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Beyond good grades: School composition and immigrant youth participation in extracurricular activities Dina G. Okamoto , Daniel Herda, Cassie Hartzog University of California, Davis, United States article info Article history: Received 13 February 2011 Revised 10 August 2012 Accepted 14 August 2012 Available online 31 August 2012 Keywords: Immigrant incorporation Race/ethnicity School composition Extracurricular activities abstract Past research has typically focused on educational attainment and achievement to under- stand the assimilation process for immigrant youth. However, academic achievement con- stitutes only part of the schooling experience. In this paper, we move beyond traditional measures such as test scores and dropout, and examine patterns of school-sponsored extracurricular activity participation. Analyzing data from Add Health and drawing upon the frog-pond and segmented assimilation frameworks, we find that immigrant minority youth are disadvantaged in regards to activity participation relative to the average student in high- compared to low-SES schools. In high-SES schools, immigrant youth are less sim- ilar to their peers in terms of socioeconomic, race, and immigrant status, and as suggested by the frog-pond hypothesis, social comparison and ranking processes contribute to lower levels of social integration of immigrant youth into the school setting. We also find that as percent minority rises in high-SES schools, participation increases as well. The opposite pattern appears in low-SES schools: when percent minority increases, activity participation among immigrant minority students declines. These results are commensurate with both theoretical frameworks, and suggest that different mechanisms are at work in high- and low-SES schools. However, the effects of minority peers do not seem to hold for sports par- ticipation, and we also find that percent immigrant operates differently from percent minority, depressing the probability of activity participation across both high- and low- SES schools. The main implication of our results is that racially diverse, higher-SES schools are the most favorable contexts for the social integration of immigrant minority youth as well as third- and later-generation blacks and Hispanics. Ó 2012 Elsevier Inc. All rights reserved. 1. Introduction Significant growth in the size and diversity of the immigrant population in the US over the past two decades has prompted scholars to examine the patterns, character, and timing of the process through which immigrants are becoming part of the American mainstream. This focus on immigrant incorporation has produced studies on the socioeconomic trajec- tories and outcomes of new immigrants and their children (Alba and Nee, 2003; Bean and Stevens, 2003; Lee and Bean, 2010; Kasinitz et al., 2008; Portes and Rumbaut, 2001; Telles and Ortiz, 2008). In particular, there has been a growing interest in the adaptation experiences of immigrant and second-generation youth because they provide insights into the future of American society. In this paper, we focus on immigrant youth incorporation into US schools, a key institution shaping future social and economic opportunities. 0049-089X/$ - see front matter Ó 2012 Elsevier Inc. All rights reserved. http://dx.doi.org/10.1016/j.ssresearch.2012.08.005 Corresponding author. Address: Department of Sociology, University of California-Davis, One Shields Avenue, Davis, CA 95616, United States. E-mail address: [email protected] (D.G. Okamoto). Social Science Research 42 (2013) 155–168 Contents lists available at SciVerse ScienceDirect Social Science Research journal homepage: www.elsevier.com/locate/ssresearch

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Page 1: Beyond good grades: School composition and immigrant youth participation in extracurricular activities

Social Science Research 42 (2013) 155–168

Contents lists available at SciVerse ScienceDirect

Social Science Research

journal homepage: www.elsevier .com/locate /ssresearch

Beyond good grades: School composition and immigrant youthparticipation in extracurricular activities

Dina G. Okamoto ⇑, Daniel Herda, Cassie HartzogUniversity of California, Davis, United States

a r t i c l e i n f o a b s t r a c t

Article history:Received 13 February 2011Revised 10 August 2012Accepted 14 August 2012Available online 31 August 2012

Keywords:Immigrant incorporationRace/ethnicitySchool compositionExtracurricular activities

0049-089X/$ - see front matter � 2012 Elsevier Inchttp://dx.doi.org/10.1016/j.ssresearch.2012.08.005

⇑ Corresponding author. Address: Department ofE-mail address: [email protected] (D.G. O

Past research has typically focused on educational attainment and achievement to under-stand the assimilation process for immigrant youth. However, academic achievement con-stitutes only part of the schooling experience. In this paper, we move beyond traditionalmeasures such as test scores and dropout, and examine patterns of school-sponsoredextracurricular activity participation. Analyzing data from Add Health and drawing uponthe frog-pond and segmented assimilation frameworks, we find that immigrant minorityyouth are disadvantaged in regards to activity participation relative to the average studentin high- compared to low-SES schools. In high-SES schools, immigrant youth are less sim-ilar to their peers in terms of socioeconomic, race, and immigrant status, and as suggestedby the frog-pond hypothesis, social comparison and ranking processes contribute to lowerlevels of social integration of immigrant youth into the school setting. We also find that aspercent minority rises in high-SES schools, participation increases as well. The oppositepattern appears in low-SES schools: when percent minority increases, activity participationamong immigrant minority students declines. These results are commensurate with boththeoretical frameworks, and suggest that different mechanisms are at work in high- andlow-SES schools. However, the effects of minority peers do not seem to hold for sports par-ticipation, and we also find that percent immigrant operates differently from percentminority, depressing the probability of activity participation across both high- and low-SES schools. The main implication of our results is that racially diverse, higher-SES schoolsare the most favorable contexts for the social integration of immigrant minority youth aswell as third- and later-generation blacks and Hispanics.

� 2012 Elsevier Inc. All rights reserved.

1. Introduction

Significant growth in the size and diversity of the immigrant population in the US over the past two decades hasprompted scholars to examine the patterns, character, and timing of the process through which immigrants are becomingpart of the American mainstream. This focus on immigrant incorporation has produced studies on the socioeconomic trajec-tories and outcomes of new immigrants and their children (Alba and Nee, 2003; Bean and Stevens, 2003; Lee and Bean, 2010;Kasinitz et al., 2008; Portes and Rumbaut, 2001; Telles and Ortiz, 2008). In particular, there has been a growing interest in theadaptation experiences of immigrant and second-generation youth because they provide insights into the future of Americansociety. In this paper, we focus on immigrant youth incorporation into US schools, a key institution shaping future social andeconomic opportunities.

. All rights reserved.

Sociology, University of California-Davis, One Shields Avenue, Davis, CA 95616, United States.kamoto).

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156 D.G. Okamoto et al. / Social Science Research 42 (2013) 155–168

Past research has often focused on educational achievement and attainment to understand the extent to which immigrantyouth are keeping up with native-born white peers (see Hirschman, 2001; Kao and Tienda, 1995; Keller and Tillman, 2008;Fuligni, 1997; Glick and White, 2004; Perriera et al., 2006). According to traditional assimilation theory, when parity in edu-cational achievement (or any other measure of educational or economic mobility) is achieved between the two groups, thissignifies that immigrants have overcome disadvantages associated with disruptions to family stability due to the migrationprocess, a lack of English fluency, and unfamiliarity with American culture (see Alba and Nee, 2003). The majority of thisresearch focuses on individual and background variables such as socioeconomic status, ethnicity, and parents’ expectationsto explain variations in educational outcomes.

The current study expands the existing literature in two ways. First, we move beyond the traditional measures of achieve-ment and attainment to understand immigrant youth incorporation. Measures of grades, test scores, and dropout are illus-trative of the assimilation process for immigrant youth, but they constitute only one aspect of the schooling experience.Students may be performing at high levels academically, but they may be socially isolated from their native-born peers.Examining the incorporation of immigrant youth into the school as a social rather than simply an academic institutionmay provide further insights into their current status in schools as well as their future integration as adults into mainstreamgroups and institutions. Thus, the current study takes an alternative approach by focusing on student involvement in school-based extracurricular activities, an integral yet understudied part of the US educational system. For immigrant youth, theseactivities provide a structure through which they build valued skills and competencies, learn about American social norms,practices, and culture, and interact with native peers in cooperative settings (Lareau, 2003; Olson, 2008).

We also contribute to the existing literature by examining the broader school context to understand the extent to whichimmigrant youth are incorporated into their schools. Clearly, broader contexts shape experiences, motivations, opportuni-ties, and ultimately, outcomes for youth (see Sampson et al., 1997; Brooks-Gunn et al., 1993). By considering how schoolcomposition – one aspect of the school context1 – shapes activity participation outcomes for immigrant and racial groups,we also address theoretical ideas in the literature. Specifically, the frog-pond framework posits that through social comparisonand evaluation processes, students who are in the minority in their school in regards to status markers such as SES will be at adisadvantage and perform poorly. We extend these ideas to race and immigrant status, and expect that immigrant minorityyouth will experience a relatively low social status in majority-white, non-immigrant school contexts, which could negativelyaffect their self-evaluations and school engagement. Alternatively stated, immigrant minority youth should fare better inschools where they are more similar to their peers along the dimensions of race and immigrant status.

In contrast, the ‘‘downward’’ trajectory of segmented assimilation theory highlights the fact that immigrant youth oftenattend low-income schools with high proportions of racial minority peers (see Portes and Zhou, 1993; Zhou and Bankston,1998; Waters, 1999). In such contexts, immigrant youth are exposed to a high risk of dropout, delinquency, and violence,which can derail their academic progress and result in downward mobility. The theory suggests that even if immigrant youthfind themselves in the majority, the increasing presence of racial minority peers in low-income contexts should have detri-mental effects on pro-social, achievement-oriented outcomes.

Using a nationally-representative data set which offers an oversample of several ethnic/immigrant groups, extensiveinformation on school-sponsored clubs and sports, and data on different age cohorts, we identify patterns of participationin extracurricular activities for immigrant and racial groups and then test theoretical ideas to find out if immigrant youthfare better in schools where they are more similar to or different from the ‘‘average’’ student along the dimensions of socio-economic, race, and immigrant status. This analysis will help us to understand the extent to which immigrant youth areincorporated into their school settings and building valued social and cultural capital, which has broader implications forsocial mobility processes.

2. Background and literature review

2.1. Participation in school-sponsored activities

Over the last decade, scholars have focused increasingly on youth-centered organized activities because they facilitate ahost of positive social and developmental outcomes (Lareau, 2003; Eccles and Barber, 1999; Eccles and Templeton, 2002;Larson and Kleiber, 1993; Larson et al., 2004; Feldman and Matjasko, 2005; Mahoney, 2000; Covay and Carbonaro, 2010).Specifically, research has documented that structured activities provide youth with opportunities to work cooperativelyas a team, build social and emotional skills, form valuable connections with adults, and interact with peers from differentsocial and ethnic backgrounds—all of which contributes to the development of non-cognitive skills valued by schools andwork environments (Dworkin et al., 2003; Larson, 2000). For example, Hansen et al. (2003) discovered that adolescentswho participated in organized activities reported that they had more experiences with problem solving and put forth moreeffort in activities than in required academic classes. These youth also disclosed that organized activities such as a service-learning leadership program in school helped them to manage anger, anxiety, and stress—key developmental traits that will

1 School context refers to those facets of the schooling environment that shape student experiences and outcomes, including school structure, composition,and climate (Lee and Bryk, 1989; Pong, 1998; Rumberger, 1995). We focus on school composition here because of the theoretical frameworks we use tounderstand the incorporation of immigrant youth in US schools.

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help youth to navigate their current and future educational, work, and personal lives. Past research has also shown that ac-tive membership in school-sponsored clubs and sports during middle and high school encourages higher levels of schoolattachment and academic achievement (Darling, 2005; Mahoney and Cairns, 1997; McNeal, 1995; Broh, 2002; Marsh,1992; Dumais, 2009; Lareau, 2003). The advantages also extend to adulthood, as studies using longitudinal data have doc-umented that involvement in extracurricular activities during high school is associated with higher levels of income, educa-tion, earnings, and political engagement, all else equal (McFarland and Thomas, 2006; Lleras, 2008; Gardner et al., 2008;Kaufman and Gabler, 2004).2

Less of the literature focuses on the factors encouraging youth participation in school-based extracurricular activities.Existing studies have emphasized the importance of socioeconomic status (SES), as children from low-income families areless likely to participate in lessons, organized activities, and clubs than children from affluent families (Lareau, 2003; Posnerand Vandell, 1999; Covay and Carbonaro, 2010; Dumais, 2006; McNeal, 1999). Studies have also found racial differences inparticipation in school-sponsored extracurricular activities (see Ingels and Dalton, 2008). For example, Dumais (2006) dis-covered that black and Hispanic children participated in extracurricular activities in kindergarten or first grade at lower ratesthan white children. When controlling for socioeconomic background, Covay and Carbonaro (2010) found similar resultsregarding racial differences in participation in organized activities among a nationally-representative sample of third-graders.

While findings from past research are valuable, the question remains whether immigrant youth are taking advantage ofextracurricular activities at the same level as their native peers3 and the extent to which school composition effects vary byimmigrant status.

2.2. School composition, educational outcomes, and immigrant youth

School composition has proven useful for understanding educational achievement patterns for youth. Students who at-tend schools with high-SES levels are more likely to be exposed to achievement-oriented social climates, social networksthat can provide useful resources and information, and other material benefits such as access to state-of-the-art computerlabs, advanced courses, and expansive extracurricular activities, which can translate into positive educational outcomes(Carbonaro, 1998; Conger et al., 1997; Hofferth et al., 1999). Conversely, attending schools without these resources can neg-atively affect the academic progress of youth. Though not always measured directly, proxies such as minority compositionand percent foreign-born, in addition to low SES, are thought to capture contextual disadvantage and have been important inexplaining academic achievement and dropout differences across schools (Lee and Burkam, 2002; Parcel and Dufur, 2001).

The frog-pond framework, developed to understand achievement-oriented outcomes, can help us to understand howschool composition might influence activity participation among immigrant youth. This framework posits that students’ aca-demic outcomes are a function of social comparison and evaluation processes (Davis, 1966; Marsh, 1987). Students evaluatethemselves relative to other students in their immediate school contexts, and while some contexts might provide objectiveadvantages for certain groups, they may also be associated with potential risks for others (Espenshade et al., 2005; Crosnoe,2009). For example, a low-income student who attends a high-income school will have access to resources, information, andsupport, but will likely rank lower in the social hierarchy, leading to negative self-perceptions and negative evaluations byothers. The more advantaged the student body is, the greater the social distance between the ‘‘average’’ student and thosewho come from lower-SES backgrounds, creating a context where students in the minority find themselves at a disadvan-tage. In support of this idea, recent studies have found that youth from underprivileged backgrounds perform at lower levelsin middle-class schools (Owens, 2010; Crosnoe, 2005, 2009; Portes and Hao, 2004).

Studies on immigrant youth generally support the idea that school contexts matter (see Crosnoe, 2005; Perriera et al.,2006; Portes and MacLeod, 1996, 1999; Ryabov and Van Hook, 2007), and school composition may be especially importantfor immigrant youth who come from predominantly low-income, minority backgrounds. These youth, who already have lowsocial status due to their class and race, may also lack English fluency and be unfamiliar with American norms and culture,further lowering their social status. In addition, past studies have suggested that racial minorities and other disadvantagedpopulations gain greater benefits from positive school organization (Lee and Smith, 1997). If this is the case, immigrantyouth ought to be more sensitive to the effects of school composition. Drawing upon the frog-pond framework, we expectthat in high-SES schools where there are fewer racial minority and immigrant students, immigrant minority youth will be ata disadvantage in terms of participation in extracurricular activities compared to the average student. This participation dis-advantage should be less pronounced in low-SES schools, where immigrant minority students are more like their peers interms of class and race. Finally, these youth should also have improved outcomes in schools surrounded by peers whoare more similar in regards to race and immigrant status.4

2 It is possible that participation in school-based extracurricular activities could have negative consequences for immigrant youth. These youth may beexposed to social norms that are not consistent with their cultural values or face peer pressure to engage in delinquent activity. While the vast majority of pastresearch concludes that participation in these activities has positive benefits for youth, it is still an empirical question whether immigrants and nativesexperience different returns to activity participation.

3 ‘‘Native’’ refers to third and later generations. We do not use ‘‘native-born’’ here because such a term could refer to second- or third-generation youth.4 This idea is also consistent with the selective acculturation pathway of segmented assimilation theory which posits that immigrant youth may perform

better in contexts when surrounded by peers who are similar in terms of immigrant status and provide social support.

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In contrast, the downward trajectory of segmented assimilation theory (Portes and Zhou, 1993) suggests that the ef-fects of school composition may work through a different process: even if immigrant youth find themselves in themajority, they will be at risk in the increasing presence of racial minority peers in low-income contexts. High concen-trations of racial minorities in schools should have detrimental effects on pro-social, achievement-oriented outcomesamong immigrant youth. Consistent with these ideas, Portes and MacLeod (1999) discovered that schools with higherpercentages of minority students were negatively associated with academic performance among second-generationimmigrants. In a study examining composition effects across generations, Ryabov and Van Hook (2007) found thatthe racial minority composition of the school had a negative effect on grades for foreign-born, but not native-born Lati-nos, providing further support for segmented assimilation theory. Thus, in contrast to the frog-pond hypothesis, we ex-pect that increasing percent minority in low-SES schools will be associated with lower participation outcomes amongimmigrant minority youth.

In the current paper, we test these hypotheses about the differential effects of school composition on extracurricularactivity participation among immigrant youth. With such a focus, we move beyond educational achievement to gain insightsinto the adaptation of immigrant youth in the school setting.

3. Data

We utilize data from the National Longitudinal Study of Adolescent Health (Add Health) to examine patterns of school-sponsored activity participation among immigrant and native youth. Add Health was compiled by the Carolina PopulationCenter at the University of North Carolina using a stratified random sample of over 170 US high schools and their feeder mid-dle or junior high schools. The initial in-school sample includes responses from 90,118 students collected at the school sitesbetween 1994 and 1995 (see Harris et al., 2009). A second, more extensive survey was administered in respondents’ homesto a sub-sample of 20,745 students from 132 schools in 1995. We focus on the 15,356 respondents who completed both thein-school and in-home surveys.5

Add Health is particularly useful for our purposes because it is one of the most comprehensive data sets on adolescentsand provides extensive measures of extracurricular activity participation. The data also represent a marked improvementfrom past surveys because they include large samples of immigrant and second-generation youth as well as native-bornyouth. We replaced missing values through multiple imputation after deleting observations that were missing sampleweights (n = 1821), as well as Native American, other race, and multiracial respondents due to their small sample sizes (com-bined n = 397).6 Our final analytical sample is comprised of 14,139 respondents from 125 schools.

3.1. Dependent variable

Extracurricular activity participation constitutes our dependent variable. Respondents were shown a list of 33 school-sponsored activities and prompted to mark any that they participated in or planned to participate in during the school year.7

We constructed two dichotomous variables to capture participation; the first was coded as 1 if respondents participated in anyclubs and the second was coded as 1 for participation in sports.8 Clubs include language, book, computer, vocational, and sub-ject-matter clubs; debate team, honors society, band, orchestra, chorus, drama, student council, newspaper, and yearbook.Sports include baseball/softball, basketball, cheerleading, field/ice hockey, football, soccer, swimming, tennis, track, wrestling,and volleyball. Because clubs and sports often represent distinct peer groups and status differences, and may even have differenteffects on social and educational outcomes (see Broh, 2002), we analyzed these activities separately.9

5 We are restricted to using the initial wave of Add Health because subsequent waves do not provide data on participation in school-sponsoredextracurricular activities.

6 We also use data from the Add Health Parents’ Survey in our analyses. Because 3125 cases did not have a participating parent or primary caregiver, weimputed the missing data. As a check, we compared results from models with and without the imputed data. Because the overall patterns were similar acrossthe two sets of models, we present models with the imputed data for the missing parent information.

7 Possible responses of either ‘‘marked’’ or ‘‘not marked’’ for each of the club and sport items resulted in zero missing observations. To test whether ‘‘notmarked’’ respondents were non-participators or missing observations, we utilized a final participation item included in the survey indicating if the respondentdid not participate in any activities. We assumed that respondents who did not mark any of the activity items and did not mark this final item were missingrather than non-participators. Sensitivity analyses in which these individuals were coded as missing revealed that our results were generally the sameregardless of how these ‘‘non-responses’’ were treated.

8 We considered alternative ways to operationalize the dependent variable. Add Health does not provide information on the frequency or intensity withwhich students participate in their chosen extracurricular activities, but we were able to model the number of activities as well as the breadth of participationacross club types such as art, academic, and leadership. In general, our results demonstrated the same patterns of participation when we used these differentmeasures. The main exceptions are in the breadth models, where first-generation Hispanics are no longer disadvantaged in high- or low-SES schools. Theseadditional analyses are available upon request.

9 We examined whether immigrant and racial groups participated in different types of clubs and sports, and found that very few differences across race andgeneration appeared in our data, suggesting that immigrants and natives are participating in the same school activities together and bolstering our claim thatschool-sponsored extracurricular activities are a place where immigrant minority youth interact with natives in a cooperative setting. Supplemental tablesavailable upon request.

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3.2. Immigrant generation and race/ethnicity

We determine immigrant status through the birthplaces of the respondent and his or her parents (see Harker, 2001; Perri-era et al., 2007; Keller and Tillman, 2008). Those born outside of the US with foreign-born parents are considered first-gen-eration immigrants, US-born respondents with at least one foreign-born parent are the immigrant second generation, andthose born in the US with two US-born parents are native (third or later generation). Respondents’ race is determined by fourmutually exclusive categories: White, Black, Hispanic,10 and Asian. We expect that participation will vary across both race andimmigrant generation. To capture this diversity, we combine the two measures to create 10 dichotomous race-immigrant gen-eration categories.11

3.3. School-level variables

To understand how school socioeconomic, racial, and immigrant composition affect activity participation, we includethree school-level measures based on aggregated student responses from the larger Add Health in-school sample. SchoolSES is a standardized mean scale constructed from two variables: the proportion of students with highly educated parents(college education or greater) and the mean level of parents’ income within each school (see Crosnoe, 2009; Portes andMacLeod, 1999; Pong and Hao, 2007).12 We stratify our sample based on school SES, estimating parallel models for above-and below-average SES samples respectively (we refer to them as high- and low-SES school contexts in the rest of the paper).Our predictions, based on the frog-pond framework and segmented assimilation theory, suggest that different processes takeplace in high- and low-SES contexts, potentially leading to discontinuities in the associations between race-immigrant gener-ation and activity participation. Thus, we analyze high- and low-SES contexts separately, providing a more nuanced understand-ing of how school contexts shape participation in extracurricular activities. We also use school-level SES as a control in ouranalyses to account for residual variation in school socioeconomic context within both groups of schools.

We measure school racial minority and immigrant composition with the summed percentage of blacks and Hispanics13

and the percentage of students born outside of the US, respectively. These measures capture the diversity within schools, whichmay attenuate social hierarchies that contribute to frog-pond effects in high-SES contexts or contribute to a ‘‘dangerous’’ schoolenvironment in low-SES contexts as suggested by segmented assimilation theory. We examine how these compositional factorscondition the association between race-immigrant generation and activity participation by including them in cross-levelinteractions.

3.4. Controls

All models control for gender, age, parental education, parental income, and language spoken at home. Because higher-achieving and more engaged students may be more likely to participate, we also include measures of grade point average(GPA) and school engagement. GPA is the mean of self-reported grades in English, math, history, and science ranging from0 to 4. School engagement is a mean scale combining three 5-category Likert-type items measuring whether the respondentfeels close to, happy in, and a part of his or her school.14

Previous research also identifies parents, especially immigrant parents, as important source of academic achievement andpossibly activity participation (see Kao and Tienda, 1995; Fuligni, 1997). We control for three parental influence variables.Parents’ expectations measures how disappointed the respondent’s parents would be if he/she did not graduate from col-lege.15 The measure ranges from 1 to 5, with higher values indicating higher expectations. Parental control is coded as 1 ifthe respondent does not make his or her own decisions about friendship choices, indicating that parents are influencing thesedecisions and exerting greater control over their children’s lives; coded as 0 if not. Parental involvement is coded as 1 if the

10 In the Add Health survey, respondents were asked: ‘‘are you of Hispanic or Latino origin?’’ We use the term ‘‘Hispanic’’ throughout the paper to refer tothose who marked yes to this question.

11 For black and white youth, we combine the first and second generations in the analysis because of small sample sizes.12 The income question was only asked in the Wave I in-home parental questionnaire, not in the larger in-school sample. Thus the aggregated measure was

constructed using the smaller pool of respondents who completed the at-home survey.13 Following Ryabov and Van Hook (2007), we do not include Asians as part of our measure of school minority composition. Even though Asians are

considered a racial minority group in the US who has experienced historical exclusion and contemporary discrimination, Asian Americans have been racializeddifferently than Latinos and Blacks— as a model minority (Hurh and Kim, 1989; Wong et al., 1998). On average, Asian Americans’ educational attainment andachievement have outstripped those of blacks and Latinos as well as whites, and Asian students attend relatively integrated schools. Thus, to include Asians aspart of our measure of school racial minority would not adequately capture the conditions predicted by the downward trajectory of segmented assimilationtheory. That said, ideally, we would stratify the sample and measure percent co-ethnic at the school level to test whether the presence of same-ethnicitystudents facilitates participation in extracurricular activities. However, stratifying the sample by ethnicity would result in a loss of power to detect relationshipsbetween the outcome and our primary independent variables. For the same reason, we chose not include percent co-race as a school-level variable. Analysesthat include percent co-racial at the individual level (not shown) indicate that it is not significantly associated with club or sports participation.

14 The scale has a Chronbach’s alpha value of 0.781, indicating high internal consistency. Additionally, principle components factor analyses in the sample as awhole and within race-immigrant generation subsamples indicate that the three items load onto a single latent factor.

15 We opted to use student’s beliefs about parents’ expectations in our analysis because the direct measure for parents’ expectations had a greater number ofmissing values and previous research shows a high correlation between parents’ and children’s expectations (see Hao and Bonstead-Bruns, 1998). We usemother’s expectations in most cases and father’s expectations when such information was missing.

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Table 1Full and SES-stratified sample means and proportions, Add Health, Wave I.

Sample full High SES Low SES

Activity participationClubs 53.34 55.9 51.13Sports 57.6 61.95 53.83

Race-immigrant statusWhite – 3rd 65.14 73.14 58.21White – 1st/2nd 3.51 5.03 2.2Black – 3rd 15.85 9.42 21.41Black – 1st/2nd 0.77 0.87 0.68Hispanic – 3rd 3.98 3.55 4.35Hispanic – 2nd 400 2.24 5.52Hispanic – 1st 2.46 1.06 3.66Asian – 3rd 0.54 1.01 0.14Asian – 2nd 1.65 1.90 1.43Asian – 1st 2.10 1.77 2.39

Control variablesFemale 50.34 49.23 51.31Age 14.84 14.92 14.76Language 6.67 4.3 8.73Parents’ education 2.89 3.27 2.57Income 8 8.83 7.28GPA 2.82 2.93 2.73School engagement 2.79 2.82 2.76Parents’ expectations 2.96 3.06 2.88Parent participation 38.69 45.25 33.01Parental control 15.48 9.66 20.51

School-level variablesSchool SES �0.04 0.76 �0.72Percent Minority 28.03 17.87 36.81Percent Immigrant 10.01 8.99 10.9

Level-1 N 14,140 6503 7637Level-2 N 125 58 67

160 D.G. Okamoto et al. / Social Science Research 42 (2013) 155–168

parent participates in the parent–teacher organization at their child’s school or in civic/social organizations in the local com-munity (coded as 0 if parents do not participate).

Table 1 presents the weighted means and proportions of the variables used in our models for the full sample. We alsocalculated means for high- and low-SES schools and as expected, low-SES schools have about 20% more immigrant studentsand twice the number of racial minorities than high-SES schools. In addition, third-generation whites comprise the majorityof the sample and are overrepresented at high-SES schools, while third-generation Blacks and all Hispanic generations areoverrepresented at low-SES schools. Second- and third-generation Asians are also overrepresented at high-SES schools. Addi-tionally, a higher percentage of youth in low-SES schools speak a language other than English at home.

4. Analytical technique

Add Health employs a two-stage sampling design in which students are nested within schools. Previous assessments ofextracurricular activity participation (and other outcomes related to schooling) often ignore the fact that students withinschools are likely to be more homogenous than students between schools. Ignoring this type of clustering of observationsviolates the regression assumption of independence, which may lead to biased and inefficient parameter estimates (Guoand Zhau, 2000; Raudenbush and Bryk, 2002).16

To deal with this issue, we use multilevel logistic regression models, which relax the assumption of independence bysimultaneously estimating separate individual- and school-level equations with unique error terms.17 The level-1 equationexpresses a linear relationship between individual characteristics and the log-odds of participation. The intercept is permittedto vary across schools and is conditional on the school-level variables included in the level-2 equation. All of the level-1 inde-pendent variables are centered around their group means and level-2 variables around their grand means, effectively removingcross-school variation from the individual-level predictors. This centering strategy ensures that the level-1 regression slopeswill provide pure estimates of the within-school relationship between individual characteristics and the outcome that are ro-

16 See Guo and Zhao (2000) for an example of the bias that occurs when the hierarchical nature of Add Health data is not accounted for by standard logitmodels.

17 In logistic models, individual-level variance is not estimated, but is assumed to be fixed in proportion to the estimated probability of event occurrence(Raudenbush and Bryk, 2002).

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Table 2Multi-level logistic regression models predicting club participation by school SES.

High-SES Low-SES High-SES Low-SESIndependent variables Model 1 Model 2 Model 3 Model 4

White – 1st/2nd 0.11 (0.15) 0.11 (0.21) 0.11 (0.18) 0.10 (0.22)Black – 3rd �0.58** (0.19) �0.26* (0.10) �0.33* (0.17) �0.18 (0.11)Black – 1st/2nd �0.19 (0.24) �0.37 (0.34) 0.06 (0.24) �0.52 (0.40)Hispanic – 3rd �0.47** (0.18) �0.06 (0.20) �0.17 (0.20) 0.06 (0.23)Hispanic – 2nd �0.68*** (0.14) �0.35+ (0.19) �0.27 (0.19) �0.13 (0.20)Hispanic – 1st �0.80* (0.34) �0.71** (0.25) �0.71+ (0.41) �0.56* (0.29)Asian – 3rd 0.37 (0.23) 0.54 (0.51) 0.59* (0.30) 0.42 (0.53)Asian – 2nd 0.36+ (0.20) 0.44* (0.23) 0.44+ (0.24) 0.38+ (0.21)Asian – 1st 0.19 (0.25) �0.21 (0.37) 0.18 (0.32) 0.12 (0.35)

Female 0.96*** (0.08) 0.92*** (0.07)Age 0.12 (0.02) 0.05 (0.04)Language 0.17 (0.25) 0.12 (0.17)Parents’ education 0 15*** (0.04) 0 13*** (0.03)Income 0.00 (0.02) 0.00 (0.02)GPA 0.54*** (0.25) 0.52*** (0.05)School engagement 0 19*** (0.04) 0.13** (0.04)Parents’ expectations 0.09* (0.03) 0.06* (0.02)Parent participation 0.43*** (0.08) 0.34*** (0.09)Parental control �0.05 (0.12) �0.21** (0.07)

School percent immigrant �0.00 (0.01) 0.01 (0.01)School percent minority 0.01** (0.00) 0.00 (0.00)School SES 0.41*** (0.10) 0.22 (0.19)

Intercept 0.20** (0.06) 0.00 (0.08) 0.30*** (0.07) 0.04 (0.09)School-level variance 0.02*** 0.32*** 0.20*** 0.40***

Log likelihood �4551.33 �5337.58 �4235.79 �4907.18AIC 1.40 1.40 1.28 1.29

Note: For high-SES schools, level-1 N = 6503 and level-2 N = 58. For low-SES schools, level-1 N = 7636 and level-2 N = 67. Robust standard errors inparentheses. Log likelihoods were calculated by taking the average log likelihood across three imputed samples.* p < 0.05, ** p < 0.01, *** p < 0.001, + p < 0.10.

D.G. Okamoto et al. / Social Science Research 42 (2013) 155–168 161

bust to omitted school-level factors (Raudenbush and Bryk, 2002; Enders and Tofighi, 2007). Without centering, level-1coefficients represent a mix of both individual and school variation that is difficult to interpret and subject to omitted variablebias.18

The multilevel approach also permits exploration of how school-level factors moderate the relationship between individ-ual characteristics and the dependent variable. Using cross-level interactions, we can determine whether variation in schoolcomposition shapes participation differences across race-immigrant generations. The slope parameters are a function of themean race-immigrant effect across schools plus the effects of school-level moderators.

We estimate weighted multilevel logistic regression models for high- and low-SES schools and test (1) whether immi-grant minority students experience relative disadvantage in activity participation compared to the average student in high-and low-SES schools; and (2) whether high concentrations of minorities or immigrants represent positive or detrimentalcontexts for immigrant students.19 We begin with reduced models that include race-immigrant generation categories onlyand then adjust for individual- and school-level variables before introducing cross-level interactions to examine how the effectsof school composition vary by race-immigrant status.

5. Results

5.1. Multilevel models

Our results from the first set of models in Table 2 indicate that race-immigrant generation group differences in club par-ticipation are for the most part, larger and more pronounced in high-SES compared to low-SES schools (Models 1 and 2). Thispattern of results is consistent with predictions from the frog-pond framework, as immigrant youth appear to be less sociallyintegrated in high-SES school contexts where they are in the minority in regards to SES, race, and immigrant status.

18 The interpretation of the intercept is sensitive to centering strategies. Without centering, the intercept can be interpreted as the mean log-odds ofparticipation in a typical school for an individual who has a value of 0 for all of the individual variables. When the individual-level variables are centered aroundtheir within-school means, however, the intercept becomes the mean log-odds of participation for the average student in the school. Consequently, theinterpretation of slope coefficients is also relative to the average student in the school under mean-centering. For example, in such a scenario, an effect for afemale indicator would no longer be comparable to males, but rather the average student in the school.

19 All estimates use sample weights to account for the complex survey design of Add Health to ensure that our results reflect the national population.

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Table 3Multi-level logistic regression models predicting sports participation by school SES.

High-SES Low-SES High-SES Low-SESIndependent variables Model 1 Model 2 Model 3 Model 4

White – 1st/2nd 0.10 (0.20) �0.11 (0.27) 0.13 (0.20) �0.16 (0.29)Black – 3rd 0.04 (0.20) 0.44*** (0.13) 0.35 (0.23) 0.64*** (0.12)Black – 1st/2nd 0.50 (0.36) 0.14 (0.28) 0.85* (0.35) 0.29 (0.26)Hispanic – 3rd �0.45** (0.16) 0.02 (0.15) �0.36* (0.17) 0.08 (0.16)Hispanic – 2nd �0.18 (0.19) �0.29* (0.13) �0.13 (0.21) �0.04 (0.18)Hispanic – 1st �0.73* (0.37) �0.19 (0.23) �0.41 (0.45) 0.19 (0.27)Asian – 3rd 0.05 (0.27) �0.13 (0.49) 0.03 (0.29) �0.18 (0.46)Asian – 2nd �0.15 (0.22) 0.12 (0.25) � 0.12 (0.23) 0.07 (0.26)Asian – 1st �0.67** (0.21) �0.11 (0.28) �0.52* (0.26) �0.22 (0.335)

Female �0.47*** (0.08) �0.37*** (0.06)Age �0.12*** (0.03) �0.15*** (0.03)Language �0.01 (0.22) �0.09 (0.20)Parents’ education 0.06+ (0.03) 0.07+ (0.04)Income 0.06* (0.03) 0.04* (0.02)GPA 0.19*** (0.06) 0.14** (0.05)School engagement 0.34*** (0.05) 0.28*** (0.04)Parents’ expectations 0.04* (0.03) 0.08* (0.03)Parent participation 0.19* (0.07) 0.32*** (0.07)Parental control 0.03 (0.12) �0.01 (0.08)

School percent immigrant �0.00 (0.01) 0.01 (0.01)School percent minority 0.01* (0.00) 0.00 (0.00)School SES 0.41** (0.13) 0.14 (0.24)

Intercept 0.53*** (0.08) 0.30* (0.12) 0.55*** (0.08) 0.28* (0.11)School-level variance 0.37*** 0.50*** 0.31*** 0.48***

Log likelihood �4350.00 �5324.20 �4154.52 �5102.70AIC 1.34 1.40 1.28 1.34

Note: For high-SES schools, level-1 N = 6503 and level-2 N = 58. For low-SES schools, level-1 N = 7636 and level-2 N = 67.Robust standard errors in parentheses. Log likelihoods were calculated by taking the average log likelihood across three imputed samples.* p < 0.05, ** p < 0.01, *** p < 0.001, + p < 0.10.

162 D.G. Okamoto et al. / Social Science Research 42 (2013) 155–168

Specifically, we find that Hispanics are the most disadvantaged. In the first generation, Hispanics are more than 50% lesslikely than the average student to participate in clubs across high- and low-SES contexts. By the third generation, the activityparticipation gap appears to have closed in low-SES schools, but in high-SES schools, Hispanics are 37% less likely to be in-volved in school clubs than the average.20 In contrast, Asians are on par with the average in regards to club participation. Infact, second-generation Asians outpace the average across high- and low-SES school contexts, by 43% and 55% respectively (Ta-ble 2, Models 1 and 2), which suggests a pattern of second-generation advantage (Kasinitz et al., 2008). In contrast to Asians andHispanics, immigrant whites and blacks do not differ from their peers in the odds of club participation in high- or low-SESschools. Native blacks, however, display lower levels of club participation across both school types, but particularly in high-SES schools. In Table 3, which displays our results for sports participation, the same general patterns of improved performancein low-SES compared to high-SES schools appear for each racial group (Models 1 and 2).

The inclusion of background characteristics, parental variables, selection and school-level factors in the models (Tables 2and 3, Models 3 and 4) accounts for many of the race-immigrant status effects. Surprisingly, some group differences remain.Notably, first-generation Hispanics are still significantly less likely than their peers to participate in clubs across SES schoolcontexts all else equal,21 and in high-SES schools, the third generation has lower odds of participating in sports. Asians continueto experience a second-generation advantage in club involvement, and a third-generation advantage appears in high-SESschools. Native and immigrant blacks remain less likely to participate in school clubs and sports in high-SES schools.22

20 We exponentiated the coefficients, subtracted by 1, and multiplied by 100 to calculate the percent that Hispanics were less likely to participate in schoolclubs in high-SES (e�.80 � 1 � 100 = �55.0) and low-SES (e�.71 � 1 � 100 = �50.8) schools.

21 In models not shown here, we find that the inclusion of GPA and school engagement fully explains the negative second-generation Hispanic effect and thatparents’ education and income provide the most explanatory power over the negative third-generation Hispanic effect. We also note that our results did notsubstantively change when we included the count of club and sports activities to control for the fact that not all schools offer the same opportunities forparticipation.

22 To further understand the patterns of club participation, we estimated models predicting the types of clubs in which immigrant youth participate (availableupon request). We found that in low-SES schools, immigrant minority youth do not look different from their peers in academic, arts, and leadership clubparticipation. Differences emerge in high-SES school contexts. Second-generation Asians were more likely to participate in academic and leadership clubs andthird-generation Asians were more likely to participate in art clubs. First-generation Hispanics were less likely to participate in art clubs, but equally likely toparticipants in academic and leadership clubs. Third-generation Hispanics were at a disadvantage in art clubs. Whites and blacks were equally likely to beactive members of all club types in high-SES schools.

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Table 4Multi-level logistic regression models with interactions between race-immigrant status and school percent minority by type of activity and school SES.

Clubs Sports

High SES Low SES High SES Low SESIndependent variables Model 1 Model 2 Model 3 Model 4

White – 1st/2nd 0.10 (0.18) 0.01 (0.16) 0.18 (0.21) �0.22 (0.34)Black – 3rd �0.39* (0.18) �0.21+ (0.11) 0.20 (0.31) 0.63*** *(0.13)Black – 1st/2nd �0.30 (0.35) 0.23 (0.52) 1.66** (0.59) 0.22 (0.35)Hispanic – 3rd �0.12 (0.19) �0.25 (0.20) �0.36* (0.17) 0.01 (0.17)Hispanic – 2nd �0.31 (0.21) �0.44 (0.27) 0.22 (0.24) �0.11 (0.23)Hispanic – 1st �0.62 (0.44) �0.61 (0.39) �0.26 (0.49) 0.47 (0.41)Asian – 3rd 0.67*** (0.19) 0.09 (0.70) 0.11 (0.35) �0.97+ (0.52)Asian – 2nd 0.34 (0.22) 0.47* (0.23) 0.02 (0.23) 0.14 (0.27)Asian – 1st 0.16 (0.33) �0.04 (0.48) �0.50+ (0.27) �0.26 (0.31)

School % Minority 0.01** (0.00) 0.00 (0.00) �0.01* (0.00) �0.00 (0.00)

Interactions with % MinorityWhite – 1st/2nd �0.00 (0.01) �0.01 (0.01) 0.01 (0.01) �0.01 (0.01)Black – 3rd 0.02* (0.01) �0.00 (0.01) 0.00 (0.01) 0.00 (0.01)Black – 1st/2nd 0.03** (0.01) �0.04** (0.02) �0.03* (0.01) 0.00 (0.01)Hispanic – 3rd 0.02 (0.01) �0.03*** (0.01) �0.00 (0.01) 0.01 (0.01)Hispanic – 2nd 0.02** (0.01) 0.01 (0.01) �0.01 (0.01) 0.00 (0.01)Hispanic – 1st �0.00 (0.00) �0.01 (0.05) �0.04 (0.03) �0.01 (0.01)Asian – 3rd �0.02 (0.02) 0.05 (0.04) �0.01 (0.02) 0.07** (0.03)Asian – 2nd 0.03*** (0.01) �0.02* (0.01) �0.02+ (0.01) �0.01 (0.02)Asian – 1st 0.03* (0.02) �0.02 (0.02) �0.01 (0.01) 0.00 (0.01)

Intercept 0.29*** (0.04) 0.04 (0.09) 0.55*** (0.08) 0.27* (0.11)Log likelihood �4127.67 �4889.91 �4157.66 �5036.82AIC 1.28 1.51 1.10 1.33

Note: For high-SES schools, level-1 N = 6503 and level-2 N = 58. For low-SES schools, level-1 N = 7636 and level-2 N = 67.Robust standard errors in parentheses. Log likelihoods were calculated by taking the average log likelihood across three imputed samples.Individual-level control variables included but not shown here.* p < 0.05, ** p < 0.01, *** p < 0.001, + p < 0.10.

D.G. Okamoto et al. / Social Science Research 42 (2013) 155–168 163

Among school-level variables, we find that school SES and minority concentration explains some of the school-level var-iation in participation rates across high-SES schools, but SES, racial, and immigrant school composition do little to explain thevariation in low-SES schools.23

5.2. School racial and immigrant concentration

So far, our results indicate that in high-SES schools, disparities in extracurricular activity participation are more pro-nounced. The effects generally indicate a participation disadvantage for immigrant and minority youth, particularlyamong Hispanics and blacks, which suggests that social ranking and comparison processes affect their participation inextracurricular activities. We hypothesized that these processes are shaped not only by SES, but also by race and immi-grant status, in which case immigrant minority youth should be disadvantaged in majority white and non-immigrantcontexts. We expect then, that as the presence of minority and immigrant students increases, participation in schoolclubs and sports will increase as well. Moreover, the positive effect of more minority and immigrant students mightbe stronger in high-SES compared to low-SES schools, where immigrant youth are most dissimilar to their peers. Onthe other hand, the increasing presence of racial minorities in low-SES schools could present additional risk factorsfor immigrant youth, leading to decreased club and sports participation which are considered pro-social forms of schoolengagement.

To test these ideas, we estimated a series of cross-level interactions, which are presented in Tables 4 and 5.24 Several inter-esting patterns emerge. Consistent with the frog-pond hypothesis, as percent racial minority increases in high-SES schools, theprobability of club participation rises for many race-immigrant status groups (Table 4, Model 1). We also discover that in low-SES schools, the probability of involvement in school clubs does not change or declines when racial minority concentration in-creases, which supports segmented assimilation theory (Table 4, Model 2).

23 Since our models are group-mean centered, the addition of contextual variables is not expected to mediate the effects of the individual-level variables.Thus, while school factors are associated with the mean level of participation across schools, in these models they do not contribute to the within-schoolrelationship between race-immigrant generation and participation.

24 Ideally, we would control for other school factors while testing the interactions, but high correlations among the school-level variables combined withrelatively low levels of slope variance led to unstable estimates, so we opted to test each interaction separately, as suggested by Raudenbush and Bryk (2002).

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Table 5Multi-level logistic regression models with interactions between race-immigrant status and school percent immigrant by type of activity and school SES.

Clubs Sports

High SES Low SES High SES Low SESIndependent variables Model 1 Model 2 Model 3 Model 4

White – 1st/2nd 0.12 (0.19) 0.07 (0.21) 0.11 (0.21) �0.18 (0.30)Black � 3rd �0.29+ (0.17) �0.24* (0.11) 0.45+ (0.26) 0.62*** (0.11)Black – 1st/2nd �0.21 (0.31) �0.66 (0.41) 1.00* (0.41) 0.34 (0.28)Hispanic – 3rd �0.17 (0.20) 0.33 (0.22) �0.35* (0.17) 0.01 (0.17)Hispanic – 2nd �0.31 (0.21) �0.35 (0.25) 0.12 (0.24) �0.00 (0.23)Hispanic – 1st �0.89+ (0.47) �0.82* (0.37) 0.09 (0.58) 0.33 (0.37)Asian – 3rd 0.31 (0.43) 0.30 (0.50) �0.07 (0.48) 0.03 (0.47)Asian – 2nd 0.59+ (0.32) 0.70* (0.28) 0.10 (0.24) �0.05 (0.28)Asian – 1st 0.56 (0.43) �0.30 (0.53) �0.66+ (0.38) �0.27 (0.36)

School % Immigrant �0.00 (0.01) �0.01 (0.01) �0.01 (0.01) �0.02 (0.02)

Interactions with % ImmigrantWhite – 1st/2nd �0.02 (0.01) �0.01 (0.03) 0.01 (0.01) �0.02 (0.04)Black – 3rd �0.02* (0.01) �0.02+ (0.01) 0.06+ (0.03) �0.01 (0.01)Black – 1st/2nd 0.01 (0.02) 0.03 (0.03) �0.04 (0.03) �0.02 (0.02)Hispanic – 3rd �0.01 (0.02) �0.07** (0.02) �0.02 (0.02) 0.01 (0.02)Hispanic – 2nd �0.00 (0.01) 0.01 (0.02) �0.01 (0.01) �0.01 (0.02)Hispanic – 1st 0.00 (0.02) 0.01 (0.02) �0.06 (0.04) �0.01 (0.02)Asian – 3rd 0.06 (0.06) 0.01 (0.07) �0.02 (0.08) �0.04 (0.04)Asian – 2nd �0.03+ (0.02) �0.06** (0.02) �0.05*** (0.01) 0.02 (0.03)Asian – 1st �0.03* (0.01) 0.00 (0.04) �0.00 (0.01) 0.00 (0.02)

Intercept 0.30*** (0.07) 0.04 (0.09) 0.55*** (0.08) 0.27* (0.11)Log likelihood �4132.71 �4894.83 �4156.29 �5112.69AIC 1.28 1.51 1.10 1.35

Note: For high-SES schools, level-1 N = 6503 and level-2 N = 58. For low-SES schools, level-1 N = 7636 and level-2 N = 67.Robust standard errors in parentheses. Log likelihoods were calculated by taking the average log likelihood across three imputed samples.Individual-level control variables included but not shown here.* p < 0.05, ** p < 0.01, *** p < 0.001, + p < 0.10.

164 D.G. Okamoto et al. / Social Science Research 42 (2013) 155–168

Interestingly, we find an opposite pattern when we turn to sports: as the percent minority increases, the probability ofparticipation decreases in high-SES schools and rises in low-SES schools (Table 4, Models 3 and 4). The effects of minoritypeers in school contexts identified by the frog-pond and segmented assimilation frameworks do not seem to hold for sports.Additionally, our results show that that percent immigrant operates differently from percent minority, depressing the prob-ability of club and sports participation across both high- and low-SES schools (Table 5, Models 1–4).

We display the interaction effects as predicted probabilities25 in Fig. 1, which allows us to compare the trajectories of a‘‘typical’’ youth from different race-immigrant groups to the average student in high- and low-SES schools.26 We note thatthe charts present scenarios that reflect the actual racial and immigrant compositions of schools in our data.27

In general, the charts presented in Fig. 1 show that immigrant minority youth are more sensitive to shifts in racial andimmigrant composition compared to the average student. In the first row of charts (Row 1), we see that when immigrantblacks attend high-SES schools with 30% or more minority students, they thrive and have higher predicted probabilitiesfor club participation than the average student. Hispanics in high- and low-SES schools also benefit from the presence ofmore minority students, and as expected, the benefits were higher in high-SES schools. Some of the most dramatic differ-ences appear between the average student and immigrant blacks for club and sports participation (Rows 1 and 2): percentminority is associated with a steeper rise in club participation and a greater decline in sports participation for black immi-grants compared to the average student, though the starting points differ for the two groups. There is also a notable declinefor second-generation Asians compared to the average student when percent immigrant increases within the school setting(Row 4).

Fig. 1 also shows us where crossover points are—the percent minority or immigrant when participation in low-SESschools becomes higher than in high-SES schools (and vice versa)—for different race-immigrant groups. For example, in

25 Each predicted probability trajectory was calculated by setting all controls equal to their low- or high-SES sample means. The predicted probability for theaverage student was obtained by setting all of the race-immigrant indicators to their sample means.

26 We created histograms and box plots to examine the distribution of our data in regards to percent minority and percent immigrant in high- and low-SESschools. Three schools were outliers for percent immigrant (over 40%) and four high-SES schools are outliers for percent minority (over 60%). As a check, we re-estimated models without these schools and found the same general pattern of results for the interaction terms regarding significance, magnitude, anddirection of effects, which gives us confidence that our results are sound.

27 In other words, some probability lines may be shorter or longer than others to reflect the realities of the sample data.

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0

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High SES Schools

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Fig. 1. Predicted probabilities of club and sports participation by school SES and percent minority/immigrant for average student and various race-immigrant status groups. Note: Predicted probability trajectories are drawn to reflect values realized for each race-immigrant category within each sample.Some lines may not extend to the full sample maximum of 100% minority and 60% immigrant.

D.G. Okamoto et al. / Social Science Research 42 (2013) 155–168 165

the second row of charts displaying predicted probabilities for sports participation in schools with varying concentrations ofminority students (Row 2), participation is higher in low-SES schools when percent minority exceeds 50 for the average stu-dent, 80% for immigrant blacks, and 30% for second-generation Asians, suggesting that minority concentration at these levelsprovide a positive context for immigrant youth. We note that these school scenarios apply to one-quarter of the black immi-grant sample and one-third of the Asian second-generation sample.28 In regards to the immigrant composition of schools,involvement in clubs and sports is greater in low-SES schools for second-generation Asians when percent immigrant exceeds40% and 20% respectively (Rows 3 and 4). In our sample, the majority of second-generation Asians in low-SES schools (81%)attend schools that are 20–30% immigrant.

Overall, the charts presented in Fig. 1 indicate that while most youth have higher probabilities of extracurricular activityparticipation in high-SES schools, participation is contingent on the presence of minority and immigrant students.

6. Discussion and conclusion

Immigrant and second-generation youth are a growing population in the US, yet there is limited knowledge about theirintegration into the school setting beyond academic measures such as educational achievement, attainment, and dropout.We focus on student involvement in school-sponsored extracurricular activities as a way to examine the social incorporation

28 A table with the distribution of groups across school percent minority and immigrant deciles is available upon request.

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166 D.G. Okamoto et al. / Social Science Research 42 (2013) 155–168

of immigrants within American schools, and investigate how school context shapes patterns of club and sports participationacross different racial and immigrant groups. Our analysis indicates that (1) disparities in extracurricular activity participa-tion are more pronounced in high-SES schools, indicating a participation disadvantage for immigrant and minority youth,particularly among Hispanics and blacks; (2) youth have improved outcomes in high-SES schools when surrounded byminority but not immigrant peers, suggesting that social hierarchy and exclusion processes operate on the basis of SESand race, but not immigrant status; and (3) the increasing presence of minority students has differing effects for school clubsand sports. We elaborate on these findings below.

We expected that immigrant minority youth would be disadvantaged relative to the average student in high- comparedto low-SES schools, all else equal, and our results generally supported this finding. In high-SES schools, immigrant youth arelikely to be less similar to their peers in terms of socioeconomic, race, and immigrant status, and as suggested by the frog-pond hypothesis, social comparison and ranking processes contribute to lower levels of social integration of immigrantyouth into the school setting via extracurricular activities. Among all immigrant groups, Hispanics were the mostdisadvantaged.

We also expected that immigrant minority youth – especially those in high-SES school settings – would experience gainsin activity participation as the minority presence increased in their school settings. What we found was that the effect ofminority concentration differed across SES school contexts for club and sports participation. An increasing percentage ofminority students seemed to ameliorate social status differences in high-SES schools, boosting the likelihood of club involve-ment among immigrant minority youth. These youth were better integrated into their school settings through their partic-ipation in clubs when there were fewer non-minority students.

In low-SES schools, minority concentration depressed participation in school clubs among immigrant minority youth.Parents of these youth may steer their children away from school-related activities if they perceive that low-SES, high minor-ity schools do not represent an enriching afterschool context and may even have detrimental influences. This explanation iscommensurate with segmented assimilation theory which proposes that such contexts hinder the upward mobility of thechildren of immigrants, and finds support in research on school context and immigrant academic achievement.

But these same explanations do not hold for the patterns associated with sports, where percent minority has the oppositeeffect, decreasing sports participation in high-SES schools and boosting it in low-SES schools. It could be that high-SESschools recruit or attract talented minority athletes whose presence diminishes the odds that the average student (who islikely to be white) will be successful in school sports. Alternatively, minority youth who attend high-SES schools may comefrom families that emphasize academics over sports, contributing to a school climate that favors academically-related extra-curricular activities. In regards to the patterns we find in low-SES schools, it is possible that as the minority concentrationincreases, the status of athletes rises. Past research demonstrates that youth who have low levels of social, cultural, and edu-cational capital are more likely to participate in sports (Eitle and Eitle, 2002), suggesting that sports is viewed as an attain-able path to mobility. Further research is needed to better understand these differing patterns of club and sportsparticipation and the mechanisms through which the presence of minority students affects these outcomes.

As for the immigrant composition of schools, we extended the frog-pond framework and expected that immigrant youthwould perform better and participate in school activities at higher levels if they attended schools with other immigrantyouth. We did not find support for this hypothesis, which suggests that social comparison processes do not operate onthe basis of immigrant status. If they did, the greater presence of immigrant students should have tempered social statusdifferences and increased participation. Instead, some racial minority and immigrant groups were disadvantaged by thepresence of other immigrant youth across school SES and activity type. It may be that schools with high percentages of for-eign-born students impede linguistic assimilation (see Bean and Stevens, 2003), which is likely to have negative effects onother types of assimilation within the school setting, such as participation in school clubs and sports, some of which mayrequire English fluency. But the negative effects were also seen for native blacks and Hispanics. The increasing concentrationof immigrants within schools could contribute to greater levels of social distance between foreign-born and native groups,further impeding participation for racial minority groups.

In general, white immigrants appear to prosper in high-SES schools, irrespective of minority presence, while Asian, black,and Hispanic immigrants are sensitive to the interaction of minority concentration and school SES. For these groups, theprobability of club participation tends to be highest in high-SES schools with sizable minority populations. The implicationis that racially diverse, relatively high-SES schools are the most favorable contexts for the social integration of immigrantminority youth as well as third- and later-generation blacks and Hispanics.29

While we find evidence that racial, SES, and immigrant composition matter for understanding immigrant and minorityyouth participation in extracurricular activities, these measures could simply be proxy measures of other aspects of schoolcontext such as teacher quality and teachers’ expectations for students rather than a process of social ranking and compe-tition which leads to disparities in the social hierarchy within schools and achievement-oriented outcomes. In other words,school composition could influence student outcomes through a contextual rather than compositional school-level effect.While we do not have evidence to bear on the mechanisms at work, case studies suggest that social ranking processes withinschools exist and that immigrants are marked by their racial status (see Crosnoe, 2009; Jimenez, 2008). For example, a recent

29 This is consistent with research by Crosnoe (2005) which found that Hispanic youth performed well academically in schools with moderate SES and someHispanic teachers.

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ethnographic study of a racially diverse high school in San Francisco revealed that immigrant students experienced exclusionand isolation because of their lack of English language fluency and differing racial status from the majority group (Olson,2008). Many white students did not include newcomers as part of the social world of the school setting and racial groupboundaries were heavily policed by students, teachers, and staff, suggesting that social ranking processes occur on the basisof race and immigrant status. Interestingly, this study found that extracurricular activities were one of the few outlets thatprovided a rationale for students to mix by race, skin color, and immigrant status.

Our research provides an important first step and improved understanding of immigrant youth incorporation into theschool setting. Future assessments of extracurricular activity participation should utilize longitudinal data to firmly establishcausal patterns. It would also be useful to predict other measures of participation, such as the amount of time spent in activ-ities, and to examine whether immigrant youth receive social and economic returns to participation in school activities com-pared to their native peers. Finally, qualitative research which focuses on interviews and observations of immigrant youth intheir school settings can provide important insights which our models cannot capture, such as what immigrant youth expe-riences are like in school clubs and sports, what they learn from their native peers within activity settings, how they makedecisions about whether to participate, and how they and their parents view these activities in relation to their academicschool work. Such research will help to provide a more complete picture of immigrant youth adaptation in school settings.

Overall, the different patterns of activity participation we find have implications for immigrant integration in the schoolsetting, as well as for differential skill development and access to higher education across racial and immigrant groups. Thisresearch also highlights the complex interplay between race and immigrant generation, and calls for future research thatexamines how racial, socioeconomic, and immigrant composition interact to shape adolescent outcomes.

Acknowledgement

This research is funded by a William T. Grant Foundation Scholars Award to the first author. We thank Erin Hamilton, BobFaris, Grace Kao, Kim Shauman, Elizabeth Vaquera, and members of the Power and Inequalities Workshop at UC Davis fortheir comments on earlier drafts of this paper.

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