Early school leaving among immigrants in Toronto secondary schools.
Anisef, Paul ; Brown, Robert S. ; Phythian, Kelli 等
IMMIGRANTS ARE WILLING TO BEAR THE costs of moving to a new and
unfamiliar country in order to pursue economic opportunities, a better
standard of living and, what is especially important to most, a brighter
future for their children. Surveys of immigrants consistently indicate
that nearly all hold postsecondary educational aspirations for their
children (Krahn and Taylor 2005). Given the need for skilled labor and
an informed citizenry, it is equally important to Canada that the
children of immigrants are well-educated. Completing high school is, of
course, a prerequisite to gaining access to postsecondary studies and is
consequently among the first, and most important, steps immigrant youth
take toward making the most of the opportunities that served to motivate
their family's move to Canada. Failing to complete high school
jeopardizes the economic prospects of immigrant youth and imposes a
social cost on Canadian society that it can ill afford. For these
reasons it is important to better understand the factors underlying the
academic performance of first- and second-generation immigrant youth.
First-generation immigrants are the foreign-born children of immigrants
and the second generation is the Canadian-born children of immigrants.
The educational aspirations of both generations tend to be high,
reflecting the optimism each feels toward attaining their social and
economic goals by succeeding in the education system (Glick and White
2003; Krahn and Taylor 2005; OECD 2006).
However, the ability of immigrant youth to realize their broader
ambitions by educational means is not assured given the rapidly changing
demographic composition of Canada's population coupled with the
economic downturn experienced by recent immigrant cohorts. At issue is,
first, the capacity of large metropolitan educational systems like the
Toronto District School Board (TDSB) to accommodate the diverse
backgrounds and needs of immigrant youth and, second, whether immigrant
families have the resources to support their children's educational
endeavors.
Newcomers to Canada have experienced unprecedented obstacles to
success that have translated into lower incomes and higher poverty rates
relative to previous immigrant waves (Aydemir and Skuterud 2004; Bloom,
Grenier, and Gunderson 1995). Research indicates, for instance, that the
earnings gap between recent immigrants (i.e., those that have arrived
within the previous five years) and the "like" Canadian born
has been increasing significantly with each successive cohort since the
1970s (Frenette and Morissette 2003). Given that employment earnings
represent the major source of income for most families, it is no
surprise that the decline in relative earnings has corresponded to an
increase in the proportion of new immigrants living below the low-income
cutoff (LICO). While low-income rates have fallen or remained constant
even for the most vulnerable groups among the Canadian born, the rate
for new immigrants rose from 25 to 36 percent between 1980 and 2000
(Picot and Hou 2003). Moreover, the low-income situation of many
newcomers has been described as chronic. As many as 65 percent of
immigrants can expect to experience a low-income spell within their
first 10 years of living in Canada and, of these, roughly one-third will
remain in low income for three years or more (Picot, Hou, and Coulombe
2007).
The deteriorating economic position of recent immigrants has
coincided with a period of rapid demographic change in Canada
(Statistics Canada 2006a, 2006b). Sustained high levels of immigration
since the latter half of the 1980s together with the removal of
preferential access for applicants from European countries in 1967
brought about a continuous rise in the proportion of ethnic, racial,
religious, and linguistic minorities. Once from the predominantly white
countries of Northern and Western Europe, the new immigration consists
largely of those from Asian and African countries. Data from the 2006
Census of Canada indicate that 58 percent of recent immigrants were from
Asian countries and another 11 percent were born in African countries.
To be sure, 19.8 percent of Canada's population is foreign born
and, as of 2006, 16.2 percent of the population identified themselves as
visible minorities. In many Canadian cities, such as Toronto, Vancouver,
Mississauga, and Markham, immigrants and visible minorities make up
close to one-half of the population or more (Statistics Canada 2006b,
2008). Canada's immigrants represent 220 countries and nearly 150
languages; fully 70 percent of Canada's foreign-born population has
a mother tongue that is neither English nor French; and it is expected
that roughly one out of every five people in Canada will be a visible
minority by 2017, when Canada celebrates its 150th birthday (Statistics
Canada 2005, 2006b).
This study employs student administrative data obtained from the
TDSB to investigate the extent to which living below the LICO affects
the likelihood of dropping out, while taking into consideration
additional risk factors associated with leaving school before graduation
(e.g., country of origin, age at arrival, family structure). Further to
this, the extent to which the association between LICO and academic
performance varies by generational status is measured. The
(longitudinal) research design employed involves analysis of data
collected from the year 2000 grade 9 cohort that were followed to 2006,
or two years after the normal year of graduation.
In employing TDSB administrative data, the study complements the
findings of previous immigrant youth studies based on nationally
representative data supplied by Statistics Canada (Finnie and Mueller
2008; Worswick 2001). Administrative data are particularly advantageous
in that they canvas an entire population. As such, the errors that arise
as a result of survey sampling and design are avoided (Warburton and
Warburton 2004). While the use of administrative data has its own
challenges, (1) the present study makes use of a highly accurate set of
data collected by the largest school board in Canada. In doing so, we
take advantage of a unique opportunity for a detailed investigation of a
large population of students that in many ways represents the future
demographic profile of the country (Yau and O'Reilly 2007).
PATHS TO ASSIMILATION
The changing demographic composition of Canada's population
and the deterioration of immigrant labor market outcomes raise important
questions about the socioeconomic integration of new immigrants,
intergenerational mobility, and the way in which the future economic
position of the first and second generation hinges on ethnic background.
The traditional theory of immigrant adaptation suggests a
"straight-line" or "linear" form of assimilation,
whereby time spent in the host country determines the degree of
assimilation both within and between generations (Gans 1992, 1997). With
respect to academic achievement, the straight-line approach suggests
that children who immigrate at a younger age will have better outcomes
than those who arrive later. Further, those belonging to the third-plus
generation should outperform those belonging to the second generation,
who in turn will have better outcomes than the first generation. (2)
Consistent with this approach, age at migration has been found to be a
strong predictor of academic performance among immigrants: the younger
immigrants are upon arrival, the better their academic outcomes tend to
be (see, e.g., Cahan, Davies, and Staub 2001). Boyd (2002), for example,
reported that the 1.5 generation--first-generation immigrants who
arrived in Canada before age 15--are more likely to complete high school
and tend to attain higher overall levels of education than those who
arrived later. Contrary to the straight-line hypothesis, Boyd (2002)
further revealed that the educational attainment of the 1.5 generation
tends to exceed that of both the second and third generations.
Recognizing that the straight-line model ignores the various paths
to assimilation that various immigrant groups might follow, the
segmented assimilation hypothesis first articulated by Portes and Zhou
(1993) highlights the potential for horizontal or downward assimilation,
particularly in the U.S. context. Segmented assimilation theory
highlights the different patterns of adaptation that characterize
different immigrant groups. Some may indeed follow the classical
straight-line route to assimilation into the white middle class, while
others fall into poverty and join the ranks of the underclass and still
others will experience varying degrees of upward and downward mobility
between generations (Portes 1995; Portes and Rumbaut 2001; Rodriguez
2002; Zhou 1997). The declining at-entry labor market position of
Canada's immigrants, no matter the reason, may be taken as an
indication that the newer immigrant cohorts are experiencing more
difficultly integrating into their host society. It also raises
questions about the extent to which future generations will be able to
assimilate, which groups they will assimilate into, and the educational
and occupational pathways they will follow.
The segmented assimilation hypothesis is therefore useful for
guiding investigation into the educational experiences of various
immigrant groups. Such factors as race, language ability, place of
birth, socioeconomic status, and age at arrival are said to determine
the segment of society into which immigrants will assimilate (Zhou
1997). As new arrivals become increasingly diverse, their paths to
assimilation are more varied: children of the newer immigrant cohorts
come from a multitude of ethnic, linguistic, religious, and
socioeconomic backgrounds, they are likely to experience some degree of
economic hardship while in Canada, and they come from a wide array of
national origins. Each of these factors has been linked with educational
performance and subsequent opportunities for upward social mobility.
The impact of economic hardship on youth receives considerable
attention in the growing literature on poverty, exclusion, and
education. Educators, community advocates, and policymakers have drawn
attention to the fact that student achievement is significantly lower in
urban schools with high levels of poverty (Levin 2007:2). Research has
further documented that children reared in low-income conditions tend to
have poorer physical and mental health, experience more punitive
discipline styles and abuse, live in poorer neighborhoods, and are more
likely to be delinquent than are children raised in wealthier households
(Jones et al. 2002; Luthar 1999). The Canadian Council on Social
Development identified 27 elements important to child development,
including family functioning, neighborhood safety, aggression, health,
math and vocabulary scores, and participation in sports or clubs. For 80
percent of the elements examined, family income played a critical role:
among children living in families with annual incomes below $30,000, the
risk of negative child outcomes and the likelihood of poor living
conditions were considerably higher than in families with higher incomes
(Ross and Roberts 1999). Given that immigrants and visible minorities
are more likely to experience poverty (Edward Herberg 1998; Kazemipur
and Halli 2000, 2001a, 2001b), one would expect that these groups are
more likely to experience more negative child outcomes, included poorer
school performance and a greater incidence of dropout.
An important concept to consider in understanding the complex
relationship between poverty and educational outcomes is social capital.
Young people that experience sustained periods of poverty often lack the
kinds of social capital or networks that are key for achieving success,
first in school and, subsequently, in the labor market. There are two
types of capital that have different benefits and consequences for young
people. The first, called bonding capital, consists of close family and
friends who belong to the same social, cultural, and economic
background, while bridging networks are made up of individuals who vary
in terms of their backgrounds (Putnam 2000). The former creates and
sustains relationships within groups, while the latter refers to ties
that developed between groups. It is bridging capital that provides
access to the mainstream and to information and services that are
otherwise unavailable; to this end, it is these heterogeneous bridging
networks that are believed to help people "get ahead."
It has been argued that the poor and socially excluded are strong
in bonding networks, but weak in bridging networks (Kunz and Frank
2004:5). Studies, such as Poverty by Postal Code, demonstrate that
Toronto has many more concentrated areas of poverty than in the past, as
well as a higher proportion of immigrants living in these poor
neighborhoods (United Way of Greater Toronto and the Canadian Council on
Social Development 2004). Since 1981, there has been a 484 percent
increase in the "poor" immigrant family population living in
high poverty neighborhoods (from 19,700 in 1981 to 115,100 in 2001) and,
as of 2001, immigrant families accounted for nearly two-thirds of
families living in Toronto's higher poverty neighborhoods.
Furthermore, Toronto is home to a significant number of ethnic
communities. Given that residential segregation favors bonding over
bridging, immigrant youth who live in and attend schools in poor
neighborhoods and ethnic enclaves, are more likely to network or bond
with peers of similar social, cultural, and economic backgrounds.
Opportunities for immigrant students to accrue bridging capital may
therefore be limited, thereby increasing the probability of poor
academic performance and leaving school early without graduating.
Empirical research from Canada and elsewhere has indicated that
immigrant and visible minority children tend to have more difficulty in
school. For instance, historically disadvantaged groups in the United
States, particularly black and Hispanics, experience severe economic and
academic disadvantage upon arrival that is likely to persist across
generations (see, e.g., Glick and White 2003). In Canada, research
findings are less conclusive but, perhaps, more optimistic. Worswick
(2001), for instance, found that language proficiency and age at arrival
were particularly salient factors that influence settlement and
adaptation to school life. Looking at school children up to age 15, he
reported that children of immigrants perform, on average, at least as
well as children of the Canadian born along several dimensions of school
performance, including reading, writing, and mathematics. However, the
children of immigrants whose first language is neither English nor
French tend to have lower reading and writing scores than children of
native-born parents. Nevertheless, with more years spent in the Canadian
school system, reading and writing test scores tend to converge (see
also Corak 2005). However, looking specifically at students for who
English was not their mother tongue, Gunderson (2007) found stark
differences in the academic performance of different ethno-cultural
groups. Based on a sample of 5,000 English as a Second Language (ESL)
students enrolled in the Vancouver school system between 1991 and 2001,
Gunderson (2007) revealed that Mandarin and Cantonese speaking students
in grades 8 through 12 outperformed English-speaking Canadians in all
subjects with the exception of grade 12 English, while Indian-,
Vietnamese-, Tagalog-, and Spanish-speaking students generally performed
less well than the Canadian born.
Though the paths to assimilation appear to be varied for immigrants
and their offspring in both Canada and the United States, the contextual
factors facing Canadian immigrants are very different, and it has been
argued that there is little evidence of second generation decline in
Canada (Boyd 2002; Boyd and Grieco 1998). Boyd (2002) points to the lack
of urban ghettos and the smaller black and Hispanic populations in
Canada relative to the United States, and suggests that downward
assimilation is unlikely simply because there is no identifiable
underclass. Boyd (2002) also points out that the greater proportion of
immigrants entering Canada may create and sustain a "critical
mass" that supports education as a tool for upward social mobility
among immigrants and their children. Yet the unlikelihood of segmented
assimilation occurring en mass in Canada does imply that upward mobility
is inevitable. Relative to their parents, "horizontal
mobility" of the second generation may be more likely (Alba and Nee
2003:268). Recent successions of immigrant cohorts entering Canada are
facing lower at-entry earnings, higher rates of unemployment, and higher
low-income rates while the native born are enjoying declining
unemployment and poverty rates (Aydemir and Skuterud 2004; Picot and
Sweetman 2005). Despite the improbability of assimilation into an
"underclass," the economic outlook for children of the foreign
born may not be much brighter than that of their parents.
IMMIGRANT STATUS AND THE SCHOOL EXPERIENCE IN ONTARIO
The school experience of first- and second-generation youth is a
particularly important issue in Ontario, where one-half of all
immigrants to Canada settle and 28 percent of the population is foreign
born. With respect to youth, 19 percent of Ontario's population
aged 15 to 24 was foreign born in 2006; in Toronto, this figure was 40
percent (Statistics Canada 2007). Its large foreign-born population,
particularly in urban areas, means that Ontario can not afford to
overlook the disadvantaged socioeconomic position of its immigrants and
the long-term consequences this might have for their children.
Data from Statistics Canada's Youth in Transition Survey
(2000) indicate that, in Ontario, 11.2 percent of 20-year-old males and
7.8 percent of 20-year-old females were not in school and had yet to
complete the requirements for a high school diploma (Bowlby and McMullen
2002). Within Ontario, high school dropout rates vary substantially by
family income. Data from 2003 show that, among those in the lowest
income quartile, the high school dropout rate at age 19 was 8.3 percent.
This is three times higher than the dropout rate of 2.6 percent among
those in the highest income quartile. Furthermore, the postsecondary
participation rate at age 19 was 40 percent higher for those in the
highest income quartile relative to those in the lowest quartile (Zeman
2007).
When asked about their main reason for dropping out, school factors
are most commonly cited by early school leavers. A 2002 survey of
17-year-old Canadians indicated that nearly 45 percent of those who had
dropped out of school attributed their departure to the school
environment. School-related factors include boredom or lack of interest
in classes, difficulties with school work and with teachers, expulsion,
and missing credits (Bushnik, Barr-Telford, and Bussiere 2004). A
comparison of school leavers and school continuers revealed that the
reading proficiency of dropouts were one full level below the average,
as defined by the Program for International Student Assessment. (3)
Early school leavers also reported much lower grades; among those who
had dropped out by age 17, 32 percent reported an overall grade of less
than 59 at age 15, compared with 8 percent of other students (Bushnik et
al. 2004).
A study commissioned by the Ontario Ministry of Education and
Training (Hospital for Sick Children 2005) revealed that first- and
second-generation youth in Toronto and Kitchener-Waterloo experience
unique challenges in secondary school. In-depth qualitative interviews
were conducted with 57 first- and second-generation youth who had left
school early or were at risk of doing so. Respondents cited the need to
learn a new language, language barriers, unfamiliarity with the Canadian
school system, and inappropriate linguistic assessment and grade
placement as important risk factors for school disengagement. Stresses
associated with resettlement, loneliness, isolation, and a lack of
friends were also reported. The study further demonstrated that age at
the time of migration was especially critical, whereby youth who
immigrated during the latter years of high school were most at risk of
dropping out.
DATA, VARIABLES, AND METHODS
Access to student level data was provided by the External Research
Review Committee of the TDSB. A single grade 9 cohort that began high
school in 2000 was tracked over a six-year period. Seventy-nine percent
of this cohort had completed elementary school within the TDSB. The
remaining 21 percent arrived from other school boards, both within and
outside of Canada. The original grade 9 cohort was made up of 18,798
students. By October 2006, the official end of year 6 of the study,
2,220 students had transferred out of the TDSB to other secondary
institutions and could no longer be tracked. Hence, they were omitted
from the analysis. Another 329 students were removed due to coding
errors, leaving a sample of 16,249 students.
By the end of their sixth year of secondary study, 72 percent of
students in the sample had graduated with an Ontario Secondary School
Diploma (OSSD) or successfully completed 30 or more credits. Two percent
had not graduated but remained in a secondary school for a seventh year
and another 26 percent had dropped out. Dropouts are classified as those
students who had left secondary school without having graduated or
transferred to another secondary institution.
The administrative data set contains a series of variables that
measure a variety of sociodemographic characteristics, including gender,
region of birth, language, family status, and the age at which each
student entered high school. Region of birth distinguishes among seven
regions, including Canada, Europe, English-speaking Caribbean, Africa,
South Asia, West Asia, and Eastern Asia. Respondents born in Canada are
further divided into two groups: those who speak English at home and
those who do not. First-generation immigrant status was thus defined as
being foreign born, second generation as being born in Canada but not
speaking English in the home, and third generation as being born in
Canada and speaking English in the home. Family status measures the
family situation of students in their third year of high school and
categorized into two groups: those who live with both parents and those
who do not. Finally, a variable based on age was included as an
indication of whether students began high school at the expected time or
if they began late.
As noted above, a variety of studies have documented the negative
impact of poverty on student achievement (Ornstein 2000; United Way of
Greater Toronto and the Canadian Council on Social Development 2004). To
capture poverty, a variable that measures the proportion of people in
the respondent's immediate neighborhood that fall below the LICO is
included. This variable was derived from student postal codes that were
matched with their dissemination area (DA): the proportion of the
population living below the LICO, as reported by the 2001 Census, was
assigned to each student based on the DA in which they lived. The
variable is coded in deciles by the TDSB, such that value 1 indicates
the highest incidence (proportion) of residents living below the poverty
line, whereas 10 indicates the lowest incidence of residents living
below the poverty line. Hence, a higher score means that a respondent
lives in a more affluent neighborhood.
Finally, three independent variables that provide information on
various aspects of schooling at the student level were included. The
first variable reflects streaming within secondary school. Streaming
refers to the majority of courses taken in grades 9 and 10, and is
employed to classify the student's program of study as academic,
applied, or essentials. Under the Ontario secondary school curriculum
introduced by the Ministry of Education in the Fall of 1999, students
are to choose a program of study that includes grades 9 and 10 courses
that are classified as academic (university-directed), applied
(college-directed), or locally developed essentials
(workplace-directed). As with previous studies, the present analysis
categorizes a student's program of study as academic, applied, or
essentials based on the majority of courses taken in grades 9 and 10.
The second independent variable indicates whether or not a student
is considered to be "at risk." A student is classified as
"at risk" if he or she had completed fewer than seven courses
by the end of grade 9. Last, the third variable distinguishes between
students who have taken ESL courses and those who have not. (4) This
variable also represents a proxy for language proficiency.
The descriptive statistics for the variables used in this analysis
are displayed in Table 1. Frequencies are provided for categorical
variables and means are provided for quantitative variables. The
descriptive statistics are provided separately for each region of
origin. With the exception of gender, there are statistically
significant differences across region of origin for all variables in the
analysis. The most noteworthy findings are discussed below.
In terms of dropout levels, students from the Caribbean had the
highest dropout rates (40 percent), whereas students of Eastern Asia
were least likely to dropout of high school (10 percent).
English-speaking Canadian students were in between, approximately 20
percent dropped out of high school. With regard to age at entering high
school, English-speaking Canadian-born students were most likely to
enter on time (97 and 98 percent, respectively), whereas Caribbean and
African students were least likely to enter on time (88 and 89 percent,
respectively). With respect to family status, European students were
most likely to live with both parents (74 percent), in contrast to
Caribbean students who are most likely to live in another family
structure. Just 26 percent of students from the Caribbean lived in two
parent families. Among English-speaking Canadian born students, exactly
one-half lived with both parents.
Turning to the academic variables, descriptive results reveal that
students from East Asia were predominantly enrolled in the academic
stream (90 percent), followed closely by students from Europe (85
percent), English-speaking Canada (78 percent), and students from South
Asia (78 percent). In contrast, Caribbean immigrants were least likely
to be in the academic track, at just 39 percent. Similar patterns
emerged for the "at-risk" variable, whereby students from East
Asia (7 percent) and Europe (10 percent) were least likely to be labeled
"at risk," and students from the Caribbean (33 percent) were
most likely to be considered "at risk." Canadian-born
English-speaking students were somewhere in the middle, as 14 percent
had not completed seven or more credits by the end of grade 9.
A slightly different pattern emerges with respect to having taken
an ESL course. As expected, English-speaking Canadian-born students were
least likely to have taken an ESL course (< 1 percent). (5) In
contrast, approximately 28 percent of East Asian immigrants had taken an
ESL course, followed by West Asian (26 percent) and South Asian
immigrants (22 percent). In comparison, 10 percent of Caribbean
immigrants have taken an ESL course.
Finally, using the LICO as an indicator of economically
disadvantaged neighborhoods, it appears that African immigrants lived in
the most disadvantaged areas, followed by South Asian immigrants and
then by West Asian immigrants. In contrast, English-speaking students
born in Canada tended to reside in neighborhoods with the lowest
percentage of families living below the poverty line.
Overall, the most consistent pattern revealed by the descriptive
statistics is that East Asian and European immigrants are generally in
the most favorable positions in terms of sociodemographic and
school-related characteristics, whereas Caribbean immigrants are in the
most disadvantaged positions. English-speaking students born in Canada
tend to fall in between the two extremes, though it is safe to say that
they are most certainly at an advantage in terms of their
sociodemographic and academic profiles.
Regression Results
The response variable in our analysis is an indicator of whether
the respondent had dropped out of the school system. Respondents are
considered dropouts if they had not graduated by 2006. (6,7) For the
regression analysis, we estimate a multilevel model in which individuals
(level 1) are nested within neighborhoods (level 2), where neighborhood
is defined according to the DAs in which the students live. The
neighborhood-level variable used in this study is the proportion of the
population living below the LICO, as defined by Statistics Canada. The
response variable is a binary variable that distinguishes between those
who dropped out of high school and those who did not. To regress the
level 1 outcome (dropout) on both level 1 and level 2 predictors, we
employ a mixed logit model. The Bernoulli distribution is specified for
the response variable and a logit link is used to map the mean of the
response variable to the linear predictor. Then logit link is defined as
[[eta].sub.ij] = log ([[PHI].sub.ij]/1 - [[PHI].sub.ij])
where [[phi].sub.ij] is the predicted probability of dropping out
for the ith observation in neighborhood j, and [[eta].sub.ij] is the log
odds of dropping out.
To estimate the magnitude of variation between neighborhoods in
dropout levels, we first estimate an unconditional model without any
predictors at either level (Model 1). Since the level 1 variance is
heteroskedastic, the intraclass correlation is not as intuitive as it is
in the standard hierarchical linear model. Nevertheless, it is still a
useful index because it represents the ratio of the level 2
(neighborhood) variance to the total variation. In models with binary
outcomes, the intraclass correlation is best considered in relation to
the latent variable approach, where the level 1 random effect is assumed
to have a standard logistic distribution with a mean of 0 and variance
equal to [[pi].sup.2]/3. (8) Using conventional notation the level 1
model is specified as
[[eta].sub.ij] = [[beta].sub.0j]
and the level 2 model is
[[beta].sub.0j] = [[gamma].sub.00] + [[mu].sub.0j]
where
[[mu].sub.0j] ~ N (0, [[tau].sub.00])
In the second equation, [[gamma].sub.00] represents the average
log-odds of dropping out across the neighborhoods, and [[mu].sub.0j] is
the random effect at level 2. The last term indicates that we are
adopting the usual assumption that the error term at level 2,
[[mu].sub.0j], is normally and identically distributed with an expected
value of 0 and a constant variance, [[tau].sub.00]. This assumption is
applied to all models estimated in this paper.
The estimates from Model 1 are provided in the first column of
Table 2. The key estimate in this model is the intraclass correlation,
[rho], which indicates that approximately 13 percent of the variation in
the outcome can be attributed to neighborhood characteristics
(p<.001). Since it is highly statistically significant, we proceed to
include a random effect at level 2 in Model 2. (9)
The region of origin variable is the only variable included in
Model 2, in which the level 1 structural model is specified as
[[eta].sub.ij] = [[beta].sub.0j] + [[beta].sub.1j][X.sub.1ij] + ...
+ [[beta].sub.kj][X.sub.kij]
where [[beta].sub.1j] through [[beta].sub.kj] are the parameters
representing the six dummy coded variables for the region of origin
variable. The level 2 model is
[[beta].sub.0j] = [[gamma].sub.00] + [[mu].sub.0j]
The parameters for the dummy coded variables are treated as fixed
(i.e., [[beta].sub.pj] = [[gamma].sub.p0] for p>0). The likelihood
ratio chi-square test for the region of origin variable is statistically
significant (p<.001) and the parameter estimates in Model 2 are
interpreted as the log-odds of dropping out of high school relative to
the reference category, English-speaking Canadian-born respondents. In
comparison with English-speaking Canadian students, only immigrants of
the Caribbean are more likely to dropout of high school (p<.001). In
contrast, immigrants that are less likely to dropout than the reference
group are students from Europe (p<.01), South Asia (p<.01), and
Eastern Asia (p<.001). Perhaps most interestingly, second generation
Canadians are no more or less likely to dropout of high school than are
first-generation Canadians. In Model 2, the estimated variance at level
2 remains statistically significant (p<.001), as approximately 11
percent of the total variation in dropout levels is attributable to
neighborhood characteristics after controlling for country of origin.
Model 3 includes the remaining level 1 variables and the level 2
variable LICO. (10) The specification of the level 1 structural model is
[[eta].sub.ij] = [[beta].sub.0j] + [[beta].sub.1j][X.sub.1ij] + ...
+ [[beta].sub.kj][X.sub.kij]
where [[beta].sub.1j] through [[beta].sub.kj] are now used to
conveniently denote the parameters for all of the quantitative and
categorical dummy coded explanatory variables in the model. At the
neighborhood level, only the intercept [[beta].sub.0j] is a function of
the level 2 predictor [W.sub.j], which is our measure of LICO:
[[beta].sub.0j] = [[gamma].sub.00] + [[gamma].sub.10][W.sub.j] +
[[mu].sub.0j]
whereas all of the other parameters are treated as fixed. Hence,
[[beta].sub.pj] = [[gamma].sub.p0] for p > 0
Most of the variables included in the model are statistically
significant (p<.001), while holding constant the value of the random
effect, [[mu].sub.0j]. (11) The only exception is the variable which
distinguishes between respondents who have taken ESL classes, which is
not statistically significant.
The magnitude of the estimates for the region of origin variable is
reduced in Model 3; however, the pattern of estimates is similar to
Model 2. It should be noted that the country of origin estimates are
reduced when the remaining variables are included in the model. Thus,
much of the impact of region of origin appears to be due to other
variables in the analysis. The most noteworthy change occurs among
Caribbean immigrants, as their relative chances of dropping out decline
dramatically when the control variables are included. In fact their
dropout levels are no longer significantly different from
English-speaking Canadian-born students. The relative chances of
dropping out also decline for students born in Africa. When the controls
are included in the model, their dropout levels become significantly
lower than Canadian-born students (p<.05), as are the dropout levels
of students from South Asia (p<.01) and Eastern Asia (p<.001).
Similar to the findings obtained in Model 2, there are no differences
between first- and second-generation Canadians in terms of their
likelihood of dropping out of high school.
With respect to the level 2 variable, LICO, respondents residing in
neighborhoods with lower proportions of residents living below the
poverty line (i.e., lower poverty) are less likely to dropout of high
school than are respondents residing in neighborhoods with higher
proportions of residents living below the poverty line. (12)
The estimates for the other variables that are statistically
significant are also in the expected direction. For example, males are
more likely than females to dropout. This is consistent with the
literature on school dropout which shows that, despite a recent decrease
in the overall dropout rate, gender differences remain. In 1990/1991,
just over one-half of dropouts were male (58.3 percent); by 2004/2005,
the proportion had increased to 63.7 percent (Bowlby 2005). In terms of
the academic achievement variables, students in the academic program,
the reference category, are least likely to dropout of high school,
whereas students in the essentials program have the highest probability
of dropping out. This finding is generally consistent with past research
(Human Resources Development Canada 2000). King et al. (1988) have
observed that the levels at which courses are taken by secondary school
students is the best predictor of dropping out. The parameter estimate
for the family structure variable reveals that students in two parent
families are less likely to dropout of high school than students living
in other family structures.
Similarly, students who start high school on time are less likely
to dropout than students who begin a year late. Finally, students who
are classified as "at risk," that is, those who completed
fewer than seven credits in grade 9, are more likely to dropout than
students who completed seven or more credits in grade 9. When
controlling for the explanatory variables, the proportion of variance
attributable to level 2 (LICO) is reduced to approximately 5 percent,
but nevertheless remains statistically significant (p < .05).
DISCUSSION AND CONCLUSION
High school graduation is a prerequisite to advanced education and
training in Canada. Consequently, the educational and occupational
futures of those who dropout of high school are severely restricted.
Immigrant adolescents generally recognize the importance of further
education and invest considerable effort in their high school studies
(Krahn and Taylor 2005). However, not all newcomer youth are successful
in school and those who exit before graduation represent a significant
cost to their parents. Canada too pays economic and social penalties
when immigrant children fail to integrate into the school system,
perform well, and subsequently contribute to the broader society.
Education, then, is a key factor in the integration process of
immigrant children. This integration process has been described by
linear and segmented assimilation theories. Explanations for the
variation in school performance among immigrant children and youth then
have focused primarily on the amount of time that has passed since their
arrival or, alternatively, by socio cultural differences that shape the
interactions between individuals and schools. Where integration is
viewed as a linear progression, earlier generations are expected to
perform better than newer generations, and those who arrive at a young
age will have better school outcomes than older immigrant youth.
Differences in school performance are therefore assumed to be a function
of institutional exposure, as indicated by age at arrival or time spent
in school. When considered from the perspective of cultural values and
linguistic differences in proficiency, the school performance of
immigrant children and youth is expected to vary by source country or
region. This study explored both generational-difference and
cultural-difference explanations for immigrant dropouts. We further
examined the extent to which barriers to school completion reflected the
individual characteristics, personal situations, and economic resources
found among immigrant youth and their families.
Results indicate little support for the straight line assimilation
model as it applies to academic achievement among immigrant youth.
Rather, findings supported the segmented assimilation hypothesis. Region
of origin was a significant predictor of dropout when first-generation
youth were compared with the native born. Students from the Caribbean
were significantly more likely than native-born English students to
dropout of school, while students from Europe, Eastern Asia, and South
Asia were less likely to leave school early. Underlying cultural factors
are often associated with regional differences in immigrant outcomes.
Cultural differences between their region of origin and the host society
present newcomers with challenges to adaptation and integration into a
new school environment. In the case of Caribbean immigrants, youth often
find themselves isolated, falling behind and falling in school, and
growing increasingly frustrated (Anisef and Kilbride 2003). It is
important to note that the dropout rate among such groups declines when
other factors are considered, including school conditions and curricular
policies.
Neighborhood effects were found also to be statistically
significant. Initial findings revealed that 13 percent of the variation
in the odds of dropping out can be attributed to neighborhood level
factors. Furthermore, close to two-thirds of the neighborhood-level
variance was explained by the poverty indicator. Specifically, higher
dropout rates were found among youth living in neighborhoods with a
higher proportion of residents living below the LICO. It is important to
point out that that this effect was statistically significant despite
controls for region of origin and the various individuallevel factors.
Given that increased numbers of immigrant youth are living below the
poverty line--and therefore in neighborhoods with cheaper housing and
poorer residents--this finding has important implications that require
attention by researchers and policymakers at all levels of government.
Individual differences also influenced the dropout rate. Gender
differences found in this study parallel those found in the literature
on male "underachievement." The effect of family structure
also is consistent with the general literature. Single parent families
generally possess fewer material and social-emotional resources that
promote student achievement.
Several factors that describe the academic potential and
performance of children were also included. "Age of entry"
indicates whether the student entered secondary school at the modal age
of native-born children. Late entry may result from additional time
needed by newcomers to adjust to the TDSB classroom or because of poor
academic performance of those immigrant children who arrived at an
earlier age but who struggled with the elementary school program. Those
who have failed to accumulate the required credits by grade 9 are more
inclined to dropout of high school. Both adjustment and academic
achievement require language competence. It is, therefore, interesting
that relatively few immigrant students take an ESL course in high
school. This is consistent with Gunderson's (2007) work, which
finds many immigrants are reluctant to enroll their children in ESL as
it limits the time available to study the core-curriculum courses.
Schoolrelated factors reflect district policies and practices or
opportunity structures available within the system. The most salient of
these in the general literature relates to the academic streaming of
children. Those who enter the "vocational" stream are more
likely to dropout than those who elect to follow the
"university" pathway. Choice of a school pathway is determined
by several factors. However, the effects of streaming are of particular
importance to immigrant children who may take a lengthy period of time
before adjusting to the Canadian social and educational norms and
practices.
Policy Initiatives
Recent OECD reviews of school achievement and immigrant adjustment
suggest several school and community practices designed to facilitate
the integration of immigrant children and youth. These include early
intervention with preschoolers to develop language skills; programs
designed to promote the social adjustment of youth; and the removal of
streaming programs that essentially sort students into vocational and
university paths according to ability. Many of these programs take into
consideration differences in the performance and needs of first- and
second-generation students (OECD 2007).
While this analysis suggests that our proxy for generational status
bears little relationship to educational outcomes among immigrant youth
in the TDSB, region of origin nevertheless exerts a significant
influence on school completion that is substantially reduced when
various demographic characteristics and measures of achievement are
controlled. This finding is important because it provides markers for
devising strategies that may lower dropout rates among specific
immigrant groups from diverse countries of origin. For instance,
students from the Caribbean are significantly more likely to enter
school one year late, live in alternate family structures, find
themselves placed in nonacademic streams and be at risk of not
completing their course of study. Many of these risk factors are
responsive to change by working effectively with schools and family. For
instance, special transition programs might be considered for students
entering school late as a means to facilitate adaptation to the social
and academic life of Canadian schools.
In the following section, we consider a number of initiatives that
either have been implemented or could be implemented at the federal,
provincial, and local levels.
Federal
Citizenship and Immigration Canada offers adult newcomers a Host
program which facilitates their integration by matching them with
Canadian volunteers who help with language barriers, with getting
contacts in their field of work, and with everyday interactions, such as
banking, grocery shopping, enrolling in school, and using the transit
system. Anisef et al. (2007) recommend that Host be extended to newcomer
youth entering the Canadian school system. Newcomer youth would be
provided a "buddy" or "mentor" to help them better
manage the difficulties associated with resettlement. Such a program
might be further complemented by calling upon school counselors to work
alongside buddies or mentors to address issues associated with
adaptation and school performance. In addition, school staff might work
closely with the families of those youth most at risk of leaving school
early in order to encourage both academic and social engagement within
the school environment.
Provincial
An important initiative launched by the Ontario Ministry of
Education in 2003 is the Student Success/Learning to 18 Strategy. The
strategy was designed to ensure that all students successfully complete
their secondary schooling with the knowledge and dispositions required
to make effective transitions to postsecondary education or employment
(Ungerleider 2007). The origins and motivations of the strategy can be
traced in part to reactions to a double-cohort longitudinal study by
Alan King (King 2002, 2003; King et al. 2005), which cited low
graduation rates within the province and identified credit accumulation
in grade 9 and 10 as a key predictor of graduation. This research
motivated the development of specific programs to help all students
acquire the required number of secondary school credits and subsequently
graduate from secondary school. While school based programs are a key
element of the Student Success initiative, there is recognition that
programs must extend beyond the school. Thus, programs have also been
developed with the community with parents, employers, community
agencies, and organizations to help inform decision making, and create
opportunities for experiential learning. Although the Student
Success/Learning to 18 Strategy is in its early stages of
implementation, a formal evaluation by the Canadian Council on Learning
indicates that it is working, providing students with a more respectful
and responsive environment and offering more choices for students not
bound for university (Ungerleider 2007:64).
Neighborhood Interventions
As noted above, the proportion of low-income families living in
student neighborhoods was found to be a significant predictor of
dropping out. Linking student postal codes with low-income data from the
Census measured at the DA level essentially assigns each student a
probability of living in a lowincome family. As such, it remains unclear
as to whether this variable is capturing poverty at the neighborhood
level (as implied by the model), the family level, or both. To be sure,
both family- and community-level socioeconomic status have been linked
to student achievement (see, e.g., Pong and Hao 2007; Webber and Butler
2007). The importance of incorporating the neighborhood into school
interventions is at the heart of Pathways to Success, a program aimed at
highly at-risk students. The highly successful program piloted in Regent
Park in downtown Toronto was organized with local community leadership,
and since then each additional program has been organized around and
involving a specific urban community. In many cases (as in Regent Park)
these communities contain diverse immigrant populations.
Secondary and Postsecondary Interventions
Interventions can take place at different parts of the transitions
process; in fact, there is a number of ongoing school, government, and
private programs for immigrant students who are at risk of poor
achievement. The Settlement Workers in Schools program was initially
piloted in the TDSB and has since been implemented in several Ontario
school boards with large immigrant populations (Ontario Council of
Agencies Serving Immigrants 2009). Among its main goals is to provide
assistance to students and parents navigating the Ontario school system
for the first time. A second Ontario initiative (part of the Student
Success/Learning to 18 Strategy) examines the direct transition into the
workplace as well as the process by which students move from the schools
and the workplace into community colleges. For example, dual credit
opportunities leading directly to college and apprenticeships are
available to TDSB and Toronto Catholic District School Board students in
partnership with all community colleges in the Greater Toronto Area
through the School/College/Work/Initiative (SCWI). The SCWI is a
strategy of Student Success/Learning to 18 initiatives introduced by the
Ministry of Education to address the number of students in Ontario who
at risk of not graduating on time. Only students in approved SCWI dual
credit programs may count dual credits toward the OSSD. All programs are
based on collaboration and partnership between school boards and
colleges. While these projects do not specifically target immigrants,
the importance and size of the immigrant population within central
Ontario means that they are an essential piece of the puzzle. An obvious
next step would involve an examination of workplace and postsecondary
transitions in terms of similarities and differences of subgroups within
this very diverse population, similar to what has been done here looking
at dropouts and graduation.
Future Research Directions
The current study contributes to increasing interest in and use of
administrative data to better specify the conditions that shape the
school performance of immigrant youth. At present, there are a number of
studies that investigate adolescent and early adult schooling outcomes
among immigrants to Canada and elsewhere. Typically, these employ
nationally representative samples that do not allow a focused,
contextualized examination of immigrant youth (e.g., Finnie and Mueller
2008; Worswick 2001). By using detailed school administrative data this
study was able to examine dropouts among a grade 9 student cohort in a
single metropolitan city with an ethnically diverse school population
consisting primarily of first- and second-generation immigrants (Yau and
O'Reilly 2007). To the extent that the student body of the TDSB is
predominantly immigrant, it anticipates the future demographic profile
of the province and the country.
The value of administrative data in studying this emerging cultural
diversity among the school-age population is seen in ongoing research
initiatives undertaken at the regional and national level. There are
currently a number of projects throughout Ontario where schools boards
are combining their data in similar ways, encouraged by the Association
of Educational Researchers of Ontario, the professional body of Ontario
board researchers, and the Ontario Ministry of Education. In addition, a
pilot project used administrative data on grade 9 student cohorts from
Toronto, Vancouver, and Montreal to compare achievement and school
completion (McAndrew et al. 2009). The basis for comparison--language
spoken at home--revealed similarities in the pattern of achievement
based on country-of-origin differences. That project allowed researchers
to look at similarities and differences in how different cultures
interact with educational systems in the three largest Canadian cities.
Future research that employs administrative data promises to contribute
to the challenging task of explaining the progress of immigrant youth
groups (defined by country of origin and home language) through the
Canadian school systems and their transitions to postsecondary education
and the workplace.
References
Alba, R.D. and V. Nee. 2003. Remaking the American Mainstream:
Assimilation and Contemporary Immigration. Cambridge, M.A: Harvard
University Press.
Anisef, P. and K.M. Kilbridge. 2003. Managing Two Worlds: The
Experiences and Concerns of Immigrant Youth in Ontario. Toronto, ON:
Canadian Scholars Press.
Anisef, P., M. Poteet, D. Anisef, G. Farr, C. Poirier and H. Wang.
2007. "Issues Confronting Newcomer Youth in Canada: Alternative
Models for a National Youth Host Program." CERIS Policy Matters No.
29.
Aydemir, A. and M. Skuterud. 2004. Explaining the Deteriorating
Entry Earnings of Canada's Immigrant Cohorts: 1966-2000. Ottawa,
ON: Statistics Canada.
Bloom, D.E, G. Grenier and M. Gunderson. 1995. "The Changing
Labour Market Positions of Canadian Immigrants." Canadian Journal
of Economics 28:987-1005.
Bowlby, G. 2005. "Provincial Drop Out Rates--Trends and
Consequences." Education Matters, Statistics Canada, Cat. 81-004
XIE.
Bowlby, G. and K. McMullen. 2002. At a Crossroads: First Results
for the 18-20 Year Old Cohort of the Youth in Transition Survey. Ottawa,
ON: Human Resources Development Canada.
Boyd, M. 2002. "Educational Attainments of Immigrant
Offspring: Success or Segmented Assimilation?" International
Migration Review 36:1037-60.
Boyd, M. and E.M. Grieco. 1998. "Triumphant Transitions;
Socioeconomic Achievements of the Second Generation in Canada."
International Migration Review 32:853-76.
Bushnik, T., L. Barr-Telford and P. Bussiere. 2004. In and Out of
High School: First Results from the Second Cycle of the Youth in
Transition Survey. Ottawa, ON: Statistics Canada.
Cahan, S., D. Davies and R. Staub. 2001. "Age at Immigration
and Scholastic Achievement in School-Age Children: Is There a Vulnerable
Age?" International Migration Review 35:587-95.
Corak, M. 2005. "Equality of Opportunity and Inequality Across
the Generations: Challenges Ahead." Policy Options 26:78-83.
Finnie, R. and R. Mueller. 2008. "Access to Post-Secondary
Education in Canada among First and Second Generation Canadian
Immigrants: Raw Differences and Some of the Underlying Factors."
Working Paper. Montreal: Millennium Foundation.
Frenette, M. and R. Morissette. 2003. Will They Ever Converge?
Earnings of Immigrant and Canadian-Born Workers over the Last Two
Decades. Ottawa, ON: Statistics Canada.
Gans, H. 1992. "Second Generation Decline: Scenarios for the
Economic and Ethnic Futures of the Post-1965 American Immigrants."
Ethnic and Racial Studies 15:173-91.
Gans, H. 1997. "Towards a Reconsideration of
'Assimilation and Pluralism': The Interplay of Acculturation
and Ethnic Relations." International Migration Review 31:875-92.
Glick, J.E. and M.J. White. 2003. "The Academic Trajectories
of Immigrants Youths: Analysis within and Across Cohorts."
Demography 40:759-83.
Gunderson, L. 2007. English Only Instruction and Immigrant Students
in Secondary Schools: A Critical Examination. Mahwah, NJ: Lawrence
Erlbaum Associates.
Herberg, E.R. 1998. "The Ethno-Racial Socioeconomic Hierarchy
in Canada: Theory and Analysis of the New Vertical Mosaic."
International Journal of Comparative Sociology 31:206-21.
Hospital for Sick Children. 2005. Early School Leavers:
Understanding the Lived Reality of Students Disengagement from Secondary
School: Final Report. Toronto, ON: Ontario Ministry of Education and
Training, Special Education Branch.
Human Resources Development Canada. 2000. Dropping Out of High
School: Definitions and Costs. Ottawa, ON: Applied Research Branch,
Author.
Jones, C., L. Clark, J. Grusec, R. Hart, G. Plickert and L.
Tepperman. 2002. Poverty, Social Capital, Parenting and Child Outcomes
in Canada. Applied Research Branch, Strategic Policy. Ottawa: Human
Resources Development Canada.
Kazemipur, A. and S.S. Halli. 2000. The New Poverty in Canada:
Ethnic Groups and Ghetto Neighbourhoods. Toronto, ON: Thompson
Educational Publishing.
Kazemipur, A. and S.S. Halli. 2001a. "The Changing Colour of
Poverty in Canada." Canadian Review of Sociology and Anthropology
38:217-38.
Kazemipur, A. and S.S. Halli. 200lb. "Immigrants and the New
Poverty: The Case of Canada." International Migration Review
38:1129-56.
King, A. 2002. "Double Cohort Study: Phase 2 Report for the
Ontario Ministry of Education." Retrieved February 24, 2010
(http://www.edu.gov.on.ca/eng/document/reports/cohortph2.pdf).
King, A. 2003. "Double Cohort Study: Phase 3 Report for the
Ontario Ministry of Education." Retrieved February 24, 2010
(http://www.edu.gov.on.ca/eng/document/reports/phase3/report3.pdf).
King, A.J.C., W.K. Warren, J.C. Boyer and P. Chin. 2005.
"Double Cohort Study: Phase 4." Report submitted to the
Ontario Ministry of Education. Retrieved February 24, 2010
(http://www.edu.gov.on.ca/eng/policyfunding/reports.html).
King, A.J.C., W.K. Warren, C. Michalski and M.J. Pearlt. 1988.
Improving Student Retention in Ontario Secondary Schools. Toronto:
Ministry of Education.
Krahn, H. and A. Taylor. 2005. "Resilient Teenagers:
Explaining the High Educational Aspirations of Visible-Minority Youth in
Canada." Journal of International Migration and Integration
6:405-34.
Kunz, J.L. and J. Frank. 2004. "Poverty, Thy Name is
Hydra." Horizons: Policy Research Initiative 7:4-8.
Levin, B. 2007 "Enduring Issues in Urban Education."
Paper presented to the Canadian Society for the Study of Education, May,
Saskatoon, Saskatchewan.
Luthar, S. 1999. Poverty and Children's Adjustment. Thousand
Oaks, CA: Sage Publications.
McAndrew, M. et al., 2009. "Educational Pathways and Academic
Performance of Youth of Immigrant Origin: Comparing Montreal, Toronto
and Vancouver." Report submitted to the Canadian Council on
Learning/Citizenship and Immigration Canada.
OECD. 2006. Where Immigrant Students Succeed--A Comparative Review
of Performance and Engagement in PISA 2003. Programme for International
Student Assessment. Paris: OECD.
OECD. 2007. No More Failures: Ten Steps to Equity in Education.
Education & Skills Number 15. Paris: OECD.
Ontario Council of Agencies Serving Immigrants. 2009.
"Settlement Workers in Schools (SWIS): Background
Information." Retrieved March 10, 2009
(http://atwork.settlement.org/sys/at
work_library_detail.asp?doc_id=1003365).
Ornstein, M. 2000. Ethno-Racial Inequality in Metropolitan Toronto:
An Analysis of the 1996 Census. Toronto, ON: Municipality of
Metropolitan Toronto, Access and Equity Centre.
Picot, G. and F. Hou. 2003. The Rise in Low-Income Rates among
Immigrants in Canada. Ottawa, ON: Statistics Canada.
Picot, G., F. Hou and S. Coulombe. 2007. Chronic Low Income and
Low-Income Dynamics among Recent Immigrants. Ottawa, ON: Statistics
Canada.
Picot, G. and A. Sweetman. 2005. "The Deteriorating Economic
Welfare of Immigrants and Possible Causes: Update 2005." Analytical
Studies Branch Research Paper Series, Statistics Canada, Cat. No.
11F0019MIE-No. 262.
Pong, S. and L. Hao. 2007. "Neighborhood and School Factors in
the School Performance of Immigrants' Children." The
International Migration Review 41:206-41.
Portes, A. 1995. "Economic Sociology and the Sociology of
Immigration: A Conceptual Overview." Pp. 1-41 in The Economic
Sociology of Immigration, edited by A. Portes. New York: Russell Sage
Foundation.
Portes, A. and R.G. Rumbaut. 2001. Legacies: The Story of the
Immigrant Second Generation. New York: Russell Sage Foundation.
Portes, A. and M. Zhou. 1993. "The New Second Generation:
Segmented Assimilation and It's Variants." Annals of the
American Academy of Political and Social Science 530:74-96.
Putnam, R. 2000. Bowling Alone: The Collapse and Revival of
American Community. New York: Simon and Schuster.
Rodriguez, T.D. 2002. "Oppositional Culture and Academic
Performance among Children of Immigrants in the USA." Race,
Ethnicity and Education 5:199-215.
Ross, D.P. and P. Roberts. 1999. "Income and Child Well-being:
A New Perspective on the Poverty Debate." Canadian Council for
Social Development, Report No. 552.
Statistics Canada. 2005. The Daily. Ottawa, ON: Statistics Canada.
Statistics Canada. 2006a. The Daily. Ottawa, ON: Statistics Canada.
Statistics Canada. 2006b. Census of Population. Ottawa, ON:
Statistics Canada.
Statistics Canada. 2007. The Daily. Ottawa, ON: Statistics Canada.
Statistics Canada. 2008. "Community Profiles." Retrieved
September 30, 2009 (http://www.statcan.ca).
Ungerleider, C. 2007. "Evaluation of the Ontario Ministry of
Education's Student Sucess/ Learning to 18 Strategy, Stage 1
Report." Canadian Council on Learning, Vancouver.
United Way of Greater Toronto and the Canadian Council on Social
Development. 2004. "Poverty by Postal Code: The Geography of
Neighbourhood Poverty 1981-2001." United Way of Greater Toronto.
Retrieved February 24, 2010
(http://www.unitedwaytoronto.com/who_we_help/pdfs/PovertybyPostalCodeFinal .pdf).
Warburton, R.N. and P. Warburton. 2004. "Canada Needs Better
Data for Evidence-Based Policy: Inconsistencies between Administrative
and Survey Data on Welfare Dependence and Education." Canadian
Public Policy 30:242-55.
Webber, R. and T. Butler. 2007. "Classifying Pupils by Where
They Live: How Well Does This Predict Variations in their GCSE
Results?" Urban Studies 44(7): 1229-53.
Worswick, C. 2001. School Performance of the Children of Immigrants
in Canada, 1994-98. Ottawa, ON: Statistics Canada.
Yau, M. and J. O'Reilly. (2007). 2006 Student Census, Grades
7-12: System Overview. Toronto, ON: Toronto District School Board.
Zeman, K. 2007. "A First Look at Provincial Differences in
Education Pathways from High School to College and University."
Education Matters. Ottawa: Statistics Canada, Catalogue Number
81-004-XIE - June 2007, volume 4 number 2.
Zhou, M. 1997. "Segmented Assimilation: Issues, Controversies,
and Recent Research on the New Second Generation." International
Migration Review 31:975-1008.
PAUL ANISEF
York University
ROBERT S. BROWN
Toronto District School Board
KELLI PHYTHIAN
University of Western Ontario
ROBERT SWEET
Lakehead University
DAVID WALTERS
Guelph University
(1.) Often, administrative data are poorly maintained, subject to
administrative changes, or ill suited to answer research questions.
Moreover, access to administrative data can be difficult to obtain.
(2.) The first generation are the foreign born, the second
generation includes those who were born in Canada to immigrant parents,
and the third-plus generation consists of the offspring the Canadian
born. The third generation is often grouped with later generations
(referred to as the third-plus generation) for theoretical and empirical
simplification.
(3.) This difference of one proficiency level can be considered
comparatively large. See Bushnik et al. (2004).
(4.) When the cohort study started in Fall 2000, the Ontario
curriculum provided ESL-ESD courses (English as a Second
Language/English as a Second Dialect). Since then, "ESD" has
been changed to "ELL," English Language Literacy. The vast
majority of courses were ESL, and we will refer to all ESL-ESD-ELL
courses as "ESL" in this paper.
(5.) It is probable that many of these English-speaking,
Canadian-born students were taking ESD or ELL courses.
(6.) Approximately 10 percent of the cohort left the TDSB for
another school board. Since we were unable to track the education
records of these students after leaving the TDSB, we removed them from
the analysis.
(7.) The number of students in the full sample was 16,249.
List-wise deletion was used for missing data and this resulted in a
final sample of 12,138. The majority of deleted observations are removed
as a result of our selection process.
(8.) Thus, for mixed models with a Bernoulli sampling distribution,
the intraclass correlation is calculated as [rho] =
[[tau].sub.00]/([[tau].sub.00] + [[pi].sup.2]/3), where [[tau].sup.00]
is variance at level 2.
(9.) If this estimate was not statistically significant we would
have proceeded to estimate a simple logistic regression model.
(10.) The LICO variable is centered at its grand mean.
(11.) When not otherwise stated, all of the interpretations for
Model 3 are made controlling for the other predictors in the model, and
holding constant the value of the random effect, [[mu].sub.0j].
(12.) Since LICO is reverse coded, the negative coefficient
indicates that students residing in the lowest incidence neighborhoods
are least likely to drop out of high school.
Authors are listed in alphabetical order and we acknowledge the
assistance of Etta Baichman-Anisef in editing this paper.
Paul Anisef, York University, 335 York Lanes, 4700 Keele Street,
Toronto, ON, Canada M3J 1P3. E-mail:
[email protected]
Table 1
Descriptive Results for Variables in the Study, Separated by
Region of Origin (n = 12,138)
Mean/proportion
Canada
Canada (non-
(English) English) Caribbean Africa
Dropout
Yes .19 .18 .40 .23
No .81 .82 .60 .77
Sex
Female .49 .47 .50 .53
Male .51 .53 .50 .47
Age of entry
On time .97 .98 .88 .89
One year late .03 .02 .12 .11
Living situation
Both parents .50 .72 .26 .42
Alternative .50 .28 .74 .58
structure
Streaming level
Academic .78 .83 .39 .59
Applied .21 .15 .53 .38
Essentials .02 .02 .08 .03
At risk
At risk .14 .13 .33 .22
Not at risk .86 .87 .67 .78
Taken ESL courses
NO .99 .99 .90 .85
Yes .01 .01 .10 .15
LICO 6.41 5.48 4.17 3.44
n 6,697 1,297 460 338
Mean/proportion
Eastern South Western
Europe Asia Asia Asia p
Dropout ***
Yes .15 .10 .16 .22
No .85 .90 .84 .78
Sex
Female .49 .47 .50 .49
Male .51 .53 .50 .51
Age of entry ***
On time .95 .92 .94 .95
One year late .05 .08 .06 .05 ***
Living situation
Both parents .74 .59 .49 .66
Alternative .26 .41 .51 .34
structure
Streaming level ***
Academic .85 .90 .78 .75
Applied .14 .09 .20 .24
Essentials .01 .01 .02 .02
At risk ***
At risk .10 .07 .11 .16
Not at risk .90 .93 .89 .84
Taken ESL courses
NO .81 .72 .78 .74 ***
Yes .19 .28 .22 .26
LICO 4.95 5.37 3.88 4.13 ***
n 800 1,027 1,094 425
*** p <.001.
LICO, low-income cutoff.
Table 2
Hierarchical Generalized Linear Model Predicting Dropout from the
Independent Variables (n = 12,128)
Model l
b SE(b) p
Fixed effects
Constant -1.627
Country of origin
Caribbean
Africa
Europe
Eastern Asia
South Asia
Western Asia
Canada (non-English)
Canada (English)
Sex
Male
Female
Age of entry
One year late
On time
Living situation of student
Alternative family
structure
Living with both parents
Streaming level
Applied
Essentials
Academic
At risk of not completing
At risk
Not at risk
Taken ESL courses
Yes
No
Level 2
LICO
Random effects
Variance of the random .498
intercept
Intraclass .131 ***
correlation ([rho])
Model 2
b SE(b) p
Fixed effects
Constant -1.544
Country of origin ***
Caribbean 1.029 (.11) ***
Africa 0.152 (.144)
Europe -0.298 (.11) **
Eastern Asia -0.808 (.114) ***
South Asia -0.305 (.096) **
Western Asia 0.148 (.13)
Canada (non-English) -0.153 (.084)
Canada (English) (Ref) --
Sex
Male
Female
Age of entry
One year late
On time
Living situation of student
Alternative family
structure
Living with both parents
Streaming level
Applied
Essentials
Academic
At risk of not completing
At risk
Not at risk
Taken ESL courses
Yes
No
Level 2
LICO
Random effects
Variance of the random .402
intercept
Intraclass .109 ***
correlation ([rho])
Model 3
b SE(b) p
Fixed effects
Constant -2.168
Country of origin ***
Caribbean .144 (.129)
Africa -.396 (.168) *
Europe -.067 (.124)
Eastern Asia -.577 (.131) ***
South Asia -.295 (.111) **
Western Asia .079 (.148)
Canada (non-English) .006 (.095)
Canada (English) (Ref) --
Sex ***
Male .345 (.057) ***
Female (Ref) --
Age of entry ***
One year late .590 (.113) ***
On time (Ref) --
Living situation of student ***
Alternative family .294 (.058) ***
structure
Living with both parents (Ref) --
Streaming level ***
Applied 1.014 (.067) ***
Essentials 1.336 (.167) ***
Academic (Ref) --
At risk of not completing ***
At risk 2.169 (.076) ***
Not at risk (Ref) --
Taken ESL courses
Yes -.119 (.11)
No (Ref) --
Level 2
LICO -.055 (.011) ***
Random effects
Variance of the random .168
intercept
Intraclass .049 *
correlation ([rho])
* p value <.5.
** p value <.01.
*** p value <.001.
Standard errors are in parentheses.
LICO, low-income cutoff.
Ref, reference category or group.
