Choice and Circumstance: Social Capital and Planful Competence in the Attainments of the ‘one-and-a-half’ Generation*

by

John Hagan, Ronit Dinovitzer and Patricia Parker

 

*Order of authorship does not reflect seniority nor priority. This research was supported by a grant from the Center for Research on Immigration and Settlement.

The study of educational attainment has been characterized by two very different, yet important modes of inquiry; the first tends to focus on structural determinants, while the second is a more individual-level examination of the factors differentiating successful students from their less successful counterparts. While structural determinants such as parental socioeconomic status have proved to be strong determinants of educational attainment, Bourdieu and Passeron ([1964] 1979) have argued that students’ educational attainment should not be conceived as ‘mechanically determined’(p.25). In other words, despite the strong influence of social structure, human agency and the power of choice remain. Clausen’s (1991) work on the ‘planful competence’ of adolescents has illuminated the importance of human agency inherent in all decision-making. Much of the research in this area, however, has not integrated these two modes of inquiry, providing a somewhat limited perspective on an adolescent’s journey through the educational system. In a recent article suitably titled "History and Agency in Men’s Lives", Shanahan, Elder and Miech (1997) have pursued this integrative approach, examining both individual choices and structural factors in assessing educational attainment.

This study examines the educational attainment of immigrant youth in a Canadian suburb focussing on the determinants of their educational success; these immigrant children can be referred to as the "one-and-a-half generation" (Zhou 1997; Rumbaut 1991). Most Canadian studies have not jointly examined structural and individual-level factors in analysing the educational attainment of native-born and immigrant youth, probably because most of these studies rely on census data. These studies are typically descriptive, and focus on structural determinants of the educational success of various ethnic groups, or the comparative success of foreign-born Canadians (Hou and Balakrishnan 1996; Geschwender and Guppy 1995; Kalbach and Kalbach 1995; Shamai 1992; Jones 1987). In an effort to better understand factors that mediate the relationship between structural variables and educational attainment, several Canadian studies have drawn on sample surveys (Bellamy 1993; Krahn and Lowe 1991; Richmond 1986), but few of these studies have distinguished the experiences of immigrant youth (but see Anisef 1975). Furthermore, data from the General Social Survey have been used to explore a variety of individual-level factors related to educational attainment (Anisef and Johnson 1993). However, these studies are more empirically than conceptually driven, and therefore tend to remain insufficiently theorized. The result is that we do not yet have a coherent theoretical explanation for the educational attainment of immigrant youth (c.f. Portes 1997). Finally, few studies integrate both structural-level and individual-level determinants, and thus only explain part of the complex social process of immigrant educational attainment (but see Shanahan, Elder and Miech 1997).

The Educational Attainment of Canadian Immigrants

Canadian research on educational attainment has focussed mainly on ethnicity rather than immigration status (Shamai 1992; Herberg 1990), often emphasizing a multidimensional definition of ethnicity (cf. Kalbach and Kalbach 1995). While this has provided important insights into ethnic stratification in Canada, the task remains of separating the attainments of foreign-born and native-born Canadians. As Geschwender and Guppy (1995) note, "[t]he effect of ethnicity on educational attainment is thus confounded with migration histories" (p.69), perhaps "mask[ing] inequalities in attainment if foreign-born ethnics have high attainments while native-born ethnics are less successful" (p.69). Despite these limitations, prior Canadian research has uncovered some important determinants of educational attainment for immigrant adolescents.

Based on a survey in the Toronto metropolitan census area, Richmond (1986) found that immigrants of non-UK/US origin exhibited "considerable upward mobility and achievement in terms of education and qualifications" (p.87). This finding was generally replicated by other researchers. For instance, studies have found that minority groups who immigrated mostly since 1970 have had higher educational attainments than the national average (Hou and Balakrishnan 1996: 311); that for most minority groups, immigrants to Canada before the age of 10 have achieved parity or have surpassed British-Canadians in terms of educational attainment (Hou and Balakrishnan 1996); that among European immigrant groups overall education levels differ markedly, though immigrants who arrive at an early age tend to attain significantly higher education levels than those who immigrate at later ages (Hou and Balakrishnan 1996); and that those who immigrate at a young age tend to attain higher educational status than older immigrants (Kalbach and Kalbach 1995). As a result, age at immigration has become a focal point for many such studies (Jones 1987; Boyd 1985; Kalbach and Kalbach 1985; Inbar 1977), with Statistics Canada adding an "age at immigration" variable to the Census of Canada in the early 1980s (Kalbach and Kalbach 1995). Investigation of the relationship between age at immigration, acculturation, and socioeconomic integration has raised important concerns regarding ethnic connectedness and educational achievement: as Kalbach and Kalbach (1995) conclude, "the evidence to date still suggests that being more ethnic, regardless of origin, presents more obstacles to educational and socioeconomic status achievement than being less ethnically oriented and committed" (p.31).

While the majority of Canadian research has centred on descriptive analyses of who succeeds, or the distilling of structural determinants of educational attainment (e.g. age at immigration), sample survey research has the potential of further revealing individual-level determinants of success. One such study was conducted by Anisef (1975), who found that foreign-born students, or students whose father was foreign-born, were more likely to plan for higher education than native-born students; these students, for instance, were more likely to plan to attend university or colleges of applied arts and technology (p.132). Furthermore, corroborating the success of ethnic groups based on census-based studies, Anisef (1975) found that foreign-born students, or students whose father was foreign-born, had higher grades in high school. Similarly, results from the 1986 and 1989 General Social Surveys (based on analyses of students in Ontario) indicate that foreign-born students spent more time per day generally on education and related activities (Anisef and Johnson 1993:27), and on homework specifically (Anisef and Johnson 1993, table 12:123). The same relationships held true for youth whose mother tongue was neither English nor French (Anisef and Johnson 1993, table 12:123). Furthermore, more foreign-born students expected to continue their education and planned to attain graduate degrees than their Canadian born counterparts. While students whose mother tongue was neither English nor French were more likely to expect to work after graduation, they all planned to further their education within the next five years (Anisef and Johnson 1993, table 19:130). Interestingly, foreign-born students were also less satisfied with their education than native-born students, as were those whose mother tongue was neither English nor French (Anisef and Johnson 1993, table 20:131). Finally, in a multivariate analysis of the predictors of educational attainment, Richmond (1986:83-5) found that controlling for immigration status, respondents with higher educational attainment had higher occupational ambitions, more parental encouragement in their studies, higher levels of parental education and fewer siblings.

 

The Educational Attainment of US Immigrants

As in the Canadian context, few US studies have focussed their attention on the educational attainment of immigrant children, with most studies either focussing on immigrant adults, or on race rather than immigration status (cf. Zhou 1997; Vernez and Abrahamse 1996). Where the educational experience of immigrant children is concerned, studies have been primarily ethnographic and are "rich in textured descriptions in specific school settings but do not permit generalizations to all immigrant youths either within a state or nationally" (Vernez and Abrahamse 1996:3). There is, as a result, a paucity of data on the specific educational outcomes of US immigrants.

Generally, the experience of immigrants in the US educational system has parallelled that of Canadian immigrants. According to a recent review of the literature, US evidence indicates that compared to their native-born counterparts, immigrant youth do comparatively well in school (Zhou 1997). Foreign-born students are most likely to enroll in post-secondary education and to attend college continuously for four years (Vernez and Abrahamse 1996). Compared with native-born students, immigrant students not only have more positive attitudes toward schooling and higher aspirations for college education, but are "more likely to make choices consistent with eventual college going" (Vernez and Abrahamse 1996:32).

In explaining the determinants of educational attainment in the US, analyses have consistently demonstrated that parental education and socioeconomic status (SES) are positively related to educational success, both for foreign-born and native-born youth (Vernez and Abrahamse 1996:52). Based on longitudinal data of high school sophomores and seniors, Vernez and Abrahamse (1996) also found that having either no siblings or more than three siblings has a negative effect on educational attainment and that the higher the educational level of either parent, the higher the education of the immigrant student (p.52). While immigrant students are not more likely than native-born students to graduate from high school or attend college, they are more likely to attend college continuously for four years (p.49-50). Length of time in the US is also an important consideration; immigrant students who spent more time in the US are more likely to attend college, and to attend continuously for four years, than more recent immigrants (p.51). Finally, speaking English at home is not positively related to these students’ educational outcomes (p.51). Vernez and Abrahamse (1996) also explored individual-level variables for both foreign- and native-born students, including parental expectations and students’ motivation to work hard. With respect to the foreign-born students, parental expectations appear to be more closely related to students’ success than students’ own attitudes; while "parental expectations for, and support of, the children’s education are both strongly and independently associated with eventual pursuit of a postsecondary education" (p.57-59), students’ motivation to work hard in school was actually negatively associated with college attendance among foreign-born students (Vernez and Abrahamse 1996, table 6.4: 55).

A recent article by Zhou (1997) offers an excellent overview of many of the studies regarding the attainments of immigrant children; the present discussion touches on some of the relevant studies. Focussing on the effect of race and ethnicity for immigrant children, Kao and Tienda (1995) use data from the National Educational Longitudinal Study to demonstrate that parental education and SES are strong predictors of educational attainment for foreign-born students, and that parental involvement plays a key role in these students’ successful outcomes. Kao and Tienda (1995) also find that foreign-born children and children of immigrants "earned higher grades and math scores and expressed higher educational aspirations than children of native-born parents...even after the effects of race, ethnicity, and parental socioeconomic status were held constant" (p.9). Finally, examining the effects of Mexican students’ English-language proficiency on academic performance, Rumberger and Larson (1998) found that students with limited language proficiency had lower academic grades than other students, even after controlling for background factors, including whether the student was foreign- or native-born. The most successful students were those who came from non-English speaking backgrounds and who became fluent in English, but, surprisingly, came from lower socioeconomic backgrounds; the authors argue that this proficiency in English is therefore an indicator of the students’ cultural, rather than social-class, advantage. Furthermore, measures of academic engagement such as classroom work habits and absenteeism were predictive of students’ school performance. That the predictors of educational attainment were both a student’s academic performance as well as his/her proficiency in English lends credence to the authors’ conclusion that "the results seem to validate a conceptual framework that recognizes that both the social and the academic dimensions of school behaviour are necessary for understanding educational achievement" (Rumberger and Larson 1998:87).

Social Capital and Educational Attainment

To better understand the determinants of educational attainment, some authors have looked to the concept of social capital to capture the network of support essential for students’ success. Reacting to the "individualist bias in neoclassical economics" (Coleman 1990:301), James Coleman developed the notion of social capital as an intangible social resource that individuals can draw upon to facilitate action and relations, "making possible the achievement of certain ends" (Coleman 1990:302). In a recent review, Portes (1998) explains that "the consensus is growing in the literature that social capital stands for the ability of actors to secure benefits by virtue of membership in social networks or other social structures" (p.6). Of course, social capital does not always lead to positive outcomes and Coleman’s work does not argue that society as a whole is always better off because of its presence. Nonetheless, social capital functions as a resource that individuals can often mobilize in particular situations (Coleman 1990:302).

In the educational context, researchers have drawn on the concept of social capital to understand the ways in which students benefit by membership in certain communities or networks which allow them to draw on positive role models, encouragement, support and advice. For immigrant communities, being able to draw on social capital may be especially important (Portes 1997; Stepick 1996; Zhou and Bankston 1994; Portes and Sensenbrenner 1993). As Bourdieu and Passeron ([1964] 1979) argue, there are serious cultural obstacles for youth who do not come from the established social class and who do not necessarily benefit from the same social resources:

Even if there were no other evidence and if we knew nothing of the numerous and often very indirect ways in which the school system steadily eliminates children originating from the least privileged backgrounds, proof of the magnitude of the cultural obstacles which these children have to overcome could be found in the fact that even at the level of higher education, one still finds differences in attitudes and ability that are significantly related to social origin, although the students whom they differentiate have all undergone fifteen or twenty years of the standardizing influence of schooling... (Bourdieu and Passeron [1964] 1979:8)

That some ethnic communities have very high educational success, then, may be related to the extent and form of social capital that they can draw upon within their own networks (see, for example, Stanton-Salazar and Dornbusch 1995). In fact, recent studies indicate that in spite of their lack of attachment to outside networks, immigrant families draw on social capital that stems from familial or ethnic networks (Portes 1998; Zhou 1997). In this vein, Portes and MacLeod (1996) hypothesized that ethnic groups that were well received in the US have been able to build stronger communities and networks, facilitating the development of social capital with subsequent positive effects for these children’s outcomes. Such well-received immigrant groups were found to have superior academic outcomes regardless of SES, suggesting that "the internal character of the community plays a key role in encouraging students to achieve" (Portes and MacLeod 1996:264). Stanton-Salazar and Dornbusch (1995) conclude that the Mexican-origin high school students with higher grades and status expectations in their sample generally had "greater social capital than their counterparts with lower grades and expectations" (p.130); these students were those with the most ties to institutional agents who could provide them with informational support (p.122). Similarly, White and Kaufman (1997) find that social capital is a significant predictor of high school completion among immigrants and native-born ethnic groups, controlling for factors such as grades, educational expectations and familial socioeconomic status. Significantly, they find that social capital "can buffer the risks associated with foreign birth and lower socioeconomic origins" (p.397). Kalmijn and Kraaykamp (1996) focus on "cultural capital," a related concept characterized by socialization into ‘high brow’ culture, and find that it is associated with higher levels of schooling, controlling for background characteristics. Overall, as Zhou and Bankston (1994) conclude based on a study of Vietnamese youth, social capital is integral to understanding the outcomes of immigrant youth:

... ethnic social integration creates a form of social capital that enables an immigrant family to receive ongoing support and direction from other families and from the religious and social associations of the ethnic group. Consequently, community standards are established and reinforced among group members, especially among younger members .... We thus conclude that social capital is crucial and, under certain conditions, more important than traditional human capital for the successful adaptation of younger-generation immigrants (p.842).

 

 

The Relationship Between Social Capital and Planful Competence

While these studies highlight the impact of social capital on educational attainment, Bourdieu and Passeron ([1964] 1979) remind us that despite a lack of social capital, students from disadvantaged groups can succeed educationally. Similarly, the existence of social capital is no panacea; as Bellamy (1993) cautions, "[f]amily background provides individuals with social, cultural, and economic capital. This capital, however, must be actively invested" (p.140). Choices made by students in their progress through the educational system remain pivotal. To better understand the process of adolescent decision-making, Clausen (1991) introduced the concept of ‘planful competence,’ arguing that students who succeed do so because they make the right choices – or at least refrain from making unwise choices – throughout their adolescence. Clausen’s analysis of longitudinal data reveals that this competence is an essential ingredient in understanding educational attainment. Social capital, however, can also be an important mediator of these individual choices. As Shanahan, Elder and Miech (1997) point out, "[a] contextual perspective on agency suggests that adolescent planfulness predicts educational attainment, but only when the social structure provides viable alternatives between school and work" (p.56). Drawing upon social capital in making individual choices can lead to better informed decisions, whose effects, as Clausen notes, can last a lifetime. In fact, Clausen (1991) finds that for males, adolescent competence is the largest contributor to explained variance in occupational attainment (p.822). Thus, the contextual effects of social capital and human agency are important not only for educational attainment, but for longer term outcomes such as occupational attainment. The literature on immigrants’ occupational attainment is extensive (see, for example, Portes and Rumbaut 1996; Hou and Balakrishnan 1996; Geschwender and Guppy 1995; Borjas 1994; Boyd 1985; Porter 1965). The present study assesses occupational attainment as the outcome in the trajectories established by immigrants’ educational histories.

Data and Method

This study explores the educational paths of immigrant students through a 19-year multiwave panel study undertaken from 1976 to 1995 in suburban Toronto (Canada). The first of the three waves of the Toronto panel study began in 1976 when the respondents were adolescents attending four high schools in a community of about a half million people. This suburban community has grown dramatically in population over the past 30 years, with population increases centered around the intersection of the two major highways that access the city. The sampling frame for the first wave of the study in 1976 was the enrollment lists of all students in grades 8 through 12 from all four secondary schools, including a vocational school, that served the central area of this community.

The original sample was disproportionately stratified by housing type to increase class variation; we used addresses to sample respondents in equal numbers from single- and multiple-family dwelling units. Sampled students were personally invited and paid five dollars each to participate after school in the survey. The response rate was 83.5%, providing 835 secondary school students for the first wave of the panel.

Thirteen and nineteen years later, telephone interviews were completed with 570 and 544 of the first wave respondents, representing response rates, uncorrected for death or other sources of attrition, of 68% and 65% respectively. Analyses of attrition across waves of the panel have revealed no patterns that bias multivariate findings based on these data (see Hagan 1991; Hagan &Wheaton 1993; Hagan et al. 1996). The immigration status of the respondents was categorised into three possible options: those who immigrated to Canada with English as their first language, immigrants to Canada for whom English was a second language, and native-born Canadians.

In assessing the educational outcomes of immigrant students, this study integrates the structural and individual approaches by relying on theories of social capital and planful competence. We employ familial- and school-based measures of social relations to assess the social capital of immigrant students. As Hagan et al. (1996) point out, "socially structured relations between individuals (e.g. parents, teachers, neighbors and children) in social groups (e.g. families, schools and neighborhoods) are sources of social capital that increase the capabilities of children" (p.370). We rely on measures of a student’s relational ties to parents, the degree of parental supervision, and the student’s extent of attachment to school as indicators of students’ social capital (see Table 1).

We measure an adolescent’s ‘planful competence’ in terms of efforts to at school. As Table 1indicates, students were asked, "On the average, how much time do you spend doing homework outside school?" This measure should reflect the extent to which the students are investing in educational choices by putting effort into their schooling.

Results

Table 1 presents definitions and summary statistics for variables used in the analysis and reveals that 11% of respondents were immigrants who spoke English as their first language, while another 11% were English Second-Language (ESL) immigrants. The average educational attainment in the sample was 2.7, indicating that the average respondent had completed high school and attained some post-secondary education. The mean differences presented in Table 2 indicate that while ESL students’ mothers had lower occupational status than native-born and other immigrants’ mothers, the ESL children had the highest amount of parental supervision, attachment to school, effort at school and English grades. Overall, these ESL immigrant students also had the highest educational attainment of all respondents. The ESL students also reported the lowest levels of delinquency, though this difference was not statistically significant.

Table 3 reports the findings from four separate models. The first model predicts educational and occupational attainment using ordinary least squares (OLS) regression, and the remaining two models use logistic regression to predict the likelihood of students dropping out of high school and the probability of university attendance. We first examined the relationship between immigration status and educational attainment using controls for age, gender, language status, pre-school or primary school immigration and parental occupational status. As indicated in the first column of Table 3, English second language status is significantly and positively correlated with educational attainment, as is father’s occupational status, while pre-school immigration tends to lower educational attainment. The elaborated model, in the second column of Table 3, indicates that while being an ESL immigrant student is positively related to educational outcomes, these students no longer perform significantly better than their counterparts when the social capital and planful competence variables are introduced. Rather, the effects of gender, father’s occupational status, a student’s ties to his/her parents, attachment to school, effort at school, math and English grades all significantly increase students’ educational outcomes. Thus, this model suggests that ESL students achieve higher educational attainment because of their increased social capital and effort at school. This full model also explains 24% of the variance in educational attainment, compared to only 5% in the previous model.

The second model, presented in the third and fourth columns of Table 3, indicates that the odds of dropping out of high school are higher for men than for women, and are also higher for students whose fathers have a lower occupational status. In the full model, these effects disappear, indicating that a student’s attachment to school, math grades and English grades mediate the effects of gender and socioeconomic status. These results indicate that attachment to school and effort in school are important determinants of students’ academic success and persistence in education.

The third model predicts the likelihood of university attendance. The initial equation, presented in column five, indicates that the significant predictors of university attendance are English as a second language and father’s occupational status, while pre-school immigration lowers the odds of university attendance. The second equation introduces the social capital and competence variables and indicates that students with stronger ties to their parents, higher attachment to school, greater effort at school, and higher math and English grades are all more likely to attend university. Furthermore, being male increases the likelihood of university attendance, but the effect of parental occupation is insignificant. Interestingly, in this final model, ESL students are 2.5 (exponential .92=2.51) times more likely than native-born students to attend university, net of all other factors. ESL status may be predictive of university attendance rather than educational attainment more generally because a small percentage of the entire sample actually attended university making this outcome more distinctive.

In order to investigate whether the effects of structure and agency ultimately exert an important effect on occupational attainment, we predicted a model examining the relationship between immigration status and occupational attainment with controls for age, gender, language status, pre-school or primary school immigration and parental occupational status, and restricted the sample to those who were active in the labour force. As indicated in the seventh column of Table 3, father’s occupational status is significantly and positively correlated with occupational attainment, while pre-school immigration tends to lower occupational outcomes. The elaborated model, in the eighth column of Table 3, introduces the social capital and competence variables, as well as a variable indicating university attendance. As expected, in this final model, the effects of a student’s competence and university attendance significantly predict occupational attainment, mediating the effects of father’s occupational status and of pre-school immigration. In this final model, university attendance now seems to act as a surrogate for social capital, as the other social capital variables are no longer significant in this equation. This is perhaps not surprising since the previous measures of social capital relate to the respondent’s social capital during adolescence. Once the transition to university is made, it may absorb the earlier effects of social capital and become the credential that continues to carry the resulting benefits.

Finally, we estimated a path model of occupational attainment for the 447 respondents who were active in the labour force. This final model includes all variables that were significant at the .05 level with standardized coefficients greater than .1, as presented in Figure 1. This path model illustrates that ESL immigrant students attain higher occupational attainment through two main paths that reflect the influences of structure and agency. First, we see that ESL immigrant students succeed because of their agency, as reflected in their attachment to school, efforts at school and their subsequent high math grades; the model also specifies that effort at school results from strong relational ties to parents and an ensuing higher attachment to school. Yet these students succeed not only through their efforts, but because they have attended university. While university attendance is partially based on a students’ attachment to and efforts in school, it is also predicted by ESL status. As argued above, university attendance is an endogenous variable in this path model, representing the culmination of a student’s accumulation of social capital in adolescence. In this sense, university attendance becomes a key structural variable that accounts for later occupational success.

Discussion

Canadian studies have found that many immigrant groups succeed educationally, yet few have explored why this is so. This study has explored social capital and planful competence as determinants of educational attainment. We expected that familial and school-based social capital would be essential components of students’ success because they would provide necessary supports and networks that all students, and perhaps especially immigrant students who may lack other sources of social capital, require. As Clausen (1991) points out, "[p]arents or other adults who can provide an orientation to potential options and who can raise thoughtful questions to help the adolescent identify important issues can assist enormously" (p.808). Recognizing that the choices a student makes throughout an educational career are pivotal, we hypothesized that both a student’s social context as well as his/her ability to make competent choices would be both complementary and essential components of educational success.

The findings from this study support these hypotheses. The measures of social capital were significantly and positively related to higher educational attainment. We found that net of background factors such as parental occupational status, students with stronger ties to their parents and higher attachments to school were more likely to succeed. Furthermore, the data indicate that measures of competence are also independently and significantly related to educational success, with increased effort at school predicting higher educational attainment. This confirms the importance of both the independent efforts of students and the social background in which the student is able to build positive social and familial attachments in determining educational success for immigrant students.

Very similar results were found with respect to the likelihood of university attendance. This model suggests that the effects of social capital and planful competence mediate the effect of father’s occupational status; as Davies and Guppy (1997) note, there may be a relative "liberation" of students from their socioeconomic status in higher education. This elaborated model also indicates that ESL status is significantly and positively associated with university attendance, even when controlling for background, social capital, and competence variables. We may hypothesize that this strong relationship is a surrogate for a student’s bilingual status since the descriptive data also indicated that the ESL students’ English grades were significantly higher than all other students’ English grades. Previous research has indicated that bilingual students have higher educational outcomes than English-only or limited English-speaking students (Rumberger and Larson 1998; Zhou 1997; Stanton-Salazar and Dornbusch 1995; Portes and Schauffler 1994; Peal and Lambert 1962). Bilingualism enables biculturalism, indicating a student’s "cultural, rather than ... social-class, advantage" (Rumberger and Larson 1998:86). This biculturalism may allow students to take advantage of the social capital available to English speakers by facilitating access to mainstream institutions which may "actively transmit values resources, special privileges, and personal assurances of future sponsorship" (Stanton-Salazar and Dornbusch 1995:120), while continued proficiency in a native language "can facilitate access to the social resources of ethnic communities" (Bankston and Zhou 1995:6). Because they can draw on the resources of both "mainstream" and ethnic communities, these students may be well-positioned to make competent choices, informed by a variety of perspectives, leading to successful personal outcomes.

Clausen (1991) suggests that the choices made in adolescence can last a lifetime. The models we have estimated predicting occupational attainment are indicative of this kind of lifetime influence. In essence, we have found that choices made by the respondents when they were adolescents had substantial effects on their occupational outcomes twenty years later. The equations predicting educational attainment suggest, however, that both agency and structure are important in determining occupational outcomes, with the effects of university attendance representing the culmination of students’ social capital in adolescence, and exerting strong and positive effects on occupational attainment.

The experience of immigrant students in the educational system, according to the data from this study, can be very positive. Their success is not necessarily contingent on their socioeconomic background, but on their planful choices to work hard while also maintaining close attachments to social and familial networks. These results highlight the importance of both individual agency and social structure as determinants of educational attainment. The high educational and occupational attainments of these students, in Bourdieu and Passeron’s ([1964] 1979) terms, indicate that they have not been "crushed by the weight of their social destiny" (p.25).

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Table 1. Descriptive Statistics for Variables in Toronto Panel Study, 1976-1995 (n=447)

Variable

Measure & Values

_

S.D.

Age (1976)

Reported Years of Age

15.473

1.568

Gender (1976)

Reported Sex (Male=1)

.593

.492

English First Language Immigrant (1976)

English First Language=1

.112

.316

English Second Language Immigrant (1976)

English Second Language=1

.110

.313

Pre-School Immigrant (1976)

Pre-School=1

.065

.247

Primary School Immigrant (1976)

Primary School=1

.114

.318

Secondary School Immigrant (1976)

Secondary School=1

.060

.238

Father’s Occupational Status (1976)

Treiman Scalea

45.895

10.760

Mother’s Occupational Status (1976)

Treiman Scalea

41.991

7.858

Relational Ties to Parents (1976)

"Do you talk about your thoughts and feelings with your mother/father?"b

4.011

1.203

Parental Supervision (1976)

"Does your mother/father know where/who you are with when you are away from home?"

10.283

2.561

Self Reported Delinquency (1976)

"How often in the last year have you:

Taken little things (worth less than $2) that did not belong to you?

Taken things of some value (between $2 and $50) that did not belong to you?

Taken things of large value (worth over $50) that did not belong to you?

Taken a ride in a car without the owner’s permission?

Banged up something that did not belong to you on purpose?

Beaten up anyone or hurt anyone on purpose?"c

9.085

3.428

Attachment to School (1976)

1-5

"Generally speaking, do you like school?"d

3.115

1.041

Effort at School (1976)

1-7

"On the average, how much time do you spend doing homework outside school?"e

3.726

1.721

Math Grades (1976)

 

 

62.018

11.884

English Grades (1976)

 

 

66.165

15.109

Educational Attainment (1996)

High School Dropout=1

High School Graduate=2

Community College/Technical School=3

University=4

2.781

1.016

Occupational Attainment (1996)

Treiman Scalea

46.201

11.381

 

 

Table 2. Mean differences Between Immigrants with English as First and Second Language and Canadian Born Panel Respondents on Adolescent Background and Adult Outcome Variables

Variables

English as First Language

English as Second Language

Canadian Born

t-value (ESL/Others)

Age

15.44

15.735

15.44

1.24

Gender

0.6

0.531

0.602

-0.95

Pre-School Immigrant

0.24

0.204

Primary School Immigrant

0.42

0.429

Secondary School Immigrant

0.26

0.225

Father’s Occupational Status

46.193

44.806

46.005

-0.75

Mother’s Occupational Status

41.616

39.788

42.356

-.209*

Relational Ties to Parents

3.94

4.082

4.012

0.43

Parental Supervision

10.16

10.918

10.211

1.85*

Self Reported Delinquency

9.44

8.592

9.104

-1.07

Attachment to School

3.08

3.429

3.075

2.25*

Effort at School

3.82

4.469

3.607

3.24*

Math Grades

63.934

62.104

61.731

0.05

English Grades

61.617

69.543

66.342

1.66*

Educational Attainment

2.72

3.102

2.744

2.36*

Occupational Attainment

45.2

48.898

45.966

1.76*

* p < .05, one tailed

 

Table 3. Reduced Form and Structural Equations for Educational and Occupational Attainment

Independent Variables

Educational Attainment Scale (OLS Regression)

High School Drop-Out (Logistic Regression)

University Attendance (Logistic Regression)

Occupational Attainment

(OLS Regression)

 

 

(1)

(2)

(1)

(2)

(1)

(2)

(1)

(2)

Age

-.01 (.03)

.01 (.03)

-.05 (.08)

.15 (.09)

-.02 (.07)

.01 (.07)

.01(.34)

.275(.29)

Gender

.01 (.09)

.25 (.09)*

.00 (.25)*

-.32 (.30)

-.08 (.20)

.68 (.26)*

.57(1.09)

.05(1.04)

English Second Language

.39 (.17)*

.18 (.15)

-.43 (.55)

-.03 (.58)

1.08 (.36)*

.92 (.41)*

3.08(1.98)

.122(1.69)

Pre-School Immigration

-.32 (.18)*

-.23 (.17)

.26 (.49)

.22 (.52)

-.90 (.48)*

-.74 (.53)

-5.59(2.27)*

-3.62(1.93)

Primary School Immigration

.11 (.16)

.09 (14)

-.53 (.52)

-.49 (.54)

.09 (.34)

-.01 (.39)

.75(1.85)

.142(1.56)

Secondary School Immigration

.10 (.20)

-.04 (.18)

-.38 (.65)

-.05 (.69)

.13 (.43)

-.02 (.47)

3.44(2.37)

3.14(2.01)

Father’s Status

.02 (.01)*

.01 (.00)*

-.03 (.01)*

-.02 (.01)

.03 (.01)*

.03 (.01)

.150(.05)*

.07(.04)

Mother’s Status

-.01 (.01)

-.01 (.01)

.02 (.02)

.02 (.02)

-.00 (.01)

-.00 (.02)

-.00(.07)

-.00(.06)

Relational Ties to Parents

 

 

.06 (.03)*

 

 

-.07 (.11)

 

 

.18 (.10)*

 

 

.589(.39)

Parental Supervision

 

 

.01 (.02)

 

 

.00 (.06)

 

 

.04 (.05)

 

 

-.183(.20)

Self-Reported Delinquency

 

 

-.00 (.01)

 

 

-.04 (.04)

 

 

-.04 (.04)

 

 

.158(.16)

Attachment to School

 

 

.11 (.04)*

 

 

-.19 (.13)

 

 

.29 (.12)*

 

 

.37(.48)

Effort at School

 

 

.17 (.03)*

 

 

-.38 (.10)*

 

 

.26 (.07)*

 

 

.81(.29)*

Math Grades

 

 

.01 (.00)*

 

 

-.04 (.04)*

 

 

.046 (.01)*

 

 

.176(.05)*

English Grades

 

 

.01 (.00)

 

 

-.01 (.01)

 

 

.025 (.009)*

 

 

.002(.04)

University Attendance

 

 

 

 

 

 

 

 

 

 

 

 

 

 

10.36(1.10)*

Constant

2.37

-0.231

 

 

5.91

 

 

-10.49

38.201

17.752

R2 / -2 log likelihood

0.05

0.24

 

 

399.08

 

 

508.17

.05

.35

* p < .05, one tailed

Note: Numbers in parentheses are standard errors

 


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