56 (0.43)	0.41 (0.32)	0.05 (0.31)
Intercept	−2.33 ** (1.01)	−3.17 (2.45)	−2.70 ** (1.19)	−2.81** (1.38)	−9.99 ** (3.08)	−4.18 ** (1.41)	−4.97 * (2.91)	−3.46 * (2.04)	−4.41 ** (1.80)
Chi-square	131.86	21.71	66.82	205.67
N	1119			1119

^**p<0.05

^*p<0.10

By far the strongest predictors of women’s work relate to family structure, and, not surprisingly, point to a significant conflict between work and family life. Married women are significantly less likely to work than unmarried women; this implies that while on average an overwhelming 87 percent of unmarried women work outside the home, only 55 percent of married women do so. Similarly, having a child in the household is also a strong constraint on employment. Transnational childrearing also significantly shapes employment decisions among immigrant women, though in the opposite direction. Thus, while the daily needs of caring for the children under their roof impede immigrant women’s employment, the financial needs of supporting non-resident children encourage it.

While this model would seem to center the relatively low rates of labor force participation among Latino immigrant women squarely within the realm of family structure, this view masks important interactions between the family and women’s structural position in the U.S. economy and political structure. When we examine the importance of human capital, immigration, and household structure separately for married and unmarried women, and across occupations, clear differences emerge. First, results in columns 3 show that married Mexican women are significantly less likely to work than their Central Americans peers, while the difference is not statistically significant among unmarried women. This pattern reinforces the idea that differences in family regimes, either the stability of marital arrangements or the gendered division of labor, between Mexico and Central America translate into differences in labor force participation after migration. Results from the multinomial model predicting type of occupation likewise show an important interaction with national origin, with Mexican women less likely to be employed in factory and non-niche jobs than Central American women. Immigration policies are a potential sources of these disparities, as Central American (particularly Honduran) women were more likely to have benefited from the Temporary Protected Status (TPS) granted in response political and natural disasters. If this helped some Central American women gain a foothold in more formal employment settings, the benefits could have diffused across social networks to facilitate the access of Central American women, regardless of legal status, to more non-niche jobs.

Human capital, both in terms of educational attainment and work experience abroad, fail to explain women’s work patterns even when disaggregated by marital status and occupation. Thus, not only is there no evidence that better educated women face greater opportunity costs for non-work, there also seem to be few human capital requirements for the occupational niches in which immigrant Latinas work. The only exception is women who did not advance beyond primary school, who are significantly less likely than more educated women to find work outside of immigrant niches.

Immigration characteristics, on the other hand, show important interactions with both marital status and occupation. First, while longer periods of Durham residence enhance work prospects for unmarried women, it has no effect on married women. The opposite is the case for English skills. One possible interpretation of these differences relates to the differential effect of exposure and female autonomy on married and unmarried women’s labor force participation. Unmarried women overall are very likely to be employed, though it generally takes time to find work. Among married women, on the other hand, time and exposure to the Durham labor market alone are less important than obtaining a degree of independence, particularly the ability to communicate in English. Moreover, while the lack of documentation exerts no significant effect on single women’s likelihood of employment, it significantly decreases married women’s labor force participation. Thus, part of the large disparity in employment probabilities between married and unmarried women is indirectly attributable to the dampening effect of being undocumented on married women’s paid work. To illustrate, while the average unmarried woman has an 87 percent probability of being employed, regardless of legal status, the average undocumented married women has only a 53 percent probability of working. Legal resident married women, on the other hand, have a much higher 67 percent probability of employment.

Second, immigration characteristics also have variable effects across occupations. Lengthier time in Durham helps women move out of childcare and into cleaning, a field that typically pays a far higher hourly wage (Hondagneu-Sotelo 2001). English skills clearly facilitate movement into fields that require more interaction with natives, especially childcare, non-niche occupations, and cleaning. More importantly, legal status and occupation interact, with undocumented women significantly more likely to work in childcare and less likely to work outside of Latino niches than their legal resident peers.

Family structure also interacts in important ways with the demands of different occupations. For two job types, childcare and laundry work, marriage and co-resident children have a far more modest impact on employment probabilities, suggesting that work-family conflict is lower in these occupations. This is not surprising for women engaged in childcare, given that many work out of their own homes, caring for their children and the children of other immigrant women simultaneously. For work in laundry flexible scheduling is likely the main factor facilitating employment. Most women in the sample work in either dry-cleaning or coin operated Laundromats, both of which have extended weekday and weekend hours, allowing women to choose shifts that conflict less with family responsibilities.

Hours worked in a typical week

While models of employment offer tremendous insight into the forces shaping immigrant women’s economic incorporation, they fail to address the considerable variation in the extent of market engagement among working women. Accordingly, Table 3 reports results from OLS models predicting hours worked during a typical week among working women, first among all women then separately by marital status (columns 1-3). Among working women, there are few differences in work hours by national origin, human capital, or immigration characteristics. Factors such as age, education, time in Durham, English skills, and legal status do not predict hours worked. Women who worked at origin actually work fewer hours in Durham than those whose first job was in the United States. Similar to the lack of effect for educational attainment, this pattern could reflect the difficulties that women face in transferring their human capital resources to the U.S. labor market. Once again, the most salient predictors of work hours relate to family structure, with married women averaging three fewer hours than their unmarried counterparts. Having children residing in the household is also an important constraint, as co-resident mothers average two fewer hours per week than other women. The importance of women’s structural position in the U.S. labor market is also central to work hours, as those working in childcare and factories average longer work weeks while those in small firms average shorter weekly hours.

Table 3.

Models of hours worked per week among working women

	OLS of hours worked						Multinomial reg. (ref=not working)
			By Marital Status
	All (1)		Single (2)		Married (3)		<20 hours (4)		20-34 hours (5)		35+ hours (6)
National Origin
Mexican	−1.04	(1.04)	1.54	(1.70)	−1.93	(1.29)	0.36	(0.35)	−0.33	(0.26)	−0.33 *	(0.19)
Human capital
Age	0.25	(0.46)	−0.36	(0.71)	0.14	(0.61)	0.17	(0.13)	0.35 **	(0.11)	0.21 **	(0.08)
Age sq	0.00	(0.01)	0.00	(0.01)	0.00	(0.01)	0.00	(0.00)	0.00 **	(0.00)	0.00 **	(0.00)
Education (ref = 10 years or more)
6 years or less	−0.32	(1.11)	−3.16 *	(1.87)	0.56	(1.35)	0.21	(0.34)	−0.24	(0.27)	−0.24	(0.20)
7-9 years	0.15	(1.24)	−1.94	(2.02)	0.44	(1.53)	−0.19	(0.39)	−0.45	(0.31)	−0.22	(0.21)
Worked at origin	−1.98 **	(0.93)	−1.59	(1.50)	−2.02 *	(1.14)	0.38	(0.28)	−0.26	(0.23)	0.00	(0.16)
Immigration Characteristics
Time in Durham	0.14	(0.14)	0.34	(0.23)	0.08	(0.17)	−0.04	(0.05)	0.00	(0.04)	0.05 **	(0.02)
Good English	−0.48	(1.79)	−3.18	(2.48)	−0.44	(2.39)	0.66	(0.69)	0.38	(0.50)	0.68 *	(0.36)
Undocumented	−1.93	(1.58)	−0.15	(2.27)	−3.40 *	(2.06)	0.97	(0.78)	−0.14	(0.41)	−0.24	(0.30)
Family and household structure
Married	−2.91 **	(1.04)	-	-	-	-	−0.24	(0.44)	−1.16 **	(0.30)	−1.37 **	(0.23)
Co-resident children	−1.90 *	(1.06)	1.69	(1.70)	−2.73 **	(1.34)	−0.18	(0.34)	−0.80 **	(0.27)	−0.64 **	(0.20)
Non-resident child	0.14	(1.13)	3.97 **	(1.77)	−1.38	(1.40)	0.32	(0.35)	0.09	(0.29)	0.51 **	(0.21)
Employment characteristics
Occupation (ref = food preparation)
Childcare	4.31 **	(2.05)	−5.66	(4.37)	6.83 **	(2.36)
Cleaning	0.91	(1.10)	−1.60	(1.73)	1.69	(1.38)
Laundry	2.88	(2.09)	1.64	(4.28)	3.35	(2.40)
Factory	4.85 **	(1.62)	0.32	(2.60)	6.05 **	(1.98)
Non-niche	1.52	(1.64)	3.85	(2.51)	0.35	(2.07)
Labor market position
Subcontractor	0.42	(1.31)	−1.53	(2.04)	1.14	(1.65)
Hispanic worksite	0.01	(1.00)	1.40	(1.56)	−0.29	(1.25)
Small firm	−3.54**	(1.02)	−2.08	(1.64)	−4.54 **	(1.26)
Intercept	38.23 **	(7.43)	44.18 **	(11.72)	39.53 **	(9.89)	−5.93 **	(2.26)	−5.28 **	(1.82)	−2.06 *	(1.24)
R/Chi-squared	0.09		0.16		0.12		147.55
N	542		145		397		910

^**p<0.05

^*p<0.10

As with the model of labor force participation, there are important interactions between marital status and other determinants of work hours. While co-resident children do not significantly lower hours among unmarried women, married co-resident mothers average three fewer hours per week than other women. The opposite pattern is evident for transnational children, who are associated with a four hour longer work weeks among unmarried women but do not predict work hours among married women. Likewise, while legal status does not predict work hours overall, it is associated with a 3.5 hour shorter work week among married women. And finally, the effects of employment characteristics, such as working in small firms, childcare, and factory occupations, shape work hours among married but not unmarried women.

Table 3 also presents results from a multinomial logistic regression distinguishing between non-working women (reference) and women working fewer than 20 hours per week, between 20 and 34 hours, and full time (more than 35 hours) (columns 4-6). Overall the largest differences are seen between women who work full time and others, rather than between non-working women and others. For instance, women working less than 20 hours per week were statistically indistinguishable from those who did not work at all. Likewise, while older women and those who are unmarried or without children are more likely to work intermediate hours relative to not working, there are no other differences between intermediate hours and non-work. The model of full time work, in contrast, shows that in addition to age, marital status, and co-resident children, a number of immigration and other family structure characteristics are also significant. In particular, both time in Durham and good English skills encourage full time work, as does having children in women’s country of origin. Mexican women also vary from Central American women in their propensity to work full time.

Weeks without work during the previous year

While the number of hours worked per week is an essential aspect of women’s labor supply, it is also important to assess the considerable variation in the number of weeks worked over the course of the year. Table 4 presents results from negative binomial regression models predicting the total weeks out of work during the previous year, and the number of weeks without work that were attributed specifically to insufficient demand and family responsibilities³ separately.

Table 4.

Negative Binomial models of weeks out of the labor force previous year

Weeks out due to:	Any reason						Slack demand		Childcare
			By Marital Status
	All (1)		Single (2)		Married (3)		(4)		(5)
Mexican origin	0.04	(0.38)	−1.49	(1.40)	−0.22	(0.46)	−0.80	(0.63)	0.36	(1.46)
Human capital
Age	−0.23	(0.16)	1.17 **	(0.57)	−0.24	(0.21)	−0.31	(0.31)	0.30	(0.61)
Age sq	0.00	(0.00)	−0.01 *	(0.01)	0.00	(0.00)	0.01	(0.00)	−0.01	(0.01)
Education (ref = 10 years or more)
6 years or less	−0.10	(0.43)	2.66 *	(1.46)	−0.55	(0.50)	−0.16	(0.77)	1.82	(1.73)
7-9 years	0.12	(0.49)	1.70	(1.63)	−0.09	(0.54)	0.57	(0.76)	0.92	(1.88)
Worked at origin	−0.73 **	(0.37)	0.07	(1.06)	−0.48	(0.45)	−0.61	(0.65)	−2.50 **	(1.27)
Immigration Characteristics
Time in Durham	−0.14 **	(0.05)	−0.24 *	(0.15)	−0.10 *	(0.06)	−0.01	(0.09)	−0.53 **	(0.27)
Good English	0.04	(0.75)	1.01	(1.71)	−0.57	(0.91)	−2.20	(1.49)	1.00	(3.60)
Undocumented	0.24	(0.60)	3.30 *	(2.02)	0.20	(0.83)	4.42 **	(1.44)	0.00	(3.44)
Family and household structure
Married	0.04	(0.47)	-	-	-	-	1.29	(0.80)	−0.28	(1.75)
Co-resident children	0.93 **	(0.48)	−0.39	(1.35)	0.79	(0.65)	−0.56	(0.82)	-	-
Non-resident child	0.55	(0.41)	−0.24	(1.33)	0.86	(0.55)	0.67	(0.81)	−1.59	(1.47)
Employment characteristics
Occupation (ref = food preparation)
Childcare	−0.99	(0.76)	-	-	−0.57	(0.80)	0.37	(1.11)	−1.61	(2.24)
Cleaning	−0.49	(0.48)	−1.54	(1.46)	−0.07	(0.52)	−0.46	(0.70)	−0.34	(1.31)
Laundry	−2.87 **	(0.80)	−2.68 *	(1.65)	−3.45 **	(1.06)	−2.91 **	(1.34)	−3.21	(2.27)
Factory	0.57	(0.59)	−0.69	(1.93)	0.82	(0.77)	0.59	(1.06)	1.75	(1.89)
Non-niche	0.71	(0.65)	−0.13	(1.41)	0.99	(0.75)	−0.69	(0.97)	−2.11	(1.65)
Labor market position
Subcontractor	−0.05	(0.55)	-	-	-	-	0.47	(0.90)	-	-
Hispanic worksite	0.52	(0.39)	2.19 **	(0.98)	0.14	(0.51)	−0.19	(0.76)	2.93 **	(1.48)
Small firm	0.71 *	(0.40)	−0.30	(1.27)	0.81 *	(0.42)	0.85 *	(0.49)	-	-
Intercept	5.15 *	(2.72)	−24.27 **	(10.69)	6.10 *	(3.33)	0.89	(5.06)	−0.62	(11.16)
Alpha	4.74 **	(0.60)	2.83 **	(0.83)	4.58 **	(0.65)	9.30 **	(1.51)	17.46 **	(4.04)
Chi-Squared	28.07		22.76		25.77		26.79		18.47
N	216		48		168		216		167

^**p<0.05

^*p<0.10

With respect to total weeks out of work during the previous year, there are once again few human capital or immigration characteristics that predict this element of labor supply. Thus, in Durham’s highly segmented immigrant labor market, better educated working women seem no more insulated from employment instability than their less educated peers, even when focusing on demand-related spells without work. Women with longer residence in Durham, on the other hand, did experience significantly less time without work than other women, net of other factors. However, Durham experience seems to alter the relationship between family constraints and employment stability rather than improve labor market prospects, since it is negatively associated with time out of work due to childcare but not time out due to insufficient demand. Work demand is steadiest in laundry occupations, which is the only occupation to average significantly fewer weeks of non-work than food preparation. Small firms, on the other hand, are associated with more weeks without work, particularly due to low demand.

Overall, results in column 1 suggest no relation between legal status and employment instability. However, this simplistic view misses the intersection between legal status and both the reason for missed work and marriage. Results in column 2 show that lack of documentation is particularly detrimental among unmarried women. However, this is largely because it is unmarried women who most clearly demonstrate the impact of slack demand on employment instability (as their work patterns are less clouded by additional time out due to childcare). Consistent with this interpretation, when results are examined separately by the reason for instability, we see that while legal status has no effect on time without work due to childcare, being undocumented powerfully predicts being without work due to slack demand. Models estimated separately by marital status (not reported) show that the effect is present among both married and unmarried women. In fact, the relationship between undocumented status and employment instability due to slack demand is so strong that it is difficult to estimate reliable parameters with our relatively small sample; only one documented woman in the whole sample reported time out of work due to slack demand. While greater variation might be evident with larger samples, the powerful intersection between documentation and employment instability highlights the impact of structural position on immigrant women’s employment.

And finally, results from the model predicting time out due to childcare are also instructive. Aside from the obvious relationship between the presence of children and time out of work due to childrearing responsibilities, family structure exerts little influence over employment instability. In addition to time in Durham, having work experience in their country of origin is associated with lower likelihood of time out of work due to childcare.

Conclusions

This paper applies intersectionality theory to the employment experiences of immigrant Latinas. Drawing on an original survey specifically designed to capture the legal, employment, and family characteristics most germane to immigrant women, the analysis takes an expansive view of labor supply, considering not only whether women work, but also in what occupations, as well as variation in the hours and weeks worked among the employed. It also takes a transnational view of the family, considering the impact of both co-resident children in Durham and non-resident children in respondents’ country of origin. More importantly, it explicitly considers not only the cumulative impact of each source of immigrant women’s disadvantage, but also the interaction between them, addressing whether and how human capital, legal status, and family constraints on women’s work vary across occupations, and how family structure interacts with structural conditions to bound immigrant Latina’s employment opportunities.

Results, summarized in Table 4, demonstrate numerous ways in which Latino immigrant women’s position in the overall economy constrain their labor supply. In the occupational niches in which immigrant women in Durham concentrate there are few signs that human capital is a significant determinant of labor force participation. While older women are more likely to work, are more often engaged in the labor market full time, and average fewer weeks of non-work over the course of the year than their younger counterparts, education has virtually no effect on employment probabilities or work effort among the employed. Among human capital and immigration characteristics it is primarily English language ability and time in Durham that shape immigrant women’s labor supply. Those with better English skills are more likely to work overall and to work full time, and are also more likely to procure jobs in childcare and non-niche occupations, which entail more interaction with non-immigrants. Women with longer tenures in Durham are also more likely to work full time, and are better able to move out of childcare and into cleaning, which pays a higher hourly wage. However, while they also spent less time out of the labor market over the previous year, it is primarily because they spent fewer weeks attending to children rather than because they were more successful at avoiding idleness due to slack labor demand.

The disadvantage associated with immigrant Latinas’ position in the legal system is also clearly evident. While undocumented women are no less likely to work overall than their legal resident peers, their employment opportunities are significantly curtailed in other ways. First, lack of documentation blocks women’s entry into non-niche occupations, where pay is often higher and work tends to be more stable, instead pushing them into childcare, where the opposite is true. Second, undocumented women also experience greater employment instability and time out of work during the previous year than their legal resident counterparts. Moreover, the impact on weeks without work is evident only for reasons relating to insufficient labor demand, and not to those pertaining to childrearing. Given the economic need of the families in which immigrant women are embedded, the numerous, sizeable impediments to stable, full time employment are a cause for serious concern. While employment conditions improve with age and time in the local labor market, the effects are relatively modest and suggest sustained disadvantage over the course of women’s lives

Results also demonstrate the profound limits to employment posed by immigrant Latinas’ family structure. Both marriage and childrearing exert independent negative effects on women’s employment. Indeed, marriage itself seems to be as large, if not a larger, impediment to work as co-resident children. Married women and those with co-resident children are not only less likely to work, they also work fewer hours per week and experience significant family-related inactivity over the course of the year. However, the effect of children on women’s employment does not end with those who are living in the household. It is important to acknowledge transnational aspects of family and childrearing; women with minor children abroad are more likely to work than other women, even net of household structure in Durham. This finding adds to a growing literature on transnational families that suggests that migration is expanding the boundaries of motherhood to include not only caring work but also financial provision (Hondagneu-Sotelo 1997; Parreñas 2005). Taken together, these findings support the need to take a broad view of the family when considering immigrant women’s work experiences. Both gender roles and family arrangements are profoundly altered through migration, and a deeper understanding of immigrant women’s work requires greater attention to the nexus between the family and other structures.

While each of these domains taken separately provide valuable insight into the complex employment patterns of immigrant Latinas, results also indicate significant intersection between structural constraints. One of the most consequential interactions is between marital and legal status. Married women are not simply less likely to work than their unmarried counterparts; their labor force participation is also more sensitive to legal status. These patterns temper our view of the Latino (particularly Mexican) family as a patriarchal constraint on women’s paid employment, and shifts the emphasis to the structural conditions affecting Latinas in the U.S. labor market. In fact, the interaction between legal and marital statuses substantially widens the employment gap that stems from family constraints; while the difference in labor force participation between married and unmarried legal residents is 20 percent, it is 34 percent among undocumented women. Thus, failing to account for the intersection between legal and marital status overstates the negative effect of marriage on immigrant Latinas’ employment, a finding that is overlooked in studies that treat family and legal contexts as separate domains.

There are also important interactions between immigrant Latinas’ human capital and family characteristics and structural conditions in the low-wage labor market. While documentation does not impede work overall, it does channel women into childcare and raises significant barriers to non-niche employment. Moreover, the conflict between work and family is not uniform across occupations. Childcare and laundry work, in particular, stand out as posing fewer barriers to work for women who are married or with children. While most of the niches in which immigrant Latinas are concentrated could be considered “women’s work,” and thus represent more modest challenges to patriarchy than work in male-dominated fields, childcare and laundry work are unique in their ability to accommodate young children at work and long hours of operation, respectively, which seem to mitigate the impact of family responsibilities on market work.

A number of caveats are in order. First, our relatively small sample size warrants caution when interpreting results. The limited variation in legal status and English language ability among this recently arrived population prevents strong conclusions about their lack of effect on some employment outcomes. Second, these findings were obtained from a case study of Durham, NC and are not necessarily generalizable to all low-skill Latino immigrants living in the United States. However, there is reason to believe that they may be applicable to other new destinations, particularly in the Southeast. While cities like Charlotte, NC and Atlanta, GA, and Durham differ somewhat in their industrial compositions they have all grown dramatically in recent decades in their native populations, with attendant growth in demand for low-skill services and sharp rise in Latino immigrant populations after 1990. Moreover, the degree of concurrence between the quantitative findings presented above and the conclusions drawn from ethnographic and other qualitative studies is striking, even though the latter have focused overwhelmingly on more traditional receiving areas.

Thus these findings add to works with diverse methodologies in demonstrating the utility of intersectionality for understanding immigrant Latinas’ employment patterns. Intersectionality theory challenges us to look beyond social categories as mere demographic variables and recognize that the impact of one social location is indelibly linked to others. The literature on immigrant adaptation would benefit from more direct engagement with this approach; immigrant Latina’s experiences in the labor market cannot be understood without considering the multiple and intersecting sources of disadvantage stemming from their position in a highly segmented labor market, as immigrant and undocumented workers, and in families in which wives and mothers shoulder a disproportionate share of the burden of household reproduction. Findings also hold implications for intersectionality theory itself. While the nexus between race, class, and gender has begun to receive the research attention it richly deserves, comparable work on how nativity and legal status intersect with other domains has not kept up with the growth in its importance. The contemporary period has been dubbed the “age of migration,” with more than 200 million people living outside their countries of origin; virtually no part of the globe has been untouched by migration in recent decades, and with growing bifurcation in post-industrial economies, immigration status has taken on outsized importance in employment outcomes worldwide. Greater attention to how gender, race, and class intersect with national origin, legal status, and context of immigrant origin and reception, including migration-related changes to family structure, would enhance our understanding of the unequal power relations that underlie the social position of women of color more generally.

Table 5.

Summary of main findings

	Working			Hours Worked			Weeks without work
	All	Single	Married	All	Single	Married	All	Slack demand	Child- care
Mexican origin	−	0	−	0	0	0	0	0	0
Human capital
Age	+	+	+	0	0	0	0	0	0
Age squared	−	−	−	0	0	0	0	0	0
Education (ref = 10 years or more)
6 years or less	0	0	0	0	−	0	0	0	0
7-9 years	0	0	0	0	0	0	0	0	0
Worked in country of origin	0	0	0	−	0	−	−	0	−
Immigration Characteristics
Time in Durham	0	+	0	0	0	0	−	0	−
Good English	+	0	+	0	0	0	0	−	0
Undocumented	0	0	−	0	0	−	0	+	0
Family and household structure
Married	−			−	0	0	0	0	0
Co-resident children	−	−	−	−	0	−	+	0
Minor non-resident children	+	0	+	0	+	0	0	0	0
Employment characteristics
Occupation (ref = food preparation)
Childcare				+	0	+	0	0	0
Cleaning				0	0	0	0	0	0
Laundry				0	0	0	−	−	−
Factory				+	0	+	0	0	0
Non-niche				0	0	0	0	0	0
Labor market position
Subcontractor				0	0	0	0	0
Hispanic worksite				0	0	0	+	0	+
Small firm				−	0	−	+	+