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Abstract

Immigrants constitute nearly one third of science, technology, engineering, and mathematics (STEM) degree holders in the United States, yet their contributions to diversifying the U.S. STEM workforce are often overlooked. The author examines disparities in the likelihood of holding a STEM degree among college graduates, considering the intersections of race/ethnicity, gender, and immigration status. The analyses reveal that immigrant men and women from all non-White racial/ethnic groups are equally or more likely than their U.S.-born White counterparts to hold a STEM degree. However, compared with the U.S.-born, race/ethnicity and gender disparities are more pronounced among immigrants, particularly the 1.25th generation: those who earned a college degree in the United States after completing K–12 education in their countries of birth. The findings of this study underscore the limitations of social interventions that have narrowly focused on U.S.-born individuals in efforts to foster a more diverse and inclusive STEM workforce.

Keywords

STEM race gender immigration 1.25th generation

Developing and diversifying the science, technology, engineering, and mathematics (STEM) workforce has been a federal priority in the United States, driven by the recognition that technological innovation is essential for long-term economic growth and national security (Holloman et al. 2018; Kuenzi 2008). Individuals holding STEM degrees have had more stable employment and higher earnings compared with those without STEM degrees (Kim, Tamborini, and Sakamoto 2015; NSB 2022). Despite the growing socioeconomic importance of STEM education at both the national and individual levels, racial/ethnic minorities and women continue to be underrepresented among STEM degree holders (Carter, Razo Dueñas, and Mendoza 2019; NCSES 2023).

Large-scale scholarly and policy efforts to diversify the U.S. STEM workforce have focused on addressing the inequitable development of STEM skills and interests through K–12 education, particularly among U.S.-born individuals (Legewie and DiPrete 2014; Tyson et al. 2007; Xie, Fang, and Shauman 2015). However, relatively less attention has been given to the growing impact of immigration on U.S. STEM workforce development, despite a large number of foreign-born STEM students and workers coming to the United States after completing their K–12 education in their birth countries (American Immigration Council 2022; Hanson and Slaughter 2016; Jacobs 2022; Lindsay Lowell and Martin 2012; Varma 2020). In 2017, international students in the United States earned 22 percent of bachelor’s degrees, 54 percent of master’s degrees, and 44 percent of doctorates awarded in STEM fields (Granovskiy and Wilson 2019).

The aim of this study is to contribute to the existing literature by delineating the disparities in the probability of holding a STEM degree among college graduates on the basis of their race/ethnicity, gender, and immigration status, with a particular focus on “STEM immigration.” In this study, STEM immigration refers to the growing influx of foreign-born individuals who pursue STEM degrees or careers in the United States, which has been facilitated by widening access, particularly for STEM degree holders, to both temporary and permanent immigration opportunities, such as optional practical training (OPT), H-1B visas, and lawful permanent residence (LPR) (Wasem 2012). The rise of STEM immigration, which began in the 1960s and accelerated in the 1990s, continues to shape the landscape of the U.S. STEM workforce (Granovskiy and Wilson 2019; Lindsay Lowell 2010). STEM immigration carries substantial social and theoretical implications for several reasons.

Public media often emphasize negative portrayals of immigrants, often framing them in ways that suggest criminality or threat (Farris and Silber Mohamed 2018). These biased representations may reinforce undesirable stereotypes and discrimination, impeding progress toward greater diversity and inclusion in the United States (Conzo et al. 2021; Esses, Medianu, and Lawson 2013). Research on STEM immigration is expected to shed light on one of the critical areas where immigrants have made substantial positive contributions to the economic growth of the United States.

Moreover, the share of immigrants in the U.S. STEM workforce has continued to increase. Federal legislators have sought to meet the domestic demand for STEM workers by recruiting foreign-born individuals with high levels of STEM skills and interest (Kuenzi 2008; Wasem 2012). However, policymakers and researchers have rarely examined how this population relates to diversity and inclusion in the U.S. STEM workforce. For example, federal reporting guidelines still require postsecondary institutions to categorize international students into a single category, disregarding their racial/ethnic heterogeneity. This approach fails to reflect the reality of higher education, where U.S.-born and international STEM students increasingly interact and shape the campus climates together (NCES 2023a). It has become nearly impossible to foster diverse and inclusive campus climates for STEM education without considering the experiences of both U.S.-born individuals and immigrants. The implications of STEM immigration for diversity and inclusion in the U.S. STEM workforce will further extend across generations, as immigration is a life-altering event with intergenerational intentions and consequences (Farley and Alba 2002; Foner and Dreby 2011; Tilbrook and Shifrer 2022).

Theoretically, close examinations of the intersections of race/ethnicity, gender, and immigration, particularly in the context of STEM immigration, can reveal how racialized and gendered disparities in socioeconomic outcomes within the United States are interconnected with global social structures. Portes (1995) asserted that the field of immigration serves as a “strategic research site,” revealing “processes of more general import manifested with unusual clarity” (p. 2). Furthermore, Sáenz and Manges Douglas (2015) emphasized the need to focus on the racialization of immigrants, particularly in recent decades. This research on STEM immigration seeks to deepen our understanding of the racialization of immigration and the heterogeneity in immigrants’ socioeconomic outcomes by analyzing variations on the basis of their places of birth and education (Kim and Sakamoto 2010; Zeng and Xie 2004).

The analysis finds that immigrants constitute nearly one third of STEM degree holders in the United States. College-educated immigrant men and women from all non-White racial/ethnic groups are as likely as, or more likely than, their U.S.-born White counterparts to hold a STEM degree. However, compared with U.S.-born individuals, race/ethnicity and gender disparities in the likelihood of holding a STEM degree are significantly wider among immigrants, particularly within the 1.25th generation: those who earned a college degree in the United States after completing K–12 education in their countries of birth. This study further reveals variations according to country of birth and place of education. The findings underscore the limitations of social interventions that have narrowly focused on U.S.-born individuals in efforts to foster a more diverse and inclusive STEM workforce. This research calls for greater attention from researchers and policymakers to STEM immigration and its growing impact on the development of the U.S. STEM workforce.

Literature Review

Race/Ethnicity and Gender Representation in the U.S. STEM Workforce Development

Racialized pathways are evident throughout the educational pipeline of the U.S. STEM workforce. Racial/ethnic minorities—particularly Black, Hispanic (or Latinx), and American Indian or Alaska Native individuals—are underrepresented in postsecondary STEM education (Chen and Soldner 2013; NCSES 2023; NSB 2022). The racial/ethnic disparities in postsecondary STEM education have been attributed to inequitable opportunities to acquire precollege STEM-related skills, which are measured by math and science course taking or test scores at the K–12 level (Wang 2013; Xie et al. 2015). Racial/ethnic achievement gaps in K–12 education are linked to structural barriers, including disparities in school quality and resources outside of school, such as family income (Condron and Roscigno 2003; Downey 2008; Kao and Thompson 2003).

The U.S. STEM workforce development also exhibits gendered pathways. Despite women’s advancements in educational attainment, they remain underrepresented in STEM fields, particularly in engineering, physical sciences, mathematics, and computer science (Charles and Bradley 2002; NCSES 2023; Xie and Shauman 2003). Gender representation in STEM education is attributed to gender disparities in STEM-related interests, which persist from K–12 to postsecondary education (Legewie and DiPrete 2014; Sadler et al. 2012). Research highlights the significant role of gendered cultural conditioning and norms, such as the “math = male” stereotype, in perpetuating gender gaps in STEM interests (Kiefer and Sekaquaptewa 2007; Nosek, Banaji, and Greenwald 2002).

In short, prior research has shown that the underrepresentation of racial/ethnic minorities and women among STEM degree holders primarily stems from the unequal development of STEM skills and interests within the U.S. K–12 education system. However, researchers and policymakers have often overlooked the rising influx of immigrant STEM students and workers, as well as their impact on the racial/ethnic and gender composition of the U.S. STEM workforce. As a considerable number of immigrant STEM students and workers completed their K–12 education in their countries of origin, existing explanations that focus on the U.S. K–12 system have limitations in addressing the persistent underrepresentation of women and racial minorities. This study seeks to fill that gap by integrating the concept of STEM immigration into discussions of race/ethnicity and gender representation in the U.S. STEM workforce.

The following sections first examine how the rise of STEM immigration has been socially constructed in recent decades and then outline hypothetical intersections of race/ethnicity, gender, and immigration status in STEM workforce development, on the basis of a synthesized review of existing literature on both STEM education and immigration.

The Rise of STEM Immigration

As the world’s largest destination for international migration, the United States received more than 1 million immigrants intending to stay long term or permanently in 2019 alone (OECD 2022b). The United States also attracts the largest number of international students worldwide, accounting for approximately 18 percent of the total international student population (NSB 2022). In 2017, 49 percent of international students in the United States pursued a STEM major. The number of foreign-born STEM workers more than doubled from 2000 to 2019, reaching 2.5 million (American Immigration Council 2022).

The United States has adapted its economic, educational, and legislative institutions to accommodate the large influx of foreign-born individuals pursuing STEM degrees or careers. Although the United States leads the world in research and development (R&D) investments, U.S. eighth graders score lower in math and science tests than students in many other countries with similar levels of economic growth (NSB 2022). U.S. policymakers remain concerned that the domestic supply of STEM workers may fail to meet the business sector’s demand (Gonzalez and Kuenzi 2012; Granovskiy 2018). Thus, while continuing efforts to improve K–12 STEM education for U.S.-born adolescents, the U.S. government has broadened immigration avenues for highly skilled STEM immigrants to promote national economic growth (Granovskiy and Wilson 2019; Lindsay Lowell 2010; Wasem 2012).

Furthermore, the world-renowned quality and prestige of U.S. universities have made the United States an attractive destination for foreign-born students interested in STEM education (Davis et al. 2023; Granovskiy and Wilson 2019; NSB 2022). U.S. universities actively recruit elite international STEM students to maintain their global competitiveness and increase tuition revenue (Granovskiy and Wilson 2019). The reciprocal relationship between U.S. postsecondary institutions and foreign-born individuals will likely continue to increase the inflow of international students seeking STEM degrees in the United States. Thus, while policymakers in many other countries are concerned about the brain drain of highly skilled individuals migrating to the United States (Docquier, Lohest, and Marfouk 2007; Gibson and McKenzie 2011), U.S. policymakers worry about the reverse brain drain of U.S.-trained STEM individuals returning to their home countries (Davis et al. 2023; Jacobs 2022; Johnson 2002; Lindsay Lowell and Martin 2012; Wadhwa 2009).

A series of recent amendments to U.S. immigration law has aimed to prevent the reverse brain drain and encourage foreign-born STEM students and workers to remain in the United States permanently (Amuedo-Dorantes, Furtado, and Xu 2019; U.S. Citizenship and Immigration Services 2024; Wasem 2012). The Immigration Act of 1990 played a critical role in this regard by increasing the annual number of available visas for foreign-born individuals, expanding the categories of employment-based immigration visas, and relaxing admission requirements, particularly for those holding STEM degrees (Lindsay Lowell 2010; Ransom and Winters 2021). For instance, foreign-born students studying full-time in U.S. postsecondary institutions enter the United States with F-1 nonimmigrant visas. F-1 students are not permitted to work in the United States before graduation; however, they can take advantage of OPT after completing their degrees, which allows them to work for 12 months in a field closely related to their area of study (Demirci 2019; Wasem 2012). During the OPT period, foreign-born workers may apply for either H-1B visas, which are for individuals engaged in specialty occupations, or LPR (Amuedo-Dorantes et al. 2019). The U.S. Department of Homeland Security announced OPT extensions of 17 months in 2008 and 24 months in 2016 for STEM degree holders only (Granovskiy and Wilson 2019). According to Wasem (2012: 16), the so-called STEM visa has expedited the immigration pathway for foreign nationals with STEM degrees, allowing them to adjust their status to LPR without waiting in line for numerically limited LPR visas.

Thus, in this study, STEM immigration refers not merely to the pursuit of a STEM degree by foreign-born individuals, but to a broader, structured pathway through which STEM education and employment in the United States facilitate long-term or permanent immigration outcomes. This pathway includes the transition from F-1 student status to OPT, the acquisition of H-1B visas for specialty occupations, and ultimately, LPR. Accordingly, the concept of STEM immigration encompasses the educational and occupational dimensions of high-skilled migration, offering a framework for understanding how U.S. immigration and education policies converge to shape the STEM workforce. Through the interplay of economic, educational, and legislative institutions, the rise of STEM immigration is expected to continue supporting the expansion of the U.S. STEM workforce.

Race/Ethnicity, Gender, and Immigration Status in the U.S. STEM Workforce Development

The process of immigration varies under the influence of social contexts. Immigrants in the United States tend to encounter limited opportunities for educational and economic attainment, with racial/ethnic minorities and women disproportionately affected (Pedraza 1991; Sáenz and Manges Douglas 2015; Waters and Eschbach 1995). Additionally, the location of education differentiates the assimilation processes and socioeconomic outcomes of immigrants (Kim 2015; Kim and Sakamoto 2010; Shao 2023; Zeng and Xie 2004). Zeng and Xie (2004) and Shao (2023) documented that Asian immigrant workers who received their education overseas faced severe disadvantages in the labor market compared with their counterparts educated in the United States. They explained that U.S. employers undervalue education attained outside the country.

Kim and Sakamoto (2010) and Kim (2015) further divided college-educated immigrants into three groups: the 1.5th generation (those who completed both secondary and postsecondary education in the United States), the 1.25th generation (those who completed secondary education in their birth countries and postsecondary education in the United States), and the 1st generation (those who completed both in their birth countries). Unlike traditional assimilation theory, which assumes a linear process of cultural and social integration, they demonstrated that the 1.25th generation’s socioeconomic outcomes—such as the level of the highest degree attained, type of college, field of study, and earnings—do not necessarily fall between those of the 1.5th and 1st generations. The empirical results highlight the importance of distinguishing the 1.25th generation from the other two immigrant groups.

More specifically, for immigrants who have the opportunity to pursue higher education, seeking a STEM degree can be a strategic choice to address their limited opportunities in immigration processes and socioeconomic advancement. Individuals with bachelor’s degrees in STEM fields have higher lifetime earnings than those in other fields of study (Kim et al. 2015; NSB 2022). Although the financial benefits of holding a STEM degree are attractive to both U.S.-born individuals and immigrants, U.S. immigration laws that favor foreign-born individuals with STEM skills and interests provide additional advantages to immigrants seeking a STEM degree (Amuedo-Dorantes et al. 2019; Wasem 2012). Possessing a STEM degree expedites the process of obtaining LPR status or U.S. citizenship for immigrants.

Legal naturalization on the basis of a STEM degree is more imperative for 1.25th- and 1st-generation immigrants compared with 1.5th-generation immigrants, whose naturalized citizenship or LPR status often stems from their parents. Additionally, the STEM immigration process is more effective for 1.25th-generation immigrants than for 1st-generation immigrants, whose STEM degrees earned in their birth countries are undervalued in the U.S. labor market and immigration processes (Shao 2023; Wasem 2012; Zeng and Xie 2004). Furthermore, recent changes to U.S. immigration law have played a role in reducing return migration among immigrants holding a STEM degree (Amuedo-Dorantes et al. 2019). As a result, college-educated immigrants, particularly those in the 1.25th and 1st generations, are more likely to hold STEM degrees than their U.S.-born counterparts.

Further attention needs to be paid to the potentially heightened barriers faced by racial minorities and women in the STEM immigration process. Previous studies focusing on U.S.-born individuals indicate that the lower probability of racial/ethnic minorities and women holding a STEM degree is rooted in the inequitable development of STEM skills and interests through the U.S. K–12 education system (Legewie and DiPrete 2014; Tyson et al. 2007; Xie et al. 2015). As 1.5th-generation immigrants completed their K–12 education in the United States, disparities in STEM degree attainment by race/ethnicity and gender within this group likely mirror those observed among U.S.-born individuals to some extent. However, more thoughtful investigations are needed to understand race/ethnicity and gender disparities among 1.25th- and 1st-generation immigrants, who did not complete their K–12 education in the United States.

Although 1.25th- and 1st-generation immigrants are not subject to the inequities of the U.S. K–12 education system, they face various, potentially even more severe, structural barriers that can racialize and gender the development of their STEM skills and interests. Disproportionate educational opportunities against racial/ethnic minorities and women exist not only in the United States but also in many countries around the world (Filmer 2005; Van De Werfhorst and Mijs 2010), and the levels of resources available to support general math and science education for children differ by country (OECD 2022a). Developed countries tend to invest heavily in STEM workforce development, with the top eight countries in R&D expenses as of 2018 being the United States, China, Japan, Germany, South Korea, France, India, and the United Kingdom (NSB 2022). As these countries are common birthplaces for White and Asian immigrants, their development of STEM skills and interests likely benefits from the abundant resources available in their home countries, which may not be accessible to individuals born elsewhere.

Furthermore, STEM immigration processes within the United States can be racialized and gendered (Sáenz and Manges Douglas 2015; Waters and Eschbach 1995). Wait times and pathways for legal immigration vary by country of origin, creating uncertainty for racial/ethnic minorities regarding the possibility of obtaining legal immigration status (Massey and Malone 2002; Obinna 2020). Socioeconomic insecurity experienced during the immigration process poses distinct challenges for immigrant women (Muchomba and Kaushal 2022; Pedraza 1991). The prevalence of negative stereotypes about racial/ethnic minorities and women in STEM fields in the United States can exacerbate the challenges they encounter in securing visa sponsorship from STEM employers (Eaton et al. 2020; McGee 2018). This dynamic may reduce the likelihood of holding a STEM degree among racial/ethnic minorities and women, particularly 1.25th- and 1st-generation immigrants.

To summarize, STEM immigration has the potential to greatly influence the development of the U.S. STEM workforce. First, college-educated immigrants, particularly those in the 1.25th and 1st generations, are expected to have a higher likelihood of holding a STEM degree compared with individuals born in the United States (hypothesis 1). Second, disparities by race/ethnicity and gender in the likelihood of holding a STEM degree would be more pronounced among immigrants, especially those in the 1.25th and 1st generations, than among their U.S.-born counterparts (hypothesis 2). Although earning a U.S. STEM degree can facilitate legal naturalization, the STEM immigration process would reflect racialized and gendered patterns, shaped by structural and contextual factors operating both in immigrants’ countries of origin and within the United States.

Analytic Strategy

Data and Sample

This study utilizes data from the National Survey of College Graduates, conducted in 2010, 2013, 2015, 2017, and 2019. The National Survey of College Graduates is a nationally representative survey of college graduates who hold bachelor’s or higher degrees, including those earned abroad, and who currently reside in the United States. It offers detailed information on respondents’ educational and occupational outcomes, with a particular focus on STEM majors and careers.

The analytic sample is restricted to non-Hispanic White (White), non-Hispanic Black (Black), Hispanic, and non-Hispanic Asian (Asian) individuals. Although the exclusion of other racial/ethnic groups is not ideal, it is necessary because of their small representation (2.4 percent), which makes it practically infeasible to further disaggregate by immigration status. The final unweighted sample size used in the main analyses was 434,230 college graduates.

Statistical Models

The logistic regression models used for the main analyses are specified as follows:

l o g i t [p (y = 1)] = α + \sum_{i = 1}^{3} \sum_{j = 1}^{3} (β_{i} R_{i} + γ G + δ_{j} I_{j} + ε_{i} R_{i} G + \in_{i j} R_{i} I_{j} + ζ_{j} G I_{j} + η_{i j} R_{i} G I_{j}) + \sum_{k = 1}^{K} θ_{k} C_{k} .

In this equation, the dependent variable (y) is a binary variable indicating whether respondents held STEM degrees in the survey reference year (0 for no and 1 for yes). This study adopts the definition of STEM fields used by NCES (2023b), which includes biological and biomedical sciences, computer and information sciences, engineering and engineering technologies, mathematics and statistics, and physical sciences and science technologies. Sensitivity analyses using slightly altered definitions of STEM do not yield substantial differences from the main findings.

The race/ethnicity variable (R_i) has four categories (White [reference], Black, Hispanic, and Asian), and the gender variable (G) has two categories (men [reference] and women). To reveal the heterogeneity within these race/ethnicity and gender categories, this study considers immigration status (I_j), which is measured using four categories (U.S.-born [reference] and 1.5th, 1.25th, and 1st generations). Following Kim and Sakamoto (2010), the study considers foreign-born college graduates who completed both secondary and postsecondary education in the United States as the 1.5th generation, those who completed their secondary education in their birth country and their postsecondary education in the United States as the 1.25th generation, and those who arrived in the United States after completing both secondary and postsecondary education as the 1st generation. The model includes interaction terms for race/ethnicity, gender, and immigration status (R_iG, R_iI_j, GI_j, and R_iGI_j). Last, the covariates (C_k) in the statistical model are survey year, age, highest degree attained (bachelor’s or graduate degree), and educational attainment of respondents’ male and female parents or guardians (parent or guardian absence, less than high school, high school, bachelor’s degree, or graduate degree).

One important caveat is that caution is required when interpreting interaction terms in logistic regression models because of critical methodological issues, such as unobserved heterogeneity, scale dependence, and variance differences across groups (Allison 1999; Breen and Karlson 2013; Long and Mustillo 2021; Mood 2010; Mustillo, Lizardo, and McVeigh 2018; Williams 2009). To address these concerns, this study follows recommendations by Mood (2010) and Long and Mustillo (2021), using marginal effects and predicted probabilities calculated from logistic regression models to draw statistical conclusions. Additionally, linear probability models (LPMs) are used as sensitivity analyses. The findings from the logistic regression models closely align with those from the LPMs, further confirming the robustness of the study’s results.

This study also investigates variations in the main findings on the basis of respondents’ highest degree attained and, for immigrants, their countries of birth. Survey weights are applied to all estimations. Table A1 in the Appendix displays the analytic variables used in this study.

Empirical Results

Descriptive Statistics

Descriptive statistics presented in Table 1 highlight the importance of immigrants in shaping the U.S. STEM workforce. Immigrants account for 29.5 percent (1 − 0.705) of STEM degree holders, compared with only 12.8 percent among non-STEM degree holders. Notably, nearly four fifths of immigrants with STEM degrees belong to the 1.25th- or 1st-generation category, having completed their K–12 education outside the United States. Together, these two immigrant groups represent 23.1 percent (0.096 + 0.135) of STEM degree holders in the United States.

Table 1.

Composition of STEM and Non-STEM Degree Holders by Race/Ethnicity, Gender, and Immigration Status.

	U.S.-Born	1.5th Generation	1.25th Generation	1st Generation	Total
Immigration status composition
STEM degree holders	.705	.064	.096	.135	1.000
Non-STEM degree holders	.872	.045	.032	.051	1.000
Race/ethnicity and gender composition by immigration status
STEM degree holders
Race/ethnicity
White	.852	.321	.182	.312	.681
Black	.053	.061	.071	.025	.052
Hispanic	.061	.165	.064	.114	.075
Asian	.034	.453	.683	.549	.192
Total	1.000	1.000	1.000	1.000	1.000
Gender
Men	.708	.676	.698	.665	.700
Women	.292	.324	.302	.335	.301
Total	1.000	1.000	1.000	1.000	1.000
Non-STEM degree holders
Race/ethnicity
White	.838	.372	.263	.274	.770
Black	.077	.095	.170	.047	.079
Hispanic	.067	.239	.153	.201	.084
Asian	.018	.295	.414	.478	.067
Total	1.000	1.000	1.000	1.000	1.000
Gender
Men	.420	.415	.430	.380	.418
Women	.580	.585	.570	.620	.582
Total	1.000	1.000	1.000	1.000	1.000

Source: National Survey of College Graduates (2010, 2013, 2015, 2017, and 2019).

Note: The sample comprises 186,021 STEM degree holders and 248,209 non-STEM degree holders. STEM = science, technology, engineering, and mathematics.

Table 1 also depicts the racial/ethnic and gender composition, categorized by immigration status. Among U.S.-born STEM degree holders, 85.2 percent are White. However, among immigrant STEM degree holders, White individuals do not constitute the majority, accounting for approximately one third or less among the three immigrant groups with STEM degrees. Black and Hispanic individuals experience relative marginalization within the STEM degree holder groups. The representation of Black individuals consistently remains lower among STEM degree holders, regardless of immigration status, indicating their persistent underrepresentation in the STEM field. Similarly, Hispanic individuals face marginalization within the STEM degree holder group, with proportions varying on the basis of immigration status. Nonetheless, like Black individuals, the representation of Hispanic individuals consistently remains lower among STEM degree holders compared with non-STEM degree holders.

The proportions of Asian individuals among STEM degree holders show significant variation by immigration status. Among U.S.-born STEM degree holders, Asians represent the smallest group, constituting only 3.4 percent. However, among immigrant STEM degree holders, Asians constitute approximately half or more, surpassing all other racial/ethnic groups. Compared with non-STEM degree holders, the share of Asians is much higher among STEM degree holders, especially within immigrant groups. Understanding the substantial contribution of Asian immigrants is crucial in explaining the large proportion of Asian individuals among U.S. STEM degree holders, accounting for 19.2 percent of the total.

The proportion of men is higher than that of women among STEM degree holders. Among U.S.-born STEM degree holders, women comprise only 29.2 percent, with their proportions showing a slight increase among immigrant groups. However, immigrant women still remain underrepresented compared with their male counterparts among STEM degree holders.

In summary, the descriptive statistics underscore the importance of considering immigration in addressing race/ethnicity and gender representation in the U.S. STEM workforce, warranting further investigation into the intersectionality of race, gender, and immigration status in the U.S. STEM workforce. The next phase of this study involves examining variations in the probability of holding a STEM degree on the basis of race, gender, and immigration status.

Regression Estimations

Main Findings

Table 2 displays differences in the predicted probability of college graduates holding a STEM degree by race/ethnicity, gender, and immigration status. These differences are calculated on the basis of logistic regression estimates reported in Table A2 to address methodological issues associated with interpreting interaction terms in logistic regression models and to facilitate a clearer interpretation (Long and Mustillo 2021; Mood 2010). The leftmost of the three sections (section A) in Table 2 presents comparisons between U.S.-born White individuals (the reference group) and all other groups. The results indicate that for both men and women, all immigrant groups, regardless of race/ethnicity, are equally or more likely than their U.S.-born White counterparts to hold a STEM degree. The findings highlight the substantial contributions of immigrants to racial diversity in the U.S. STEM workforce.

Table 2.

Differences in Predicted Probability of Holding a STEM Degree by Race/Ethnicity, Gender, and Immigration Status on the Basis of Logistic Regression Estimates.

	Section A: Differences from White Born in the United States		Section B: Differences from White with the Same Immigration Status		Section C. Differences between Men and Women with the Same Race/Ethnicity and Immigration Status
	Men	Women	Men	Women
U.S.-born
White	−	−	−	−	−.163 (.003)***
Black	−.069 (.007)***	−.002 (.004)	−.069 (.007)***	−.002 (.004)	−.096 (.008)***
Hispanic	−.035 (.008)***	.007 (.005)	−.035 (.008)***	.007 (.005)	−.121 (.009)***
Asian	.086 (.014)***	.078 (.008)***	.086 (.014)***	.078 (.008)***	−.171 (.016)***
1.5th generation
White	.081 (.015)***^†††	.031 (.010)**^††	−	−	−.212 (.018)***^††
Black	−.008 (.026)^†	.038 (.018)*^†	−.089 (.030)**	.007 (.021)	−.117 (.032)***
Hispanic	.013 (.017)^†	.028 (.015)	−.068 (.023)**	−.003 (.018)	−.147 (.022)***
Asian	.185 (.015)***^†††	.132 (.011)***^†††	.104 (.021)***	.101 (.015)***	−.216 (.019)***
1.25th generation
White	.272 (.018)***^†††	.116 (.015)***^†††	−	−	−.318 (.023)***^†††
Black	.095 (.024)***^†††	.050 (.018)**^††	−.177 (.030)***^†††	−.066 (.023)**^††	−.207 (.030)***^†††
Hispanic	.107 (.025)***^†††	.054 (.015)***^††	−.165 (.031)***^†††	−.062 (.021)**^††	−.216 (.029)***^††
Asian	.452 (.012)***^†††	.337 (.015)***^†††	.180 (.021)***^†††	.221 (.021)***^†††	−.277 (.019)***^†††
1st generation
White	.303 (.015)***^†††	.184 (.013)***^†††	−	−	−.282 (.019)***^†††
Black	.064 (.032)*^†††	.055 (.029)	−.239 (.035)***^†††	−.129 (.031)***^†††	−.172 (.043)***
Hispanic	.166 (.027)***^†††	.046 (.014)***^††	−.138 (.031)***^††	−.137 (.019)***^†††	−.282 (.030)***^†††
Asian	.315 (.013)***^†††	.188 (.009)***^†††	.011 (.019)^††	.004 (.016)^†††	−.289 (.016)***^†††

Source: National Survey of College Graduates (2010, 2013, 2015, 2017, and 2019).

Note: The sample comprises 434,230 college graduates. Numbers in parentheses are standard errors.

p < .05, **p < .01, and ***p < .001 (two-tailed tests).

†

p < .05, ^††p < .01, and ^†††p < .001 (two-tailed tests of differences from estimates for U.S.-born).

The middle section (section B) of Table 2 presents differences in the probability of holding a STEM degree compared with White individuals of the same immigration status. Among men, compared with their White counterparts with the same immigration status, Black and Hispanic individuals are less likely to hold a STEM degree. Among women, the White-Black and White-Hispanic gaps are not statistically significant within the U.S.-born and 1.5th-generation groups but within the 1.25th- and 1st-generation groups. The White-Asian gap within the same immigration status is significant for all groups except the 1st generation.

Furthermore, the dagger marks in section B of Table 2 indicate whether the observed racial/ethnic gaps significantly differ by immigration status. For both men and women, racial/ethnic disparities among the 1.5th generation are not statistically different from those among the U.S.-born. However, racial/ethnic disparities among the 1.25th- and 1st-generation groups differ significantly from those among the U.S.-born. Among men, the White-Black and White-Hispanic gaps are at least 2.5 times wider among 1.25th- and 1st-generation immigrants than among the U.S.-born. Similarly, the White-Asian gap among 1.25th-generation immigrant men is 2.1 times wider than that among U.S.-born men. Similarly, among women, the White-Black and White-Hispanic gaps are statistically significant only among 1.25th- and 1st-generation immigrants. The White-Asian gap among 1.25th-generation immigrant women is 2.8 times wider than that among U.S.-born women. Notably, the White-Asian gaps among 1st generation immigrants, for both men and women, are not statistically significant.

Last, the right section (section C) of Table 2 presents gender differences in the probability of holding a STEM degree within the same race/ethnicity and immigration status. Women are less likely than men to hold a STEM degree across all groups. Gender disparities among the 1.5th-generation groups are not statistically different from those among the U.S.-born groups, except for the 1.5th-generation White group, which exhibits significantly wider gender disparities compared with its U.S.-born White counterpart. All 1.25th- and 1st-generation groups, except for the 1st-generation Black group, show wider gender disparities than the U.S.-born groups. Although gender disparities among 1st-generation Black immigrants are not statistically different from those among U.S.-born Black individuals—partly because of the small sample size of 1st-generation Black women—the coefficient for the former is approximately 1.8 times larger than that for the latter. Overall, these results highlight the striking variation in race/ethnicity and gender disparities in the probability of holding a STEM degree on the basis of immigration status.

Figure 1 provides a comprehensive overview of differences in the probability of holding a STEM degree by race, gender, and immigration status. The predicted probabilities in Figure 1A are calculated using logistic regression estimates from Table A2. First, despite a few exceptions noted earlier, both immigrant men and women, particularly those in the 1.25th- and 1st-generation groups, have equal or higher probabilities of holding a STEM degree compared with their U.S.-born White (hypothesis 1). Additionally, race/ethnicity and gender disparities in the probability of holding a STEM degree are more pronounced among the 1.25th- and 1st-generation groups than among the U.S.-born (hypothesis 2).

Figure 1.

Predicted probability of holding a science, technology, engineering, and mathematics degree by race/ethnicity, gender, and immigration status.

Another noteworthy finding is that the predicted probability of holding a STEM degree is notably lower among Asian 1st-generation immigrant men and women compared with their Asian 1.25th-generation counterparts. In contrast, the differences between the 1st and 1.25th generations are not significant among White, Black, and Hispanic immigrants. These results suggest the possibility that STEM degrees attained in Asian countries are particularly undervalued in the U.S. labor market and STEM immigration processes.

To verify the robustness of the main findings from the logistic regression model, an LPM is estimated as a sensitivity analysis. Figure 1B displays the predicted probabilities calculated from the LPM alongside those from the logistic regression model shown in Figure 1A. The results from both models are almost identical. The full LPM is presented in the right column of Table A2. Additionally, Figure A1 presents the results of a sensitivity analysis using two alternative dependent variables: STEM degrees excluding biology and biomedical sciences and STEM occupations. The analysis implies that gender disparities tend to be wider in the male-dominated STEM fields and that some STEM degree holders do not engage in STEM occupations. However, the sensitivity analyses do not yield any substantial differences from the main results, further confirming the robustness of the findings on the intersectionality of race/ethnicity, gender, and immigration status. Future research on STEM immigration should further investigate the extent to which STEM degree holders transition into STEM occupations, and how this pathway may vary by race/ethnicity, gender, and immigration status.

Group Variations

Given that U.S. immigration laws have been more favorable to immigrants holding a STEM degree at the graduate level rather than at the undergraduate level, the differences by race, gender, and immigration status in the probability of holding a STEM degree may be more pronounced among graduate degree holders than bachelor’s degree holders. To investigate this possibility, the predicted probabilities of holding a STEM degree, estimated separately for graduate degree holders and those holding only a bachelor’s degree, are displayed in Figure 2. Although 1.25th- and 1st-generation immigrants have a higher probability of holding a STEM degree than U.S.-born individuals at both the bachelor’s and graduate levels, with a few exceptions, the differences between the U.S.-born and immigrants are more noticeable among graduate degree holders than among those with only a bachelor’s degree. Moreover, variations in race/ethnicity and gender disparities by immigration status are more evident among graduate degree holders than among bachelor’s degree holders. These results indicate that U.S. immigration laws have played a role in constructing race/ethnicity and gender representation in the U.S. STEM workforce, even if the large race/ethnicity and gender disparities in the probability of holding a STEM degree among immigrants may not be a consequence intended by policymakers.

Figure 2.

Predicted probability of holding a science, technology, engineering, and mathematics degree among bachelor’s and graduate degree holders by race/ethnicity, gender, and immigration status.

In addition to U.S. immigration laws and processes, the socioeconomic contexts in immigrants’ birth countries would be connected to educational and other socioeconomic outcomes in the United States. Figure 3 illustrates immigrants’ predicted probabilities of holding a STEM degree, estimated separately by country of birth. Each racial/ethnic group is subdivided into five commonly observed birth countries and an “Other” category. Substantial heterogeneity by immigration status and birth country is observed within racial/ethnic groups, particularly among White and Asian immigrant groups. For men, 1.25th-generation and 1st-generation immigrants from China, India, Iran, Russia, and Taiwan are the only groups with predicted probabilities higher than 0.6. For women, 1.25th-generation and 1st-generation immigrants from China, India, Iran, and Russia are the only groups with predicted probabilities higher than 0.4. All of these countries are popular birthplaces for White and Asian immigrants. With the exception of immigrants from these countries, the predicted probabilities of holding a STEM degree largely overlap across racial/ethnic groups and do not differ significantly.

Figure 3.

Predicted probability of holding a science, technology, engineering, and mathematics degree among college-educated immigrants by race/ethnicity, immigration status, and birth country.

Supplementary Analyses

The results raise a question about why immigrants’ probabilities of holding a STEM degree vary by birth country. Although this new question is out of the scope of this study, supplementary analyses are conducted to provide insights for future studies. The supplementary analyses include data from the World Bank and the National Statistics of the Republic of China to explore whether the gross domestic product (GDP) of immigrants’ birth countries is related to racial/ethnic gaps in the probabilities of holding a STEM degree. The World Bank data contain many missing values, which are unevenly distributed, with historically underrepresented racial/ethnic groups in the U.S. STEM workforce more likely to come from countries with missing values. To avoid missing values, the sample for the supplementary analyses is limited to immigrants from 20 selected countries: the top 5 birth countries for each of the four racial groups, listed in Figure 3. Among the 20 selected countries, only Taiwan is not included in the World Bank data. To fill in the missing values for Taiwan, data from the National Statistics of the Republic of China are used. Because of the data limitations, the supplementary results should be interpreted with caution.

Figure 4 indicates that immigrants from countries with larger GDPs tend to have a higher probability of holding a STEM degree. The positive correlations between immigrants’ probabilities of holding a STEM degree and their birth country’s GDP are particularly strong and statistically significant among both 1st-generation men and women. Furthermore, Table A3 presents racial/ethnic disparities in the probability of holding a STEM degree for immigrants from the 20 selected countries, 7 estimated without (model 1) and with (model 2) the control for log-transformed GDP. Controlling for birth country GDP somewhat attenuates the coefficients for White-Black and White-Hispanic gaps and makes some of them nonsignificant. However, the White-Asian gaps have rarely changed by controlling for GDP. The supplementary analyses imply that the socioeconomic conditions of immigrants’ birth country would be one of the many factors affecting their probability of holding a STEM degree.

Figure 4.

Relationship between predicted probability of holding a STEM degree and GDP of country of origin among immigrants from 20 countries.

Discussion

This research has examined disparities in the likelihood of holding a STEM degree among college graduates in the United States, focusing on race/ethnicity, gender, and immigration status. The analyses reveal striking variations in race/ethnicity and gender disparities in the probability of holding a STEM degree across different places of birth and education. These findings offer valuable insights into the intricate dynamics that shape the U.S. STEM workforce at the intersections of race, gender, and immigration status.

Regardless of race/ethnicity and gender, college-educated immigrant men and women from all non-White racial/ethnic groups are equally or more likely than U.S.-born White college graduates to possess a STEM degree. These findings highlight the substantial contributions of STEM immigration in enriching and diversifying the U.S. STEM workforce. Additionally, the gaps observed between immigrants and U.S.-born individuals in the probability of holding a STEM degree are more pronounced among those with graduate degrees than among those holding only a bachelor’s degree, indicating the critical impacts of U.S. immigration policies that aim to bolster the domestic STEM workforce by facilitating the immigration of foreign-born individuals with STEM degrees, particularly at the most advanced level (Roach and Skrentny 2021; Wasem 2012). Nonetheless, the positive contributions of immigrants to the U.S. STEM workforce are often overlooked, as some politicians and media outlets frequently emphasize negative portrayals of immigrants (Conzo et al. 2021).

Moreover, there has been a lack of policymaking aimed at promoting diversity and inclusion in STEM immigration processes. Race/ethnicity and gender disparities in the probability of holding a STEM degree are much wider among 1.25th- and 1st-generation immigrants compared with U.S.-born individuals. In contrast, patterns of race/ethnicity and gender disparities are similar between 1.5th-generation immigrants and U.S.-born individuals. The striking race/ethnicity and gender gaps observed among the 1.25th- and 1st-generation immigrants cannot be explained by previous studies that focus on the unequal development of STEM-related academic skills and interests through U.S. K–12 education (Legewie and DiPrete 2014; Tyson et al. 2007; Xie et al. 2015). 1st- and 1.25th-generation immigrants completed their K–12 education in their birth countries before immigrating to the United States.

The findings of this study raise a new question for future research: why are race/ethnicity and gender disparities so pronounced among college-educated 1.25th- and 1st-generation immigrants in the United States? Addressing this question will require carefully designed studies that examine immigrants’ experiences both in their countries of birth and in the United States. Although collecting high-quality data on immigrants’ experiences across countries presents particular challenges, further investigations into STEM immigration are essential to enhancing diversity and inclusion in the U.S. STEM workforce.

In the supplementary analyses, controlling for birth-country GDP partially reduces estimated racial/ethnic gaps between White/Asian and Black/Hispanic individuals in the probability of holding a STEM degree among immigrants. This indicates that the higher probabilities of holding a STEM degree among White and Asian immigrants are partly associated with their socioeconomic advantages derived from their home countries’ economic resources and advanced education systems, which may not be as accessible in countries with smaller GDPs. Limited economic and educational resources in birth countries can restrict opportunities for developing STEM-related capacities and immigrating to the United States, particularly for racial/ethnic minorities and women (Pedraza 1991; Waters and Eschbach 1995). To some extent, race/ethnicity and gender representation within the U.S. STEM workforce is intertwined with global economic inequalities between countries. However, even after controlling for the GDP of immigrants’ birth countries, noticeable race/ethnicity and gender disparities in the probability of holding a STEM degree among immigrants persist. Additional analyses, not presented in this article, incorporated various country-level variables from immigrants’ birth countries, including R&D expenditure, life expectancy, poverty rate, Gini index, and average schooling years. However, these analyses did not yield interpretable findings, partly because of the large number of missing values and their nonrandom distribution. Future studies should incorporate various socioeconomic indicators beyond GDP to examine the social contexts experienced by immigrants in their birth countries.

In addition, further investigations into the structural barriers that immigrants face within the United States are imperative. Securing employer sponsorship is necessary for most immigrants to obtain a work permit, and they are required to regularly renew their visa documentation unless they obtain LPR status (Granovskiy and Wilson 2019; Roach and Skrentny 2021; Wasem 2012). Wait times in visa and LPR queues can vary significantly, sometimes lasting several decades, and these prolonged delays disproportionately affect racial/ethnic minorities and women (Massey and Malone 2002; Pedraza 1991; Waters and Eschbach 1995). Additionally, the prevalence of discriminatory stereotyping of STEM skills and interests based on race/ethnicity and gender can exacerbate the barriers faced by racial/ethnic minorities and women in pursuing STEM degrees and careers in the United States (Eaton et al. 2020; McGee 2018; Trauth et al. 2016). Nonetheless, the racialized and gendered aspects of immigration processes have been understudied because of the limited availability of government data for researchers (Obinna 2020).

This study highlights the need for improved data collection to better understand race and gender disparities in the development of the U.S. STEM workforce. Although previous studies have extensively documented the STEM pathways, they have rarely included immigrant STEM students and workers. Although this study helps address this research gap, data limitations prevented it from accounting for various covariates, such as family income and precollege test scores, which have been considered in prior research. However, even if such covariates were available, cross-country comparisons would remain highly challenging because of differences in education systems and socioeconomic classifications. In addition to expanding quantitative data collection, qualitative studies would be essential for understanding the mechanisms driving the racialized and gendered patterns identified in this study.

Another intriguing question raised by the findings in this study is why the White-Asian gaps in the probability of holding a STEM degree among 1.25th-generation immigrants are much wider than those among U.S.-born individuals and 1st-generation immigrants. The significant gaps between Asian and White 1.25th-generation immigrants are rarely diminished when controlling for the GDP of their birth countries. In contrast, the White-Asian gap among 1st-generation immigrants is not statistically significant even without the GDP control. As suggested by Kim (2015) and Kim and Sakamoto (2010), 1.25th-generation immigrants constitute a distinctive group that needs to be considered separately from both 1.5th-generation and 1st-generation immigrants. Considering the place of education is crucial for enhancing the understanding of the heterogeneity among immigrants (Shao 2023; Zeng and Xie 2004).

It is possible that seeking a STEM degree is a strategically effective choice for Asian immigrants because of the prevalent positive stereotypes surrounding the proficiency of Asian individuals in STEM fields in the United States (Chen and Buell 2018; McGee 2018; Xie and Goyette 2003). Drawing on cultural, structural, and marginality perspectives, Xie and Goyette (2003) presumed that Asian individuals feel compelled to pursue STEM education unless they encounter severe discrimination in the labor market, particularly in the non-STEM fields.

This strategic adaptation may be vital for Asian 1.25th-generation immigrants because they not only encounter barriers in labor market processes but also face challenges in the immigration process, lacking the social capital and resources often available to their U.S.-born and 1.5th-generation immigrant counterparts. Compared with Asian 1.25th-generation immigrants who had the opportunity to seek a college degree in the United States, this strategy is less effective for Asian 1st-generation immigrants who completed postsecondary education in their birth countries. Educational degrees obtained outside the United States are undervalued in the labor market and in STEM immigration processes in the United States (Shao 2023; Wasem 2012; Zeng and Xie 2004).

This study reveals that Asian 1st-generation immigrants have a significantly lower probability of holding a STEM degree compared with Asian 1.25th-generation immigrants. The gap between 1st- and 1.25th-generation immigrants is not significant in any other racial/ethnic groups. The STEM degrees obtained in Asian countries may be particularly undervalued in the United States, highlighting the importance of investigating immigrants’ experiences both in the United States and in their countries of birth to understand the racial/ethnic disparities in the STEM degree attainment among immigrants in the United States.

The strategic adaptation perspective also provides a clue as to why immigrants from countries such as China, Iran, and Russia exhibit significantly higher probabilities of holding a STEM degree, even compared with other White and Asian immigrants. Considering that these countries are often viewed as strong competitors, if not adversaries, of the United States, immigrants from these countries likely face heightened challenges in the U.S. labor market and immigration processes unless they demonstrate exceptional STEM skills and interests.

It is important to acknowledge several limitations of this study. Although the quantitative analyses employ interaction terms to account for the intersectionality of race, gender, and immigration status, this approach may not fully capture the complexity of intersectionality or the unique experiences of individuals within specific groups. The four racial/ethnic categories used in this study may not be ideal, but the inclusion of other minority groups is not feasible because of the small sample sizes (Oh, Mackin Freeman, and Shifrer 2023). The large sample size used in this study enhances statistical power; however, it also increases the likelihood of detecting statistically significant differences with small effect sizes. Accordingly, readers are encouraged to interpret the findings with this consideration in mind. In addition, this study includes a limited number of covariates because of data limitations, highlighting the need for new datasets to further explore race and gender diversity in the U.S. STEM workforce, including immigrant students and workers.

Furthermore, this study focuses on college graduates. Although many STEM occupations require postsecondary education, the STEM workforce also includes individuals who do not have a college degree (American Immigration Council 2022). Last, the analyses cannot distinguish between second-generation immigrants and other U.S.-born individuals, implying that the contribution of STEM immigration to the U.S. STEM workforce may be greater than that discussed in this study. These limitations warrant future research to provide a more nuanced understanding of the complex dynamics shaping the intersectionality of race, gender, and immigration status in the U.S. STEM workforce development.

Conclusion

U.S. immigration policies, which favor foreign-born individuals with STEM skills and interests, have increased the representation of immigrants in the U.S. STEM workforce (Amuedo-Dorantes et al. 2019; Granovskiy and Wilson 2019; Wasem 2012). The STEM-focused immigration policies may have disproportionate impacts on racial/ethnic minorities and women. Nonetheless, the development of policies aimed at improving diversity and inclusion in STEM immigration processes has been surprisingly lacking thus far. To accelerate economic growth, policymakers need to continue encouraging talented individuals from abroad to pursue STEM degrees and careers in the United States, thereby further growing the importance of STEM immigration in promoting diversity and inclusion in the U.S. STEM workforce.

This study emphasizes the urgent need for increased scholarly and policy attention to racialized and gendered aspects of STEM immigration processes. Efforts should include expanding access to government data on immigration processes for research purposes, mitigating racial/ethnic and gender biases related to STEM skills and interests, and embracing international students and workers to promote the success of underrepresented groups in STEM education and occupations. By achieving greater diversity and inclusion in the STEM workforce, U.S. society can unlock the full potential of all individuals—regardless of race, gender, or immigration status—to drive technological innovations and foster sustainable economic growth.

Footnotes

Appendix

Table A3.

Differences in the Predicted Probability of Holding a Science, Technology, Engineering, and Mathematics Degree by Race/Ethnicity among Immigrants from 20 Countries on the Basis of Logistic Regression Estimates.

	Men		Women
	Model 1	Model 2	Model 1	Model 2
1.5th generation (reference: White)
Black	−.089 (.039)*	.054 (.077)	.050 (.032)	.108 (.066)
Hispanic	−.100 (.031)***	−.050 (.040)	.027 (.026)	.041 (.034)
Asian	.112 (.032)***	.118 (.029)***	.104 (.022)***	.104 (.021)***
Log-transformed GDP		.032 (.012)**		.013 (.010)
n	8,232	8,232	7,271	7,271
1.25th generation (reference: White)
Black	−.134 (.060)*	−.096 (.080)	−.122 (.039)**	−.014 (.068)
Hispanic	−.133 (.061)*	−.120 (.070)	−.095 (.037)**	−.070 (.045)
Asian	.179 (.055)***	.163 (.057)**	.178 (.039)***	.122 (.040)**
Log-transformed GDP		.015 (.014)		.051 (.009)***
n	15,976	15,976	10,032	10,032
1st generation (reference: White)
Black	−.420 (.031)***	−.263 (.055)***	−.108 (.051)*	.063 (.056)
Hispanic	−.139 (.031)***	−.050 (.041)	−.147 (.038)***	−.093 (.038)*
Asian	−.049 (.034)	−.046 (.029)	.020 (.043)	.031 (.036)
Log-transformed GDP		.067 (.013)***		.063 (.011)***
n	15,177	15,177	11,408	11,408

Sources: National Survey of College Graduates (2010, 2013, 2015, 2017, and 2019); World Bank (2019); National Statistics of the Republic of China (2019).

Note: Numbers in parentheses are standard errors. As the inclusion of country-level variables can lead to a downward bias in standard errors, clustered standard errors are calculated. Control variables include survey year, age, highest degree attained, and educational attainment of male and female parents or guardians. The coefficients and standard errors are available upon request. GDP = gross domestic product.

p < .05, **p < .01, and ***p < .001 (two-tailed tests).

ORCID iD

Byeongdon Oh

Author Biography

Byeongdon Oh is a first-generation immigrant scholar from South Korea. He is an assistant professor of sociology and the founding director of the Diversity, Equity, Inclusion, and Belonging (DEIB) Research Center at the State University of New York Polytechnic Institute. He also serves as a visiting research professor at the Social Science D-Lab at the University of California-Berkeley. Drawing on a diverse professional background as a journalist, military officer, and policy researcher, he offers a sociological perspective deeply informed by a commitment to social justice. His research interests include social inequality and stratification, race and ethnicity, gender, education, STEM, quantitative methods, and mixed methods. For more information, visit .

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STEM Immigration and U.S. STEM Workforce Development at the Intersections of Race/Ethnicity,Gender,and Immigration Status

Abstract

Keywords

Literature Review

Race/Ethnicity and Gender Representation in the U.S. STEM Workforce Development

The Rise of STEM Immigration

Race/Ethnicity, Gender, and Immigration Status in the U.S. STEM Workforce Development

Analytic Strategy

Data and Sample

Statistical Models

Empirical Results

Descriptive Statistics

Regression Estimations

Main Findings

Group Variations

Supplementary Analyses

Discussion

Conclusion

Footnotes

Appendix

ORCID iD

Author Biography

References