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choices
Vol. 12, no. 5, October 2006 ISSN 0711-0677 www.irpp.org
Investing in Our Children
IRPP
Marni Brownell,
Noralou Roos,
Randy Fransoo et al.
Is the Class
Half Empty?
A Population-Based
Perspective on
Socioeconomic Status
and Educational
Outcomes
Founded in 1972, the Institute for Research on
Public Policy is an independent, national,
nonprofit organization.
IRPP seeks to improve public policy in Canada by
generating research, providing insight and sparking
debate that will contribute to the public policy
decision-making process and strengthen the quality of
the public policy decisions made by Canadian
governments, citizens, institutions and organizations.
IRPP's independence is assured by an endowment fund
established in the early 1970s.
Fondé en 1972, l’Institut de recherche en
politiques publiques (IRPP) est un organisme
canadien, indépendant et sans but lucratif.
L’IRPP cherche à améliorer les politiques publiques
canadiennes en encourageant la recherche, en mettant
de l’avant de nouvelles perspectives et en suscitant des
débats qui contribueront au processus décisionnel en
matière de politiques publiques et qui rehausseront la
qualité des décisions que prennent les gouvernements,
les citoyens, les institutions et les organismes
canadiens.
L’indépendance de l’IRPP est assurée par un fonds de
dotation établi au début des années 1970.
This publication was produced under the
direction of Sarah Fortin, Research Director, IRPP.
The manuscript was copy-edited by Jane
Broderick, proofreading was by Mary Williams,
production was by Anne Tremblay, art direction
was by Schumacher Design and printing was by
Impressions Graphiques.
Copyright belongs to IRPP. To order or request
permission to reprint, contact:
IRPP
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Montreal, Quebec H3A 1T1
Telephone: 514-985-2461
Fax: 514-985-2559
E-mail: irpp@irpp.org
All
IRPP Choices
and
IRPP Policy Matters
are
available for download at wwwwww..iirrpppp..oorrgg
To cite this document:
Brownell, Marni, Noralou Roos, Randy Fransoo et
al. 2006. “Is the Class Half Empty? A Population-
Based Perspective on Socioeconomic Status and
Educational Outcomes.”
IRPP Choices
12 (5).
The opinions expressed in this paper are those of the authors and
do not necessarily reflect the views of IRPP or its Board of Directors.
1
About the Authors
MMaarrnnii BBrroowwnneellll is a senior researcher with the
Manitoba Centre for Health Policy and assistant pro-
fessor in the Department of Community Health
Sciences, Faculty of Medicine, University of
Manitoba. She has been the recipient of a Canadian
Institutes of Health Research New Investigator Award
and is a core member of Raising and Leveling the
Bar, a national collaborative research initiative on
children’s learning, behavioural and health outcomes
jointly funded by the Canadian Institute for
Advanced Research and the Social Sciences and
Humanities Research Council. Her background is in
developmental psychology and her research interests
include the role of socioeconomic factors in chil-
dren’s health and development.
NNoorraalloouu RRooooss is founder of the Manitoba Centre for
Health Policy and was its director until 2004. Her
research is focused on populations’ use of the health
care system and the role of medical care and other
factors as determinants of health. Her research,
employing routinely collected administrative data,
has created a new model for population health
research in Canada. A focus of her career has been
understanding policy-makers’ need for research on
these issues and communicating the evidence derived
from the research across the academic/policy inter-
face. She holds a tier 1 Canada Research Chair and
was recently awarded the Order of Canada.
RRaannddyy FFrraannssoooo is a researcher with the Manitoba
Centre for Health Policy and a candidate in the Ph.D.
program in the Department of Community Health
Sciences, Faculty of Medicine, University of
Manitoba. He has been involved with numerous proj-
ects at MCHP, most notably research on physician
supply and services, and with documenting health
status and health care use for Manitoba’s Regional
Health Authorities. He is a core member of the Need
to Know team, a nationally recognized and funded
project to engage researchers with provincial and
regional health managers to create new research and
effectively translate the findings into policy and pro-
gram changes. In his doctoral research, he is quanti-
fying the effect of children’s health status at birth
and beyond on their progress and performance in
school to age eight.
Acknowledgements
We are grateful to the following individuals
for helping to make this research possible:
John VanWalleghem, Richard Perrault,
Carol Crerar, Jean Britton, Ken Clark, Irene Huggins,
Randy Stankewich and Shirley McLellan from
Manitoba Education, Citizenship and Youth; Louis
Barre from Manitoba Health; and Charles Burchill,
Patrick Nicol, Natalia Dik, Shelley Derksen, Bogdan
Bogdanovic, Monica Sirski, Randy Walld, Dan
Chateau and Shannon Lussier from the Manitoba
Centre for Health Policy.
We are indebted to Systems and Technology
Services and Assessment and Evaluation, Manitoba
Education, Citizenship and Youth, as well as Health
Information Management, Manitoba Health, for the
provision of data.
The research leading to the preparation of this
report was undertaken as part of a research team
composed of the following individuals: Leslie L. Roos
(director of the Population Health Research Data
Repository at the Manitoba Centre for Health Policy);
Anne Guèvremont (RBC Financial Group Research
Fellow at the Manitoba Centre for Health Policy);
Leonard MacWilliam (data analyst, Manitoba Centre
for Healthy Policy); Lauren Yallop (graduate student
in clinical psychology at the University of Manitoba
and a research coordinator at the Manitoba Centre for
Health Policy); and Ben Levin (deputy minister of
education for Ontario, a position he holds on leave
from a Canada Research Chair in education policy
and leadership at the Ontario Institute for Studies in
Education, University of Toronto). They deserve the
same recognition for this paper as the lead authors.
This research was funded by the Canadian
Population Health Initiative, a program of the
Canadian Institute for Health Information and the
RBC Financial Group Child Health Award. The views
expressed herein do not necessarily represent those of
the Canadian Institute for Health Information or the
data providers.
2
Contents
3 Introduction
4 Socioeconomic Status and Social Outcomes
5 Developing a Population-Based Approach:
The Manitoba Experience
9 Using Population-Based Data to Describe
Socioeconomic Inequalities in Educational
Outcomes: The Manitoba Example
11 Educational Outcomes in Manitoba
19 Policy Implications
22 Conclusion
24 Notes
25 References
Investing in Our Children /
Investir dans nos enfants
Research Director / Directrice de recherche
Sarah Fortin
This research program examines issues related to
family policy from the perspective of lifetime
investment in human capital based on in-depth
empirical and analytical evidence of the strengths
and weaknesses of current policies as well as evi-
dence supporting alternative strategies. The IRPP's
research in this area focuses on recent developments
across the country in policies that are geared toward
children.
Ce programme examine les politiques publiques
familiales selon une perspective d'investisse-
ment à long terme dans le capital humain et
sur la base d'études empiriques et analytiques des
forces et faiblesses de nos politiques actuelles, et
explore des stratégies de rechange. Il met l'accent sur
les récents choix des gouvernements fédéral et
provinciaux en matière de politiques destinées à l'en-
fance.
3
Is the Class Half Empty? by Marni Brownell, Noralou Roos, Randy Fransoo et al.
Introduction
Recent years have seen more and more
demands for educational systems to be
accountable for student outcomes. This is not
surprising given the importance of quality education
for employment opportunities and economic power in
our increasingly knowledge-based economies
(Keating and Hertzman 1999).
With the demands for accountability have come
policy initiatives on reporting of student performance;
as a result, reports comparing educational test results
across different schools within a region, across regions
and across countries are now common (Bussière et al.
2001; Canadian Education Statistics Council 2003;
Martin et al. 2000; Most 2003; Mullis et al. 2000;
Organisation for Economic Co-operation and
Development [OECD] 2001; Willms 1997; Wirt et al.
2003). Canada has been shown to score among the top
OECD countries in reading, mathematics and science
on the Programme for International Student
Assessment (PISA), with American students at the
average (OECD 2001, 2004). Of course, there is room
for improvement. On the literacy scales of the
International Adult Literacy and Skills Survey (IALSS),
almost half of the Canadian adult population scored
below the level of competence considered necessary
for coping in a knowledge-based economy (Statistics
Canada 2005). These various reports have led to sig-
nificant changes in education policy; results from
IALSS 2003, for example, contributed to the develop-
ment of a pan-Canadian strategy on literacy, and
OECD recommendations based on PISA results led to
the development of the Canadian Council on Learning.
It is therefore vital that assessments provide a com-
plete picture of student performance. But do these
tests provide the full story on student achievement?
This report describes the development and use of
population-based databases and illustrates their role
in drawing a more complete picture of educational
outcomes using one such database in Manitoba. A
Is the Class Half
Empty?
A Population-Based Perspective
on Socioeconomic Status and
Educational Outcomes
Marni Brownell, Noralou Roos,
Randy Fransoo et al.
IRPP Choices, Vol. 12, no. 5, October 2006
4
tion between socioeconomic status and school perform-
ance has also been demonstrated in many precursors to
educational success, including preschool conversational
skills (Hoff-Ginsberg 1991), vocabulary development
(Willms 2002), literacy competence (Willms 1997,
2003), mathematical skills (Case, Griffin and Kelly
1999), memory performance (Herrmann and Guadagno
1997) and school attendance (Haveman and Wolfe
1995). Some researchers have argued that differences in
performance across socioeconomic levels can be attrib-
uted to differences in intelligence (Herrnstein and
Murray 1994); however, others have argued convinc-
ingly that inequalities in educational outcomes have
very little to do with individual or group differences in
ability and are largely the result of social conditions
and policies (Fischer et al. 1996). More recently,
Turkheimer and colleagues have demonstrated that
genetic influences on ability are most apparent in
affluent families — that is, well-off households have the
resources needed to provide for the fullest development
of a child’s natural abilities (2003); children in less
affluent families are much less likely to reach their full
potential (Kirp 2006).
Education is not the only outcome related to
socioeconomic status. Health is strongly related to it,
with both adults and children at lower socioeconomic
levels experiencing poorer health and higher rates of
death across a wide range of disease categories (see,
for example, Adler et al. 1993; Brooks-Gunn, Duncan
and Britto 1999; Chen, Matthews and Boyce 2002;
Gissler et al. 1998; Marmot et al. 1991; Mustard et al.
1997; Raphael 2004). Emotional and behavioural dis-
orders in children are also strongly related to
socioeconomic status; children from families at low
socioeconomic levels are more likely to have one or
more emotional or behavioural disorders (Offord and
Lipman 1996) and to engage in physically aggressive
and delinquent behaviour (Ross, Roberts and Scott
2000; Tremblay 1999).
This well-established relationship between socio-
economic status (SES) and social outcomes is not just
a case of impoverished children having poor outcomes
when compared to others. Children from lower-middle
SES families have poorer outcomes than children from
middle-SES families, who in turn have poorer out-
comes than children from upper-middle SES families.
Each increase in socioeconomic status raises the like-
lihood of positive outcomes. This association between
socioeconomic status and social outcomes is referred
to as the socioeconomic gradient (Marmot et al. 1991;
Willms 2003). The term “gradient” conveys the idea
population-based analysis is one that is conducted
on the entire population, rather than only on school-
children. In contrast, surveys and school-based test-
ing, which are how most Canadian provinces evalu-
ate students and school performance, typically
include only those children who reach a specific
grade and may provide a limited picture of the true
outcomes of students; low-performing children may
have already fallen behind or even dropped out of
school (Roos et al. forthcoming). Since those students
who fall behind or drop out are disproportionately
children from disadvantaged backgrounds, school-
based testing limits our ability to assess the real
inequalities in educational achievement.
The purpose of this report is twofold: to provide a
model for those jurisdictions that have the potential
to implement similar population-based methods in
their own provinces or school districts; and to
outline the insights and implications of population-
based work for researchers, educators and policy-
makers. We begin with a brief summary of the
relationship between socioeconomic status and social
outcomes. We follow with a discussion of the impor-
tance of building information systems to make better
use of existing data in order to inform policy; the
data repository at the Manitoba Centre for Health
Policy (MCHP) is used as an example of what can be
done. We then provide examples of how population-
based analyses in Manitoba have revealed far greater
socioeconomic disparities in educational outcomes
than had been previously realized. Analyses are
divided according to region of residence (Winnipeg
versus the rest of the province), socioeconomic status
and sex. We finish with a discussion of the policy
implications of the research and the recommenda-
tions that follow from this work.
Socioeconomic Status and Social
Outcomes
Achild’s performance in school is strongly
related to socioeconomic status. Children in
families or areas with higher levels of educa-
tion, employment and income (the major components
of socioeconomic status) generally do better in school
than children in families or areas with lower levels.
Indeed, socioeconomic status is the single most pow-
erful predictor of educational outcomes (Gorard, Fitz
and Taylor 2001; Ma and Klinger 2000). This associa-
5
Is the Class Half Empty? by Marni Brownell, Noralou Roos, Randy Fransoo et al.
grade are assessed, which results in performance
being measured only for those students who have
made it far enough in the system to be examined.
Because those children who are absent on the day of
the test, have been retained by one grade or more, or
have withdrawn from school tend to be lower-
achieving than those who take the test, analyses of
outcomes can be misleading: they include only those
students in a given grade present to take the test.
This paper proposes an alternative (or complemen-
tary) population-based approach focusing on the per-
formance of all children of a given age regardless of
where, or whether, they are enrolled in the school
system. Also examined in this approach are out-
comes based on where children live rather than on
where they go to school. Because student perform-
ance is strongly associated with socioeconomic sta-
tus, it is reasonable to use this status as the funda-
mental organizing principle in a population-based
approach to analyzing educational achievement.
Simply presenting the mean scores for different
schools or for different areas of a city tells us little
about why these scores are different. Organizing
results by the socioeconomic status of area residents
helps us to move from blaming schools and teachers
for poor performance to identifying the policy
approaches necessary to ensure that all children have
a chance to achieve their potential.
Developing a Population-Based
Approach: The Manitoba
Experience
Over the last three decades, researchers at
MCHP have built a research data repository
that consists of a number of administrative
databases routinely created as part of the Manitoba
government’s system of managing services. Although
the information in these databases was originally
collected for purposes other than research, it has
proved to be a powerful research tool. Numerous
studies have demonstrated the validity and utility of
using this information for health services and policy
research (Roos, Menec, and Currie 2004; Roos and
Nicol 1999), and MCHP has built an international
reputation for conducting high-quality research in
this area (Evans and Mustard 1999).
In 1991 MCHP began to develop a health informa-
tion system that included information on the utilization
that the change in outcomes is gradual and occurs
across the full range of socioeconomic levels.
Education itself is often seen as a means for
changing the gradient in social outcomes, with
investments in education perceived as promoting
equality of opportunity across social groups. Indeed,
schooling appears to be able to attenuate the rela-
tionship between socioeconomic status and educa-
tional outcomes. A study of schools in North
Vancouver found that a primary-level literacy pro-
gram reduced the association between socio-
economic status and literacy skills with each pro-
gressive year of participation (D’Angiulli, Siegel and
Hertzman 2004). Frempong and Willms (2002) pro-
vide evidence from the National Longitudinal
Survey of Children and Youth suggesting that chil-
dren of similar ability and socio-economic status
will have substantially different levels of
mathematical achievement according to whether
they attend a school with above-average or below-
average performance. This may help to explain the
widening social gap in test scores observed as chil-
dren progress through school (Willms 1997); chil-
dren of higher socio-economic status tend to attend
better-quality schools (Currie and Thomas 2001).
Measuring educational outcomes
The research findings cited above not only highlight
the role of education in fostering equality of opportu-
nity across social groups, but underscore the impor-
tance of having a system in place to monitor outcomes
and determine the impact of programs and policies
intended to reduce socioeconomic disparities. As a
result of increasing demands for accountability on the
part of the education system, a new set of policies has
been initiated, focused on the reporting of student per-
formance. Most Canadian provinces now have some
form of achievement testing at various stages within
the elementary and/or secondary levels, designed to
assess curriculum-based standards. Although test
results have often been used to highlight differences in
performance across schools or school districts, they are
also a means for assessing how well schools are serv-
ing students from different socioeconomic back-
grounds. Often, this is the only kind of information
available to the schools for assessing socioeconomic
disparities in student performance.
But how accurate are these provincial educational
assessments as a means for comparing the outcomes
of students from different socioeconomic back-
grounds? Typically, only students in one particular
IRPP Choices, Vol. 12, no. 5, October 2006
6
What is needed to build a population-based
information system?
Central to the MCHP’s population-based research data
repository is the population-based research registry.
This registry is based on an anonymized version of the
population registry maintained by Manitoba Health
(the Ministry of Health) and contains information for
every individual registered to receive health services in
the province. It includes, for each registrant, an
encrypted personal health identification number
(PHIN), demographic characteristics (for example, age
and sex), location of residence (according to postal
code) and family composition. It has been built over
the course of 30 years and includes demographic
information on individuals from 1970 onwards, allow-
ing for longitudinal and intergenerational analyses.
While not all provinces have longitudinal registry
information, most possess the minimal amount of data
required to build a research registry, including infor-
mation on date of birth and/or entry into the province,
date of death and/or migration out of the province,
and place of residence within the province. This infor-
mation allows for the tracking of all residents of the
province and represents a source for developing
denominators for research. In the absence of data for a
research registry, publicly available census data can be
used to build denominators.
Databases to be included in a population-based
information system depend on availability. As stated
above, the MCHP repository relies on administrative
databases, generally collected through provincial minis-
tries. Most provinces now have some form of provincial
educational assessment, given to all students at a par-
ticular level, and hold the results in computerized data-
bases. As well, most provinces have a computerized
student information system that includes not only an
individualized student number but also data on age,
sex and grade. Additional school information, such as
data on marks, type of program, special status and high
school completion, may also be available.
Information on socioeconomic status is also neces-
sary, particularly for research on the association
between socioeconomic factors and educational out-
comes. At MCHP, area-level measures of socioeconomic
status are based on publicly available census data.
Research on Manitoba data has found that area-level
income measures provide a good approximation of
household income (Mustard et al. 1999). Census data,
available at the level of dissemination area (about 400
to 600 individuals), include socioeconomic information
such as average household income, education level of
of health services, as well as information on factors
outside the health care system that are known to influ-
ence health, such as socioeconomic status (for detailed
descriptions of this system, see Roos and Shapiro 1995,
1999). This health information system is population-
based. As described above, it is based on the entire
population of Manitoba. Researchers can consider out-
comes based on where people live rather than on where
they have received their health care or on the volume
of services provided by a particular physician or hospi-
tal. This approach allows us to describe the differences
in outcomes across populations, and embeds these dif-
ferences in the context of the various characteristics of
the population that may be related to the outcomes
under study. As an example, a population-based
approach to studying health and health care allows for
a focus on how health status varies across populations
(for example, are people living in the southern regions
of the province healthier than those living in the north-
ern regions?), what factors are associated with poor
health (for example, is poor health in the north related
to provision of health services, or to higher unemploy-
ment rates?), and whether the implementation of
particular policies or programs has had an impact on
population health (for example, are hospital bed clo-
sures associated with poorer health outcomes?). Other
research centres, both in Canada (for example, the
Centre for Health Services and Policy Research in
British Columbia, the Institute for Clinical and
Evaluative Sciences in Ontario) and abroad (for exam-
ple, the state of Western Australia, the Oxford Record
Linkage Study, the Scottish Record Linkage System, the
Rochester Epidemiology Project), have developed simi-
lar capabilities for population-based analysis (Roos,
Menec and Currie 2004).
The Manitoba repository has expanded in recent
years, in part due to the recognition that health sta-
tus is influenced by multiple factors outside the
health care system. This expansion has entailed the
addition of databases from the education and social
services systems. This expanded repository is a pow-
erful vehicle for addressing important policy issues
in education. The ability to combine information on
individual background (such as area-level socio-
economic status or age of mother) with birth status
(such as birth weight and Apgar scores) and educa-
tional outcomes (such as standards test performance
or high school completion) for the entire provincial
population allows one to investigate issues that are
difficult to study. Some examples of the work per-
formed are presented in this report.
7
Is the Class Half Empty? by Marni Brownell, Noralou Roos, Randy Fransoo et al.
results by area of residence also serves to avoid the
mistake of blaming specific schools for poor results
and leads to a broader understanding of the factors
that influence school success. While schools do have
an impact on the outcomes of their students (see
Raudenbush and Willms [1995] for a discussion of
school effects on student outcomes), a population
focus acknowledges and highlights the broader social
and economic factors that lie outside the control of
school personnel. Box 1 outlines some of the charac-
teristics of population-based administrative data that
are particularly relevant for education research.
Confidentiality of data in the MCHP repository is
ensured through a number of procedures and security
measures. No names or addresses are ever contained
in the repository, and any individual or family identi-
fiers (for example, PHINs) are scrambled by the data
provider prior to data transfer to MCHP. Furthermore,
only projects approved by the university research
ethics board, by the Manitoba Health Information
Privacy Committee and by each data provider have
access to the repository. Any material prepared for
public presentation or dissemination must be submit-
ted to the Ministry of Health and the data provider
(for example, the Ministry of Education) to ensure
that the anonymity of individuals has been preserved.
MCHP has benefited from years of experience with
developing and upholding the highest standards of
privacy and confidentiality, building good working
relationships with provincial ministries and securely
handling administrative data sets. Despite this experi-
ence, and despite MCHP’s well-established security
adults, employment rates, rates of lone-parent house-
holds and immigration status. While each of these
characteristics could be used individually, at MCHP
we have developed a socioeconomic index that com-
bines several of these components in order to describe
areas and neighbourhoods in Manitoba (this is
described more fully below).
Putting the pieces together in order to provide
population-based information requires the creation
of meaningful geographic units. These units should
make implicit sense to residents of the province and
may follow established neighbourhood or school dis-
trict boundaries. Depending on the analysis, smaller
areas can be rolled up into larger regions or larger
areas broken down into smaller districts.
The population-based approach to looking at edu-
cational outcomes requires a focus that is different
from the one generally used when reporting educa-
tional statistics. Whereas most data are reported on
the basis of school attended, in a population-based
approach the outcomes are examined according to the
student’s area of residence (providing an easy link to
socioeconomic characteristics). A focus on the area of
residence allows for a more inclusive denominator for
analysis: achievement test results are not reported
based on the number of students writing the test;
rather, all individuals born in the province in a given
year are tracked as they move through or drop out of
the educational system, or as they are retained one
grade or more. The denominator becomes all individu-
als born in the selected year(s), according to their area
of residence at the time of testing. Reporting test
Box 1
Characteristics and Research Relevance of Manitoba Centre for Health Policy Databases
Characteristics Research relevance
Very large numbers Many physical and statistical controls feasible
Population-based for an entire province Heterogeneity on many variables
Longitudinal data (going back over 30 years) Many types of longitudinal studies, compilation of cohorts,
more reliable measurement of important variables
Specification of place of residence (according to Key to neighbourhood and longitudinal studies,
postal code) at any time point permits analysis of small area variation
Mobility/migration and other loss to follow-up Follow-up data critical for cohort studies, mobility data
well specified allow the capture of “length of exposure”
Family and sibling information (ties in with Data allow powerful non-experimental designs estimating
neighbourhood information) importance of different factors and controlling for
unobserved and unmeasured background characteristics
IRPP Choices, Vol. 12, no. 5, October 2006
8
payoffs are tremendous. The large number of observa-
tions available for population-based analyses
facilitates tracking outcomes in both small and large
jurisdictions. With population data routinely collected
every year on all members of the population, analyses
can be replicated over multiple years for groups or
jurisdictions of interest.
Box 2 outlines the types of indicators that can be
identified using administrative data in the Manitoba data
repository. Although some important indicators such as
parental education are typically not available from
administrative data, almost all of the variables noted in
the major studies of human development can be
record of handling administrative health data, the
road to obtaining the new databases, including those
of the Ministry of Education, required a complex
series of discussions and agreements, over the course
of which we worked with several ministers and
deputy ministers. This process included not only
arriving at agreements in principle, but also specify-
ing and negotiating what data needed to be trans-
ferred and how the transfers would take place.
Strengths of population-based data
While a great deal of time and effort is needed to
establish a population-based information system, the
Box 2
Indicators That Can Be Derived from Manitoba’s Population-Based Research Repository
Level 1: Student
• Age and sex of student
• Birth weight and Apgar score for child one minute and five minutes after birth
• Birth order of the child
• Spacing of the next birth in the family
• Age of student’s mother at first birth
• Enrolment in special education classes
• Whether child enrolled in Reading Recovery program
• Performance on standards tests (grades 3, 6 and 12)
• Grades in all courses starting grade 9; hence relative performance and type of program (university entrance and
so on) or number of years of physical education can be studied
• Enrolment in school K-12 by year; hence retention can be derived
• Number/types of schools attended
• Number of years to graduation or withdrawal
• Health characteristics of child (chronic disease, major disability and so on)
Level 2: Family
• Family structure over the life course (single parent, birth parents, stepfamilies)
• Sibling controls for family characteristics
• Mental health characteristics of family members
• Family receipt of income assistance
Level 3: Neighbourhood
• Socioeconomic characteristics of neighbourhoods of residence over the life course, including patterns of
upward/downward mobility, number of years in disadvantaged neighbourhoods
• Resources available in the community (libraries, parks, recreation programs, daycare and so on)
Level 4: School
• Size of school
• Student turnover rates (percentage of students enrolled two consecutive years)
• School retention rates (percentage of students retained one grade or more)
• Socioeconomic characteristics of students (percentage from highest-income neighbourhoods, percentage from
lowest-income neighbourhoods)
• Type of school (elementary only; elementary and middle grades; elementary, middle and senior grades)
• University entrance focus of school: percentage of students enrolled in university entrance courses
9
Is the Class Half Empty? by Marni Brownell, Noralou Roos, Randy Fransoo et al.
consistently report this indicator, we also counted the
number of course credits per student to determine
high school completion. Manitoba students must accu-
mulate 28 course credits in their senior years (grades 9
through 12) in order to graduate. We classified as
“graduated” those students who had either an indica-
tor for graduation or 28 course credits.
Data for grade 3 provincial exams in language
arts and mathematics are available for the 1997-98
and 1998-99 school years. We examined the results
for 1998-99. Provincial grade 3 testing was discon-
tinued after that year.
Socioeconomic index
A variety of socioeconomic characteristics can be
used to describe neighbourhoods — for example,
unemployment rates or high school completion rates.
At MCHP, we have developed an index that combines
those socioeconomic characteristics that are most
strongly related to health outcomes into a single
score (for a detailed description, see Martens et al.
[2002]). These characteristics include unemployment,
high school completion, lone-parent households and
female participation in the workforce. We calculated
this index for 1,146 small areas (census dissemination
areas) within Winnipeg and 1,172 areas outside of
Winnipeg, using publicly available data from the
2001 Census.2A socioeconomic index score for each
of 25 Winnipeg neighbourhoods was generated using
a weighted average of the scores for each dissemina-
tion area in the neighbourhood. The scores for these
25 neighbourhoods were then divided into four
groups based on how they differed from the average
score for all 25 neighbourhoods: low socioeconomic
status (SES), or most disadvantaged, low-middle SES,
middle SES and high SES. A similar process was fol-
lowed for each of 46 districts outside of Winnipeg.
Maps showing how the 25 Winnipeg neighbourhoods
and the 46 other districts were aggregated into the
four socioeconomic categories are shown in figures 1
and 2. Note that the number of children and the total
number of people in these groups are not equal; the
middle SES categories for both Winnipeg and non-
Winnipeg areas comprise over half of the total child
population in these areas.
Compared to the other areas, low-SES areas have
more unemployment, more lone-parent families,
fewer adults with high school education and fewer
women in the workforce. The groups also differ on
other important dimensions; for example, the aver-
age selling price of houses in Winnipeg in 1999
accurately measured using the Manitoba database.
Designs based on sibling controls are especially power-
ful and are useful in dealing with unmeasured variables
and measurement error (Solon, Page and Duncan 2000).
Using Population-Based Data to
Describe Socioeconomic
Inequalities in Educational
Outcomes: The Manitoba Example
The new social databases in the MCHP reposito-
ry are a unique resource for examining educa-
tional outcomes for all Manitoba children at
specific points in time. Combining data on all stu-
dents enrolled in Manitoba schools, high school
course marks and provincial standards tests scores
for grade 12 and grade 3 students with population
data on area residents provides a much more com-
plete perspective on educational performance than
would be possible otherwise.
Data used
For grade 12 students, Manitoba has had a provincial
testing system in place since 1993. The current stan-
dards tests are curriculum-based and mandatory,
with adaptations available for many special needs
students (and exemptions for individual students as
required). The annual standards tests are “locally
marked” by the school divisions and assess mathe-
matics and language arts in separate tests.1These
tests contribute 30 percent to students’ final course
marks. Students pass the language arts test by scor-
ing 50 percent or more on any of the following
examinations: English, French as a secondary lan-
guage (for students in the French immersion pro-
gram) and French as a primary language. Individuals
pass the mathematics test by scoring 50 percent or
better on the precalculus exam, the consumer math
exam or the applied math exam. Because the type of
math exam taken is also related to socioeconomic
status (24 percent of grade 12 students in the high-
est-income neighbourhoods take the precalculus
exam, compared to only 7 percent of those in the
lowest-income neighbourhoods), the measure “per-
centage passing the math test” will underestimate
socioeconomic differences in achievement.
The student enrolment data file provides a “gradua-
tion” indicator for students who complete grade 12.
Because not all schools or school districts in Manitoba
IRPP Choices, Vol. 12, no. 5, October 2006
10
ranged from $38,400 in low SES-areas to $132,218 in
high-SES areas. The figures show that the more disad-
vantaged areas (those most heavily shaded on the
maps) tend to be found in central Winnipeg and in the
northern parts of the province, and the most advan-
taged areas (those slightly less shaded on the maps) on
the outskirts of Winnipeg and in the southern parts of
the province.
Population studied
The educational outcomes presented here are based on
where children live, as opposed to where they go to
school. Most children (85 percent) attend schools close
to the area in which they live. For the outcomes of
grade 12 standards tests, we examined two different
populations. The first population included those youths
who were in grade 12 in the 2001-02 school year and
writing the standards test (total number = 11,750). This
population would include youths not born in Manitoba
but living in Manitoba and in grade 12 in the 2001-02
school year, as well as youths born prior to 1984 but
held back at least one grade and in grade 12 in 2001-
02. This is the group typically included in provincial
testing comparisons and surveys. The second population
included youths born in 1984, and still residing in the
province, who would have been writing the grade 12
standards tests in 2001-02 had they progressed through
the school system as expected (total number = 12,874).3
These two populations contain some of the same youths,
with close to 7,500 overlapping the two populations.
For analyses of high school completion, we selected
a cohort of students in grade 9 in 1997-98 (most were
14 or 15 years of age) and followed them for five
years to determine whether they completed high school
(total number = 15,572). Selecting students in grade 9
allowed us to include those who were not born in
Manitoba but who moved into the province prior to
grade 9.
In analyzing the outcomes of grade 3 standards
tests, we followed a strategy similar to that used for
the grade 12 tests, examining the results using two
different but overlapping populations of children. The
first included only those children writing the grade 3
tests in 1998-99 (
N
= 12,574), whereas the second
included all children born in 1990, who would have
been writing the grade 3 tests in 1998-99 had they
progressed through the school system as expected (
N
=
13,282). The overlap between these two populations
was close to 10,200. The year chosen was based on
availability of the grade 3 test results; the grade 3
examinations were discontinued after 1998-99.
High (most advantaged)
Pop. = 48,789
Child pop.: 13,087
Socioeconomic status
Middle
Pop. = 354,712
Child pop.: 90,272
Low-middle
Pop. = 140,469
Child pop.: 32,803
Low (most disadvantaged)
Pop. = 104,989
Child pop.: 28,202
Figure 1
Socioeconomic Status by Neighbourhood,
Winnipeg, 20011
Source: Calculations by the authors based on Statistics Canada, Census of
Canada, 2001.
1Assessed by unemployment rate, number of lone-parent families, high school
education rate, female workforce participation rate.
High (most advantaged)
Pop. = 95,901
Child pop.: 30,556
Socioeconomic status
Middle
Pop. = 294,736
Child pop.: 83,923
Low-middle
Pop. = 66,673
Child pop.: 21,085
Low (most disadvantaged)
Pop. = 42,700
Child pop.: 19,614
Figure 2
Socioeconomic Status by Region, Manitoba, 20011
Source: Calculations by the authors based on Statistics Canada, Census of
Canada, 2001.
1Assessed by unemployment rate, number of lone-parent families, high school
education rate, female workforce participation rate.
11
Is the Class Half Empty? by Marni Brownell, Noralou Roos, Randy Fransoo et al.
in Winnipeg in 2001-02, we determined where they
were in the school system at that time (that is, dur-
ing what should have been their final year in school)
and also identified those who had withdrawn from
school. Figure 3B shows this very different reality:
only 27 percent of the youths living in the low-SES
areas who should have been writing the standards
test that year actually wrote and passed the test. The
pass rate was over two-and-a-half times higher for
students in the high-SES group (77 percent). A very
large proportion of the students from the low SES
areas (36 percent) were at least one year behind (in
grade 11 or lower); almost 20 percent had withdrawn
from school (not enrolled for at least two years). In
other words, for all four socioeconomic groups, if
students were in grade 12 and wrote the test, the
great majority passed. But many of the youths from
low-SES areas had not yet made it to grade 12 and
almost one in five were not in school at all.5Figure 4
shows these same results for the non-Winnipeg
areas; the patterns are similar to those for Winnipeg
residents, although the passing rate is lower overall
and the gaps between youths from the lowest and
the highest socioeconomic areas are even wider than
those for Winnipeg youths.6
Figures 3 and 4 suggest that most youths from the
1984 birth cohort were still in school in 2001-02. But
Students in both the public and private school
systems were included in all analyses.
Educational Outcomes in
Manitoba
So how much do educational outcomes differ
across socioeconomic levels? Figure 3 shows
performance on the grade 12 language arts
standards tests by Winnipeg socioeconomic area.
Figure 3A reflects what the schools see when they
review the performance of students taking the tests:
92 percent of students living in the high-SES areas
passed, along with 75 percent of those living in low-
SES areas. As illustrated, there are systematic differ-
ences across the groups, though these differences
seem modest.
These numbers do not tell the whole story, how-
ever; they just report results for those who are in
school, in grade 12 and writing the standards tests.
The larger question is: What happens when we focus
on who
should
have been writing the standards test
at that time? This very different story is told in
figure 3B. To develop this graph we used the cohort
of children born in Manitoba in 1984 and remaining
in Manitoba until 2001-02.4Then, for those residing
Box 3
Demographic Profile of Manitoba
According to a 2006 study from Statistics Canada, with a population of 1.17 million, Manitoba is the fifth-largest
of Canada’s provinces and territories. Over half the population lives in the capital city of Winnipeg (population
706,900), ranking Winnipeg the ninth-largest city in Canada. Children under 15 years of age make up 19.7 percent
of Manitoba’s population, which is similar to the figures for Saskatchewan and Alberta and a little higher than the
national average of 17.6 percent. Furthermore, Manitoba has a large Aboriginal population (12.7 percent), with only
Saskatchewan (13.1 percent) and the territories (Yukon 21.1 percent, Northwest Territories 43.6 percent, Nunavut
75.7 percent) reporting higher percentages; the overall Canadian percentage is 3.0.
The percentage of Aboriginal people also differs according to age group: 23.3 percent of those 0 to 14 years,
11.5 percent of those 15 to 64, and 3.5 percent of those 65 and over are of Aboriginal descent (compared to
Canadian averages of 5.7, 2.7 and .9 percent, respectively). In other words, Manitoba has higher proportions of
Aboriginal people than the overall averages for Canada; this difference in numbers decreases progressively with
increased age.
Within Winnipeg, only 7.9 percent of the population is composed of Aboriginal people, which indicates higher pro-
portions of Aboriginal people living in rural Manitoba. This value is similar to percentages for Regina (7.9) and Saskatoon
(8.6) and is similar in trend to other Canadian cities (that is, lower percentages of Aboriginal people in urban areas).
In terms of immigrant population, the percentage for Manitoba (11.4) is lower than that for the country as a
whole (16.9). The majority of Manitoban immigrants are from Europe (47.5 percent) and Asia (30.3 percent), which
is the trend for immigration throughout Canada.
IRPP Choices, Vol. 12, no. 5, October 2006
12
neighbourhoods were “near graduation,” meaning that
they had made it to grade 12 but had not yet graduat-
ed at the end of five years.7One in four students had
withdrawn even before completing high school. An
additional 20 percent were still in school after five
years but had not yet made it to grade 12 (shown as
“continuing” in the graph). The picture differed consid-
erably for students living in other neighbourhoods. In
what proportion of children in each socioeconomic
group will graduate? To answer this question, we
tracked all students in grade 9 in the 1997-98 school
year for five years (
N
= 15,572). Figure 5 shows what
we found. For Winnipeg residents (figure 5A), only
37 percent of students from the low-SES neighbour-
hoods graduated by the end of five years. An
additional 17 percent of students from low-SES
Low
(n = 187)
Low-middle
(n = 561)
Socioeconomic status
Middle
(n = 3,349)
High
(n = 1,231)
Percent
A) Pass/fail rates of test-writers
0
10
20
30
40
50
60
70
80
90
100
57
78
87 87
Low
(n = 544)
Low-middle
(n = 776)
Socioeconomic status
Middle
(n = 3,845)
High
(n = 1,300)
Percent
B) Outcomes for all 18-year-olds who should have written
0
10
20
30
40
50
60
70
80
90
100
14
38
55 62
Passed Failed Dropped course, absent,
exempt, incomplete
In grade 12,
but no test mark
In grade 11
or lower
Withdrew
Figure 4
Grade 12 Performance on Language Arts Test by Socioeconomic Status, Non-Winnipeg, 2001-02
Source: Calculations by the authors based on language arts standards tests results, student enrolment and population registry information from the Manitoba Population
Health Research Data Repository.
Low
(n = 680)
Low-middle
(n = 1,148)
Socioeconomic status
Middle
(n = 3,934)
High
(n = 660)
Percent
A) Pass/fail rates of test-writers
0
10
20
30
40
50
60
70
80
90
100
75
83 87 92
Low
(n = 977)
Low-middle
(n = 1,212)
Socioeconomic status
Middle
(n = 3,605)
High
(n = 615)
Percent
Passed Failed Dropped course, absent,
exempt, incomplete
In grade 12,
but no test mark
In grade 11
or lower
Withdrew
B) Outcomes for all 18-year-olds who should have written
0
10
20
30
40
50
60
70
80
90
100
27
52
65
77
Figure 3
Grade 12 Performance on Language Arts Test by Socioeconomic Status, Winnipeg, 2001-02
Source: Calculations by the authors based on language arts standards tests results, student enrolment and population registry information from the Manitoba Population
Health Research Data Repository.
13
Is the Class Half Empty? by Marni Brownell, Noralou Roos, Randy Fransoo et al.
Although it is tempting to conclude from these
figures that poor educational outcomes are more fre-
quent for those students who live in socio-
economically poor areas, the numbers at the top of
each bar in figure 5 tell another story. While the
withdrawal
rate
is highest among those in low-SES
areas, the actual
number
of children living in each
area must be considered. The number of youths in
the middle-SES groups is much larger than the num-
ber in the other groups — over half of the children in
Winnipeg and non-Winnipeg areas live in middle-
SES areas. Even though the percentage of middle-
SES youths withdrawing from school is about one-
third that of low-SES youths, the
numbers
of with-
drawals in these two areas are very similar in
Winnipeg: 309 students from low-SES areas had
withdrawn from school, but so had 358 students liv-
ing in middle-SES neighbourhoods. In non-Winnipeg
areas, the number of youths in middle-SES areas
withdrawing from school is substantially higher than
the number in low-SES areas (601, compared to 170).
At this point we cannot track Manitoba students who
return to school as adult learners; however, youths
from higher-income backgrounds appear to be better
situated to take advantage of remedial opportunities
(Ceci and Papierno 2005).
Outcomes at earlier ages
Both the grade 12 language arts examination results
and the high school completion results demonstrate a
strong socioeconomic gradient in educational out-
comes: students who live in socioeconomically poor
neighbourhoods are less likely to pass the grade 12
standards tests, are less likely to graduate from high
school within five years of entering, are more likely
to fail a grade at some point and are more likely to
withdraw from school before completing high school.
When do children from lower socioeconomic areas
start falling behind?
To try to answer this question, we looked at grade
3 standards tests. Figure 6 shows these results for
Winnipeg children. By grade 3, children from low-
SES neighbourhoods were already much less likely to
be performing well — that is, passing the grade 3
standards test at an age-appropriate time. Looking
only at the performance of those who wrote the test
(figure 6A), the differences across socioeconomic
areas do not seem very large — they range from 83
percent passing in the low-SES areas to 94 percent
passing in the high-SES areas. Once again, this does
not tell the whole story. To see the complete picture,
the high-SES areas, 81 percent had completed high
school within five years and only 3 percent had
withdrawn. For non-Winnipeg residents (figure 5B),
only 15 percent of students from the low-SES areas
graduated by the end of five years and more than a
third had withdrawn before completing high school;
an additional 25 percent were still in school after
five years but had not yet reached grade 12. As was
found for Winnipeg, the picture was very different
for students living in other areas; in the high-SES
areas, 71 percent had completed high school within
five years and less than 11 percent had withdrawn.8
Low
(n = 1,216)
Low-middle
(n = 1,543)
Socioeconomic status
Middle
(n = 4,713)
High
(n = 671)
Percent
Graduated Near graduation Continuing Withdrew
A) Winnipeg
0
10
20
30
40
50
60
70
80
90
100
37
n = 309
60
n = 182
74
n = 358
81
n = 22
Low
(n = 446)
Low-middle
(n = 979)
Socioeconomic status
Middle
(n = 4,526)
High
(n = 1,478)
Percent
B) Non-Winnipeg
0
10
20
30
40
50
60
70
80
90
100
16
n = 170
44
n = 235
62
n = 601
71
n = 161
Graduated Near graduation Continuing Withdrew
Figure 5
High School Completion Rates, by Socioeconomic
Status, Winnipeg and Non-Winnipeg, 2002-031
Source: Calculations by the authors based on student enrolment and population
registry information from the Manitoba Population Health Research Data
Repository.
1We tracked 15,572 grade 9 students for five years.
IRPP Choices, Vol. 12, no. 5, October 2006
14
hoods were enrolled in grade 2 or lower and, com-
pared to other neighbourhoods, more children from the
low-SES neighbourhoods failed the test, did not com-
plete it, were exempt from it or were absent on the day
(or days) when it was written.
Figure 7 shows the grade 3 results for children resid-
ing outside of Winnipeg. For these children, observing
just the performance of those who wrote the test shows
a slightly steeper gradient across socioeconomic levels
we identified all children born in Manitoba in 1990
and living in Winnipeg in the 1998-99 school year
who
should
have been writing the grade 3 standards
test that year. As can be seen in figure 6B, only 50
percent of those living in low-SES neighbourhoods
passed the test on schedule, compared to 84 percent
of those living in Winnipeg’s high-SES neighbour-
hoods (a difference of 68 percent). Additionally, 15
percent of students living in low-SES neighbour-
Low
(n = 891)
Low-middle
(n = 1,323)
Socioeconomic status
Middle
(n = 3,997)
High
(n = 607)
Percent
A) Pass/fail rates of test-writers
0
10
20
30
40
50
60
70
80
90
100
83 91 93 94
Low
(n = 1,105)
Low-middle
(n = 1,354)
Socioeconomic status
Middle
(n = 4,001)
High
(n = 598)
Percent
Passed Failed Absent Exempt Incomplete Grade 2 or lower
B) Outcomes for all 8-year-olds who should have written
0
10
20
30
40
50
60
70
80
90
100
50
70
78 84
Figure 6
Grade 3 Performance on Language Arts Test by Socioeconomic Status, Winnipeg, 1998-99
Source: Calculations by the authors based on language arts standards tests results, student enrolment and population registry information from the Manitoba Population
Health Research Data Repository.
Low
(n = 238)
Low-middle
(n = 749)
Socioeconomic status
Middle
(n = 3,525)
High
(n = 1,244)
Percent
A) Pass/fail rates of test-writers
0
10
20
30
40
50
60
70
80
90
100
63
82 90 91
Passed Failed Absent Exempt Incomplete Grade 2 or lower
Low
(n = 374)
Low-middle
(n = 841)
Socioeconomic status
Middle
(n = 3,661)
High
(n = 1,348)
Percent
B) Outcomes for all 8-year-olds who should have written
0
10
20
30
40
50
60
70
80
90
100
33
58
70 69
Figure 7
Grade 3 Performance on Language Arts Test by Socioeconomic Status, Non-Winnipeg, 1998-99
Source: Calculations by the authors based on language arts standards tests results, student enrolment and population registry information from the Manitoba Population
Health Research Data Repository.
15
Is the Class Half Empty? by Marni Brownell, Noralou Roos, Randy Fransoo et al.
four groups: 81 percent of the children in the low-
SES group had been normal weight at birth, com-
pared to 82 percent for the high-SES group. The four
groups vary only slightly in the rates of low and
high birth weight.
Figure 8 also presents the percentage of children
with “good” five-minute Apgar scores across socio-
economic groups (figure 8B). As with birth weight,
there is little difference in Apgar scores: 85 percent of
children from low-SES areas have good scores, com-
pared to 84 percent of those from high-SES areas. This
lack of difference across groups in both healthy birth
weight and healthy Apgar score is even more notewor-
thy when one considers the differences in life
expectancy for these children. For example, males born
than for Winnipeg children: the percentage passing
the test goes from 63 in the low-SES areas to 91 in
the high-SES areas (figure 7A). The gradient across
socioeconomic areas becomes even steeper when the
complete picture is examined (figure 7B): only 33 per-
cent of those living in low-SES areas passed the test
on schedule, compared to 69 percent of those in the
high-SES areas. Thirty percent of students living in
low-SES areas were enrolled in grade 2 or lower, and
almost 18 percent failed the test.
Even in the primary school years, there are big dif-
ferences in educational outcomes across socioeconomic
groups. Indeed, evidence from Vancouver shows sub-
stantial socioeconomic gradients at school entry, with
children from neighbourhoods with lower socio-
economic status entering kindergarten less prepared for
learning than children from neighbourhoods with
higher socioeconomic status (Hertzman et al. 2002).
Are these differences in children apparent at
birth? One hears a lot about the problems of poor
nutrition, smoking and inadequate prenatal care fac-
ing pregnant women in disadvantaged neighbour-
hoods. These factors put the women at risk of having
babies with birth weights that are too low or too
high or at increased risk for other problems at birth
(Perinatal Education Program of Eastern Ontario
1998). Babies with low birth weight (under 2,500
grams) are at risk for a number of developmental,
cognitive and health problems, and those with high
birth weight (over 4,000 grams) are at risk for both
birth complications and health problems (Perinatal
Education Program of Eastern Ontario 1998;
Saskatchewan Health 2000). Babies born with low or
borderline Apgar scores may also be at increased risk
for health and developmental problems.9We looked
at both the birth weights and the Apgar scores of our
1984 cohort (the children we focused on for the
grade 12 language arts standards tests), our 1990
cohort (the children we focused on for the grade 3
language arts standards tests) and a more recent
birth cohort (2003), to see if differences in children
from different socioeconomic groups10 were apparent
at birth. Results were similar for all cohorts, so we
report on the children born in 1984.
Figure 8 shows the percentage of children with
normal birth weight (that is, neither low nor high)
across the four socioeconomic groups for our 1984
birth cohort (Winnipeg and non-Winnipeg residents
have been combined and the bars are shaded to cor-
respond with the four groups shown in figures 1 and
2). There are remarkably few differences across the
Low Low-middle
Socioeconomic status
Middle High
Percent
A) Children with normal birth weight
0
10
20
30
40
50
60
70
80
90
100
8181 83 82
Low Low-middle
Socioeconomic status
Middle High
Percent
B) Children with good Apgar scores
0
10
20
30
40
50
60
70
80
90
100
87
85 85 84
Figure 8
Health of Children at Birth, by Socioeconomic
Status, Manitoba, 1984 Cohort
Source: Calculations by the authors based on birth hospitalization and population
registry information from the Manitoba Population Health Research Data
Repository.
IRPP Choices, Vol. 12, no. 5, October 2006
16
analyses separately for Aboriginal youths, because using
the MCHP repository to identify Aboriginal people miss-
es a significant portion of Aboriginal youths, particularly
nonregistered First Nations and Métis youths. An analy-
sis that was able to exclude an estimated half of the
Aboriginal youth population from Winnipeg found
strong gradients across socioeconomic levels for grade
12 test results similar to those reported here (Roos et al.
forthcoming). The educational performance of Aboriginal
youths, and the socioeconomic circumstances that
impede their performance, are areas that warrant further
research attention.
Sex differences in school performance
Differences between males and females in school per-
formance have been highlighted recently both in the
literature and in the mainstream press. The population-
based approach can also be used to examine these sex
differences in educational outcomes. Let us consider the
grade 12 standards tests. Females writing the language
arts standards test tended to have a slightly higher pass
rate than males — 89.8 percent, compared to 82.4 per-
cent for males. When we took a population-based
approach and included all students from the 1984
cohort who should have been writing the test, the gap
between males and females widened, with 61.6 percent
of the females passing the test on time, compared to
only 47.6 percent of the males. Males were more likely
than females to fail the test, to be in grade 12 but not
write the test, to be behind by a year or more, or to
withdraw from school. The sex differences in perform-
ance on the language arts standards test are illustrated
in figure 9, which shows the ratio of female to male
in Winnipeg’s high-SES neighbourhoods are expected
to live three years longer than males born in the low-
middle-SES neighbourhoods (life expectancy of 79.2
and 75.9 years, respectively). And males born in low-
SES neighbourhoods have an even lower life expectan-
cy — only 69.5 years, despite the fact that children
from all of these neighbourhoods appear similarly
robust at birth.11 Are these differences large or small?
Actually, they are enormous. Three years is the differ-
ence in life expectancy to be gained if we eliminated
all types of cancer (Manton 1991). We clearly need to
do more to reclaim the three years of life lost for males
in lower-middle-class areas and the almost ten years of
life lost for males born in low-SES neighbourhoods.
First Nations and Métis youths
As indicated in the demographic profile in box 3, close
to 20 percent of children and youths in Manitoba are
Aboriginal people, with higher percentages in rural
areas and lower percentages in Winnipeg. Aboriginal
youths are more likely to live in low socioeconomic
areas and have poorer educational outcomes than non-
Aboriginal youths (Canadian Education Statistics
Council 2003; Heisz and McLeod 2004; Indian Affairs
and Northern Development 2000; Lee 2000; Peters
2005). Given that among Canadian cities Winnipeg has
the highest concentration of Aboriginal people living
in poor neighbourhoods (Richards 2001), at least part
of the weak performance observed in the most socio-
economically deprived Winnipeg and non-Winnipeg
areas may be attributable to the high percentage of
Aboriginal children in these areas and the impover-
ished living conditions of this group. We have not run
Low Low-middle
Socioeconomic status
Middle High
Ratio
A) Test-writers
1.0
1.2
1.4
1.6
1.8
1.07 1.08 1.10 1.09
Low Low-middle
Socioeconomic status
Middle High
Ratio
B) Total 1984 cohort
1.0
1.2
1.4
1.6
1.8
1.66
1.38
1.27 1.26
Figure 9
Ratio of Female to Male Pass Rates on Grade 12 Language Arts Test, Manitoba, 2001-021
Source: Calculations by the authors based on language arts standards tests results, student enrolment and population registry information from the Manitoba Population
Health Research Data Repository.
1A ratio of 1.2 would indicate that female pass rates were 20 percent higher than male pass rates.
17
Is the Class Half Empty? by Marni Brownell, Noralou Roos, Randy Fransoo et al.
percent; this difference was far greater in the socio-
economically deprived areas (where the female pass
rate was 82 percent higher than the male).
We also found sex differences in the rates of high
school completion within five years of grade 9 (fig-
ure 11). Girls were almost 18 percent more likely
than boys to complete high school within the five
years, and the withdrawal rate was 32 percent lower
for girls. Interestingly, completion rates for females
and males living in the high-, middle- and low-
middle-SES neighbourhoods differed only minimally,
performance for test-takers only (figure 9A) and for
the entire cohort (figure 9B). This figure shows that if
we look only at test-takers, the differences between
female and male performance are less than 10 percent
for each of the four socioeconomic groups. When we
take a population-based approach, however (figure
9B), the differences between female and male out-
comes widen, with the greatest sex differences in
those living in the most socioeconomically deprived
areas (with female pass rates over 60 percent higher
than male) and the smallest differences in those liv-
ing in the most socioeconomically advantaged areas
(females still outperforming males, with a pass rate
26 percent higher than that of males).
The literature examining sex differences in school
performance generally shows that girls tend to perform
better in subjects related to language arts, but that per-
formance differences between the sexes in mathematics
and science, which initially favoured males, have dis-
appeared in recent years (Lauzon 2001). We examined
the mathematics standards tests to determine whether
taking a population-based view would confirm these
findings (figure 10). When looking only at test-takers,
we did indeed find minimal differences in pass rates
between females and males — a less than 2 percent dif-
ference overall, ranging from a 7 percent advantage
for females over males in socioeconomically poor areas
to a 1 percent advantage for males over females in
more affluent areas (figure 10A). The population-based
approach (figure 10B) revealed much greater sex differ-
ences, with females outperforming males by about 25
Low
1.54
Low-middle
1.05
Socioeconomic status
Middle
1.12
High
1.03
Ratio
1.0
1.2
1.4
1.6
1.8
Figure 11
Ratio of Female to Male High School Completion
Rates, Manitoba, 2001-021, 2
Source: Calculations by the authors based on student enrolment and population
registry information from the Manitoba Population Health Research Data
Repository.
1A ratio of 1.2 would indicate that female completion rates were 20 percent
higher than male completion rates.
2We tracked 15,572 grade 9 students for five years.
Low Low-middle
Socioeconomic status
Middle High
1.07
1.03 1.02 0.97
Ratio
A) Test-writers
0.8
1.0
1.2
1.4
1.6
1.8
Low
1.82
Low-middle
1.26
Socioeconomic status
Middle
1.23
High
1.17
Ratio
B) Total 1984 cohort
0.8
1.0
1.2
1.4
1.6
1.8
Figure 10
Ratio of Female to Male Pass Rates on Grade 12 Math Test, Manitoba, 2001-021
Source: Calculations by the authors based on maths standards tests results, student enrolment and population registry information from the Manitoba Population Health
Research Data Repository.
1A ratio of 1.2 would indicate that female pass rates were 20 percent higher than male pass rates; a ratio of 0.8 would indicate that female pass rates were 20 percent
lower than male pass rates.
IRPP Choices, Vol. 12, no. 5, October 2006
18
teacher to work one-on-one or with small groups of
children for several hours each week. A pretest enables
teachers to select the neediest children for the program.
Figure 12 shows the percentage of grade 1 children in
the Reading Recovery program by the four socio-
economic areas in Winnipeg. As can be seen, children
from the low-SES group have the lowest overall partici-
pation rate, even though one would expect those chil-
dren to have the greatest need for the program. There are
other early intervention literacy programs besides
Reading Recovery, used in Winnipeg schools and
throughout the province, the implementation of which
might at least partially explain the low percentages seen
for low-SES groups in figure 12.14 We have presented
these findings to numerous groups of educators in
Manitoba, from teachers, to school district administra-
tors, to policy-makers. In our discussions with educators
from these low-SES areas, they reported that so many of
their grade 1 students needed remedial reading instruc-
tion that they could not afford to provide the resource-
intensive Reading Recovery program to all of them (the
funding formula assumes that around 20 percent of all
children will need early literacy programming). The
high-need schools therefore use their early literacy funds
for programs that are less intensive but reach more chil-
dren. Thus, the most extensive use of the Reading
Recovery program is in schools in high-SES areas, where
almost 13 percent of grade 1 children receive it, com-
pared to only 4 percent of children in the low-SES areas.
(These percentages vary widely by school. In 2000-01
whereas completion rates were over 50 percent high-
er for females from the low-SES areas compared to
males from these areas.
The fit between resources and need
The preceding sections demonstrate that the educa-
tion system allows most students to pass the stan-
dards tests on schedule and to complete high school
within five years of grade 9. However, children in
the most disadvantaged areas of Manitoba are clearly
at higher risk of poor educational outcomes than
children in more advantaged areas.12 This raises the
question: Are we directing resources in such a way
as to help these children and their families overcome
the enormous challenges they face? Manitoba’s
expenditures per student in the 1990s tended to be
close to the average for Canadian provinces
(Statistics Canada 2001); educational funding per
child is relatively equal across areas (Manitoba
Education, Citizenship and Youth 2004; Task Force
on Educational Funding 2001), with some extra
funding going to schools having more students from
low-income families (Manitoba Education,
Citizenship and Youth 2006).13 Does this additional
funding translate into greater concentrations of
effort in areas with higher concentrations of children
with risk factors and poor educational outcomes?
In a sense, this is the way the health care system
works — showing a relatively good fit between
resources and need. When we look at children’s
health outcomes, we find — as with educational out-
comes — important differences across socioeconomic
groups: children in the most disadvantaged neigh-
bourhoods have poorer health status than those from
more advantaged neighbourhoods. However, the
Canadian universal health care system delivers more
care to those who need it most: people in socio-
economically deprived areas make more doctor visits
and are admitted to hospital more frequently than
those in more affluent areas, reflecting their greater
need for care (Roos, Brownell and Menec 2006).
Our population-based data allowed us to look at
the fit between needs and educational resources, to see
whether high-needs groups were receiving the
resources necessary to succeed in one specific area:
early literacy development. Several years ago, the
Manitoba government made a commitment to improv-
ing literacy and initiated an early literacy grant to
achieve this goal. One widely used program for early
literacy in Manitoba schools is called Reading
Recovery. It is an intensive program requiring a
Low
(n = 54)
Low-middle
(n = 163)
Socioeconomic status
Middle
(n = 472)
High
(n = 70)
Percent
0
2
4
6
8
10
12
14
9
4
10
13
Figure 12
Proportion of Grade 1 Students in Reading Recovery
Programs, by Socioeconomic Status, Winnipeg,
2000-01
Source: Calculations by the authors based on student enrolment, Reading
Recovery participation and population registry information from the Manitoba
Population Health Research Data Repository.
19
Is the Class Half Empty? by Marni Brownell, Noralou Roos, Randy Fransoo et al.
achievement captures outcomes for those students
who stay in school and keep up with their classmates.
While these performance data suggest that socio-
economic status matters, they greatly underestimate
the inequalities that exist in educational achievement.
The first part of this report reviewed Manitoba’s
development of a population-based approach in
order to provide a model for those jurisdictions with
the potential to implement such an approach in their
own area. Making use of routinely collected adminis-
trative data that can track an entire population’s
experience could be the key to providing a more
complete picture of the role of socioeconomic status
in educational achievement. Organizing educational
data by the characteristics of the community in
which students reside (or in which a school is lo-
cated), rather than by the school or school district,
focuses attention on the powerful role played by
socioeconomic status and the enormous challenges
facing schools that serve disadvantaged communi-
ties. The emphasis then moves from blaming teachers
and schools for poor performance to confronting the
challenge of improving educational opportunities.
Understanding the role of socioeconomic status is
particularly important as educational systems con-
sider a charter school approach or seek competitive
ways to improve educational performance. Private
schools that draw children from advantaged families
are no more responsible for these children’s subse-
quent stellar performances than schools in core areas
are responsible for their students’ poor performance.
Population-based data provide the information that
policy-makers require to assess, debate and challenge
decisions about programs and priorities. Schools and
policy-makers have typically focused on who is in the
classrooms. From society’s perspective, however, those
who are not in school (and who should be) are a miss-
ing piece of the educational achievement picture. The
ability of a population-based system to describe the
numbers and whereabouts of the students who with-
draw from school provides much-needed information
to policy-makers. When students do not return, the
schools do not know if they have moved away, are
attending another school or have dropped out.
Knowing who is not in school, who should be and the
whereabouts of those children should serve to bring
about programs designed to help individuals return to
complete their education.
Different groups have different information needs,
and these needs can be identified through a population-
based focus. Policy-makers and the public need
three-quarters of schools in the low-SES areas had no
children in Reading Recovery, whereas other schools in
these areas had almost half their grade 1 students in
the program.) While the other early literacy programs
may be as effective as Reading Recovery, the marked
differences in educational performance across grade 3
and grade 12 students make a compelling case for
needs-based investment in the early years.
Interestingly, outside of Winnipeg the Reading
Recovery program appears much more targeted to
those children who need it most. Figure 13 shows
that over a quarter of grade 1 children in the low-
SES areas received the program — twice as many as
in the high-SES areas. This is a step in the right
direction, although, as seen in figure 7, two-thirds of
grade 3 children in the low-SES non-Winnipeg areas
did not pass the grade 3 language arts standards
tests on time. These outcomes suggest that substan-
tially more young children in low-SES areas may
require this intensive early intervention program.
Policy Implications
Making better use of administrative data
The current practice, in many provinces, of using
standards tests to gather information on the
performance of the education system and to
identify areas or schools that show difficulties in
Low
(n = 105)
Low-middle
(n = 134)
Socioeconomic status
Middle
(n = 599)
High
(n = 200)
Percent
0
5
10
15
20
25
30
20
26
15 13
Figure 13
Proportion of Grade 1 Students in Reading
Recovery Programs, by Socioeconomic Status, Non-
Winnipeg, 2000-01
Source: Calculations by the authors based on student enrolment, Reading
Recovery participation and population registry information from the Manitoba
Population Health Research Data Repository.
IRPP Choices, Vol. 12, no. 5, October 2006
20
examine factors associated with successful progression
through the system and to identify those children who
are in need of additional resources. While not all
research questions can be answered using routinely
collected data, longitudinal data repositories can pro-
vide the information necessary to determine the repre-
sentativeness of sample surveys.
Optimizing social program design — universal,
with a needs-based focus
Our population-based analyses highlight the impor-
tance of policies that can change the trajectories of
disadvantaged children. Our results show the true
steepness of the gradient in educational outcomes. Key
social programs and their delivery must be rethought.
The education system is administered and funded
using a roughly flat per capita approach, with a mod-
est extra allocation based on need. Our results suggest
that this is not enough, that increased investments for
those with greater needs are necessary. More resources
are needed to keep children in poorer areas enrolled
and engaged in school.
But what is the optimal design for improving edu-
cational outcomes at the population level? Although
the rates of poor outcomes are much higher for chil-
dren and youths in socioeconomically deprived areas,
most of the students who are performing badly do not
live in those areas. This is the rationale for educational
programs that are universally available — programs
that are directed only at low-income areas would not
substantially reduce the total number of poor out-
comes. Universal programs are also more likely to win
the support of the middle class and businesses that
employ parents of young children (Skocpol 1991).
However, a universal approach does not necessarily
mean equal funding per child: targeting within a uni-
versal approach should ensure that children with the
greatest needs receive whatever extra support is
required to help them improve their outcomes. This
needs-based universal approach, which is how our
health care system functions, addresses the needs of
the many students from the middle class who require
some help but allows for greater investment in those
who require the most help.
Concerted effort may be necessary to ensure that
universally available programs and services are
used
by those who need them the most. Typically, the
uptake of attractive universally available programs will
be skewed by the more sophisticated abilities of
higher-SES groups to take advantage of them. For
instance, Quebec’s widely admired “universally
macro-information — the overall picture that demon-
strates links between socioeconomic status and educa-
tional outcomes. Such information provides a rationale
for changing investment patterns in the education sec-
tor. School principals and district superintendents need
different information in order to identify areas of better
and poorer performance relative to what might be
expected of the school given the socioeconomic charac-
teristics of the area it serves. The off-diagonal perform-
ers (those schools/areas whose students are performing
much better or much worse than expected given their
socioeconomic characteristics) make great case studies.
However, broader initiatives, including early childhood
investments designed to raise overall levels of perform-
ance for high-needs children entering school, and tar-
geted investments focused on reducing the inequalities
in achievement, are likely to have greater payoffs.
A population-based approach to examining edu-
cational achievement can provide information about
the distribution of existing resources and the accessi-
bility of particular services (such as an early inter-
vention literacy program in the primary years or
advanced courses in the senior years). Juxtaposing
information on the educational resources that are
available, the socioeconomic needs of local popula-
tions and educational achievement levels can trans-
form simple reports on resource provision into a
meaningful portrait of who gets what; services
offered in one district can be compared to those
available elsewhere relative to a description of needs.
Manitoba policy-makers were not taken completely
by surprise by the population-based data on Reading
Recovery programs; however, they acknowledged
that they had never focused on resource distribution
relative to local needs. Population-based data make it
clear to policy-makers that simply making social
programs available will not ensure that needs are
met in all areas; such programs may sometimes
aggravate rather than reduce disparities in children’s
opportunities (Ceci and Papierno 2005).
Building a population-based repository like that in
Manitoba is not easy or without cost. However, given
that such repositories are developed from existing
data routinely collected for other purposes, using
those data for research purposes makes more eco-
nomic sense than raising the considerable sums
necessary to mount large-scale surveys with unpre-
dictable funding. Because all provinces already have
some educational testing in place, developing the
capability to track children’s progress should be
made a priority. This would allow researchers to
21
Is the Class Half Empty? by Marni Brownell, Noralou Roos, Randy Fransoo et al.
women with children under six years of age in the
paid workforce — from less than one-third in 1976 to
almost two-thirds in 2003 (Statistics Canada 2003).
In the United States, the push for universal preschool
is becoming more widely recognized (Oklahoma and
Georgia have been pioneers); this suggests a recogni-
tion of the potential contribution of universal pre-
school to long-term economic growth.
Over the last five to ten years, particularly since the
First Ministers agreed in 1997 to develop the National
Children’s Agenda, many early childhood development
programs have been put in place. In Manitoba these
have included income and program supports for low-
income pregnant women and home visiting programs
designed to enhance the parenting skills of those with
infants and young children (Healthy Child Manitoba
2006). As with other programs, early childhood pro-
grams need to be continuously monitored to ensure
their effectiveness and ongoing improvement. An
important tool for monitoring early childhood pro-
grams is the Early Development Instrument (EDI),
which was developed by the Offord Centre for Child
Studies and has been used in British Columbia
(Hertzman et al. 2002) and in other provinces to assess
key dimensions of child development at school entry.
Such assessments should be incorporated into popula-
tion-based information systems to facilitate research
on the impact of early child programs.
Quality child care
Given that research consistently supports the impor-
tance of quality child care, programs that develop the
skills of educators and child care personnel are also
necessary. Programs that instruct early childhood
educators in promoting literacy development, lang-
uage learning and positive peer interaction (see, for
example, Weitzman and Greenberg 2002) will be
essential to ensure positive outcomes. Such programs
have been shown to effectively increase talkativeness,
vocabulary diversity and peer interaction in children
(Girolametto, Weitzman and Greenberg 2006).
Parenting programs
The most important relationship in a child’s early life
is that between the child and his or her primary
caregivers. It is critical that parents be offered ade-
quate supports, including community programs
designed to enhance parenting skills. Community-
based parenting programs can lead to significant
improvements in parenting practices and decreased
behavioural problems in children (Bradley, Caldwell
available” $7-a-day child care system has not, par-
ticularly in its early years, translated into equality of
access. Because demand exceeds the supply of
spaces, families in middle and higher socioeconomic
categories are much more likely to prepare for their
child care needs (through early sign-up) and to enrol
their children in the higher-quality programs. Some
have argued that the program may be accentuating
rather than reducing the inequalities in preparation
for school that exist across socioeconomic groups
(Japel, Tremblay and Côté 2005; Lefebvre 2004). This
is not an inevitable consequence of universal pro-
grams, but special efforts are often needed to reach
those who may be in greatest need of the services
and thus to minimize socioeconomic disparities in
uptake (Gupta et al. 2003; Link et al. 1998).
Keeping in mind the universal needs-targeted
approach, the Manitoba results lead us to suggest
several programs that could improve the educational
outcomes of Canadian children.
Programs to improve educational outcomes
Early childhood programs
Our research has centred on school achievement, but
the focus of policies aimed at changing the trajecto-
ries of disadvantaged children should not be limited
to the school system. Our analyses and work else-
where (Hertzman et al. 2002) reveal that, while the
vast majority of children at every socioeconomic
level show remarkable similarities at birth, inequali-
ties in achievement are evident early in childhood,
prior to school entry. Children who are already
behind their peers when they begin school will likely
fall further behind; engaging them in the educational
process may be difficult. This makes it imperative for
governments to provide effective early childhood
programs (starting in the first few years of life) to
improve the experiences of children at risk.
Much research has demonstrated the remarkable
power of quality early childhood care and education-
al programs to improve a vast range of social out-
comes, particularly for socioeconomically disadvan-
taged children: reduced grade retention, higher read-
ing and mathematics scores, increased IQ, higher lev-
els of social competence, higher graduation rates,
lower teen pregnancy rates, less smoking and drug
use, higher employment and income levels, and
lower crime rates (see, for example, Kohen, Hertzman
and Willms 2002; Peisner-Feinberg et al. 2001;
Ramey and Ramey 2004). The need for quality pro-
grams is underscored by the growing number of
IRPP Choices, Vol. 12, no. 5, October 2006
22
with more effective remediation strategies for address-
ing learning difficulties could help prevent high school
withdrawal.
Addressing the gender gap
The gender gap in school performance, demonstrated
in numerous studies in Canada and elsewhere, has
gained increasing attention over the last several years.
Prior to the 1980s, concerns were raised about girls’
poorer performance, especially in mathematics and sci-
ences; however, since the mid-1980s the gender gap
has shifted, with girls consistently outperforming boys
on achievement and standards tests (Robinson 2004;
Van de gaer et al. 2004; Younger and Warrington
2002). Numerous programs have been developed to
address this gender gap, ranging from instructional
guides for teachers aimed at improving boys’ literacy
skills15 to single-sex classrooms (Mills 2004; Robinson
2004; Salomone 2006; Van de gaer et al. 2004;
Younger and Warrington 2002). Our results suggest
that the gender gap is far more pronounced among
children from socioeconomically deprived neighbour-
hoods, particularly for high school completion rates.
Thus, any programs implemented to address the gender
gap should pay particular attention to the needs of
boys from low-income areas. Given that girls from
low-income areas have much poorer performance on
standards tests than girls from more affluent areas,
and are over four times more likely to withdraw from
school, it is imperative that policies and programs
aimed at reducing the gender gap not overshadow
those aimed at reducing the socioeconomic gap.
Indeed, the key role played by girls in parenting the
future generation calls into question the current policy
of investing substantially more corrective resources in
the education of boys (Tremblay 2006).
Conclusion
This report makes it clear that whether and how a
child progresses through the school system is
strongly related to socioeconomic status. This is
not a new story. “Everyone knows” that children and
youths from socioeconomically deprived areas gener-
ally have poorer educational outcomes than those from
more affluent areas. However, population-based data
demonstrate that traditional methods of assessing the
relationship between socioeconomic status and educa-
tional achievement profoundly underestimate its
and Corwyn 2003), as well as increased numeracy
and literacy development in children (Gordon 2002).
Early school years intervention programs
Given the importance to one’s subsequent academic
success of learning to read in the early school years,
children experiencing reading difficulty must be
identified early. Appropriate interventions available
to all children experiencing difficulty may hold the
most promise for disadvantaged children (Beswick
and Sloat 2006).
One early school years program that has demon-
strated improvements not only in literacy skills but
also in mathematics is full-day kindergarten (Lee et
al. 2006). New Brunswick, Nova Scotia and Quebec
currently fund compulsory full-day kindergarten, and
all of the other provinces and territories have at least
some full-day kindergarten programs available
(Society for the Advancement of Excellence in
Education 2005). Research evaluating the effective-
ness of full-day kindergarten is limited in Canada,
and results from the United States are mixed, in
terms of long-term effectiveness (for example,
Cannon, Jacknowitz and Painter 2006; Society for
the Advancement of Excellence in Education 2005).
This points to the need for continued evaluation of
full-day kindergarten programs.
Programs for the prevention of high school
withdrawal
Programs for older children and youths, designed to
engage them and keep them interested in school
while at the same time providing them with the skills
necessary to complete high school, should also be
supported and enhanced. Whereas investing in early
child development in order to prevent poor school
outcomes from occurring in the first place may be
easier and more cost-effective, there will always be
those who have trouble in high school; effective pro-
grams to help struggling adolescents to stay in
school and improve their outcomes have been identi-
fied (Alvermann 2002; Langer 2001).
There is some evidence that students who are
retained are more likely to drop out of school than
their nonretained peers (Jimerson, Anderson and
Whipple 2002). This may at least partly explain the
higher withdrawal rate for non-Winnipeg compared
to Winnipeg students. Other research in Manitoba
has demonstrated that the retention rate for non-
Winnipeg students is over twice that for Winnipeg
students (Brownell et al. 2004). Replacing retention
23
Is the Class Half Empty? by Marni Brownell, Noralou Roos, Randy Fransoo et al.
report we have highlighted the relationship between
socioeconomic status and educational outcomes. This
relationship has wide-reaching implications that
extend beyond educational achievement. Poor school
performance in childhood can set the stage for nega-
tive outcomes in adulthood, including low incomes
(Haveman and Wolfe 1995), poor health (Centers for
Disease Control and Prevention 2002; Paeratakul et
al. 2002) and shorter life expectancy (Backlund,
Sorlie and Johnson 1999; Steenland, Henley and
Thun 2002). We need to build on the insights that we
obtain from these population-based data in a way
that will improve educational and life outcomes for
all children.
strength. We are certainly not criticizing the testing
process itself, nor even claiming that it is biased. The
testing process is very good at comparing those who
have “made it” to a given grade in school or to a
specific class. However, the testing process misses all
those who have fallen behind their classmates and
all those who have left school. Hence, we consistent-
ly underestimate the handicaps associated with low
socioeconomic status and fail to develop policies that
enable children to overcome them. In this report we
have demonstrated the need for educators to focus
not only on the performance of those who write the
examinations, and the factors that contribute to pos-
itive performance, but also on the factors that may
impede progress through the school system and lead
to dropout. We need policies that directly target the
requirements of children who have experienced
poverty, limited opportunities and other factors over
which they have little control. These children enter
the world ready to learn and create. Their parents
face multiple challenges that form strong barriers to
their children’s ability to achieve. These children will
or will not become the inventors, managers and
entrepreneurs of tomorrow, depending on how well
we help them reach their potential.
Further research, in Manitoba and in other
provinces and territories, will help us to understand
these disparities in educational outcomes and how to
overcome them. We are currently attempting to
determine what works — for example, by examining
outcomes for children of low socioeconomic status
participating in Reading Recovery programs. We are
also capitalizing on the longitudinal capabilities of
the Manitoba repository and tracking students’
achievement paths through high school, focusing on
whether high-risk youths do better in certain types
of schools (for example, in schools where more or
fewer students are taking university entrance
courses, where more students are middle class, where
fewer students become teenage mothers or where
teenage mothers are receiving special support).
Future research will also use the early child assess-
ment data now being collected in Manitoba by
means of the EDI to evaluate the impact of early
childhood programs on school readiness.
In summary, a population-based focus is needed
to change the way we think about the education sys-
tem and what we expect from it. By keeping all chil-
dren in focus, not only those who are “making it”
through the system, we can develop a framework for
changing belief structures about what matters. In this
IRPP Choices, Vol. 12, no. 5, October 2006
24
grade or more and 3 percent of those who had withdrawn
ended up graduating within two years of the test date.
6 Some students in the 18-year cohort were enrolled in a
band-operated school in 2001-02. Enrolment data for
band-operated schools are only partially reported to the
provincial Education Information System (EIS). As a
result, students in band-operated schools and not inclu-
ded in EIS enrolment data would be misclassified as
withdrawn, so an estimated number of students expected
to be enrolled in band-operated schools (from counts
provided by the department of education) were removed
from the analysis.
7 Follow-up analysis will allow us to determine what per-
centage of these students do end up graduating in subse-
quent years.
8 Students in band-operated schools were excluded from
this analysis because enrolment data are only partially
reported to the EIS. It is possible that some students were
enrolled in a non-band-operated school in grade 9 and
later transferred to a band-operated school, and would
therefore be misclassified as withdrawn because they no
longer appeared in our data. However, when this issue
was examined, only 111 (out of 15,572) students in our
1997-98 cohort (less than 1 percent) transferred to a
band-operated school in a later year.
9 Apgar scores measure the physiological well-being of
newborn babies and are recorded for virtually all births in
hospital. A score of 0, 1 or 2 is given for each of five vital
signs that are assessed at one and five minutes after birth.
These five scores are added up to give a total score
between 0 and 10. The five vital signs are appearance,
pulse, reflex, muscle tone and breathing pattern. Very low
scores are associated with poor neurological outcomes
(Stanley 1994), whereas “borderline” scores are associated
with decreased visual attentiveness in the first year of life,
compared to “good” scores (Lewis et al. 1967). Our analy-
sis considered scores of 9 or 10 at five minutes as “good.”
10 Assignment of socioeconomic group for the 1984 and
1990 cohorts was based on residence at the time the
standards test was taken.
11 Slightly smaller differences were found for females and
for residents of non-Winnipeg areas. All life-expectancy
estimates were based on Manitoba mortality rates for
1998 through 2002.
12 One limitation of this research, which may have influ-
enced the results, is the fact that the standards tests in
Manitoba are not centrally marked but are marked with-
in the school divisions (although there is a marking feed-
back process — see note 1). This could bias results if
those marking the examinations are likely to give lower
scores to students from lower socioeconomic back-
grounds. However, the main determinant of poor educa-
tional performance in this report is not performance on
the examination itself but failure to reach grade 12 on
time and write the test; the way that examinations are
marked would not influence this result.
Another limitation of the research is the use of an
area-level rather than individual-level measure of
socioeconomic status; however, past research has
Notes
1 There is, however, a marking feedback process in place
in which centrally trained markers look at a sample of
test booklets from every district.
2 Data from Winnipeg and non-Winnipeg areas were
analyzed separately because non-Winnipeg areas are
less homogeneous on socioeconomic measures than
areas within Winnipeg.
3 By using data from the research registry together with
information on school enrolment, we were able to
identify those members of the cohort who were in the
province but not enrolled in school. The quality of the
linkage between these two data sources was high, with
only 2.8 percent of the students enrolled in school in
2002 not linkable to the registry. Of this small group, a
certain percentage would not be expected to be in the
registry; these included foreign students, Canadian stu-
dents who had moved to Manitoba but whose health
coverage had not yet been transferred from their home
province and immigrant students not yet eligible for
Manitoba coverage.
4 Although some parents of the 1984 birth cohort may
have deliberately held their children back a year at
school entry, in the absence of enrolment data for the
1989-90 school year (the year they should have entered
kindergarten) it was impossible for us to determine how
frequently this occurred. An analysis of children in
kindergarten in 1998-99 through 2002-03 showed that
this deliberate holding back of students occurred for
only 2.05 percent of Winnipeg children. However, chil-
dren from the 1984 birth cohort born in December (and
to a lesser extent in November) were considerably more
likely than those born earlier in the year to be in grade
11 or lower at the “age appropriate” time. Much of this
discrepancy is likely due to cut-off dates for school
entry, which varied across school divisions at the time
that the 1984 cohort started school, with some divi-
sions using a late-November cut-off and others using a
December 31 cut-off. Some children born in November
and December appear to have started school with their
birth cohort, while others started the following year.
Analyses eliminating those born in December were
compared to those including all 12 months; small (1-2
percent) differences in frequencies were noted; if any-
thing, they accentuated the gradients across socioeco-
nomic groups in test performance.
5 Although it is tempting to assume that those who
missed the test or who were behind at least one grade
will eventually complete high school, we have found
that those who do not participate in the test “on time”
are much less likely to graduate. In a separate analysis
focusing only on Winnipeg youths, we tracked test-
takers and nontakers to determine what happened
within two years of the examination (Roos et al. forth-
coming). Ninety percent of those who passed and 76
percent of those who failed graduated within the two
years. In contrast, nontakers were much less likely to
graduate: 32 percent of those who were absent on the
test day, 19 percent of those who were retained one
25
Is the Class Half Empty? by Marni Brownell, Noralou Roos, Randy Fransoo et al.
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la population, laquelle englobe donc tous les élèves qui
auraient dû passer ce test, l’écart est beaucoup plus
prononcé : seulement 25 p. cent environ des jeunes issus
des milieux les plus défavorisés ont passé et réussi le test à
l’âge prescrit, contre 75 p. cent de ceux qui vivent dans les
quartiers les mieux nantis. De plus, les auteurs montrent
que ce décalage apparaît très tôt : dès la troisième année
du primaire, les enfants de milieux défavorisés risquent
d’avoir un rendement scolaire plus faible. Cette approche
révèle en outre un écart plus prononcé entre les sexes —
en faveur des filles — que ne le montrent les tests provin-
ciaux traditionnels, surtout dans les milieux défavorisés.
Les résultats de recherche examinés dans cette étude
montrent ainsi que les méthodes classiques qui servent à
évaluer le rapport entre milieu socio-économique et rende-
ment scolaire sous-estiment l’importance de ce lien. Une
sous-estimation qui ajoute à la difficulté d’élaborer des poli-
tiques qui permettrait aux enfants de ces milieux de sur-
monter leur désavantage. À la lumière de leurs conclusions,
les auteurs formulent donc les recommandations suivantes :
•
Les provinces doivent prioritairement renforcer leur
capacité de suivre les progrès des enfants au sein du
système éducatif.
En général, les écoles et les décideurs
se concentrent sur les élèves qui fréquentent l’école. Or
les données manquantes sur les élèves absents (et qui
devraient se trouver en classe) altèrent le tableau glo-
bal du rendement scolaire. Un suivi « fondé sur la po-
pulation » aiderait à dresser un tableau plus fidèle.
•
La conception des programmes sociaux doit intégrer
une approche universelle fondée sur les besoins.
Si l’on
rencontre beaucoup plus fréquemment des résultats
scolaires inférieurs en milieu défavorisé, le plus grand
nombre des élèves à faible rendement n’en vit pas
moins dans des quartiers mieux nantis. Les pro-
grammes ciblant uniquement les quartiers défavorisés
ne peuvent donc améliorer substantiellement le rende-
ment scolaire, d’où la nécessité de programmes uni-
versels. En ciblant les enfants dans le cadre d’une
approche universelle, on devrait assurer à ceux qui en
ont le plus besoin le supplément de soutien nécessaire
à l’amélioration de leur rendement.
•
Les provinces doivent élaborer des politiques visant à mo-
difier le parcours des enfants défavorisés au sein comme à
l’extérieur du système scolaire,
notamment grâce à des
soins de qualité et à des programmes éducatifs destinés à
la petite enfance, de même qu’à des programmes
parentaux et de lutte contre le décrochage scolaire.
La recherche montre que le rendement scolaire des
enfants s’améliore à mesure qu’on monte dans
l’échelle socio-économique. L’éducation elle-même
est généralement considérée comme un moyen d’atténuer
cet écart. Dans notre économie du savoir, on insiste
d’ailleurs de plus en plus sur l’importance de l’éducation
pour favoriser l’employabilité et la réussite économique du
plus grand nombre. Dans ce contexte, on exige maintenant
du système éducatif qu’il réponde de la réussite des élèves.
Les initiatives visant à évaluer le rendement scolaire des
enfants et à comparer les résultats sur une base régionale
et internationale sont ainsi devenues chose courante.
La plupart des provinces canadiennes administrent
aujourd’hui plusieurs examens, à différents stades, pour
évaluer les compétences et habiletés des enfants. Souvent
utilisés pour mettre en relief les écarts de rendement entre
les écoles et les districts scolaires, ces examens sont aussi
généralement l’unique source d’information dont dis-
posent les écoles désireuses de contrôler les résultats
selon le milieu socio-économique des enfants.
Les auteurs se demandent toutefois si la façon dont les
données issues de ces examens sont rapportées permet de
mesurer adéquatement les disparités socio-économiques
en matière de rendement scolaire. Ils soulignent qu’on ne
les administre qu’aux seuls élèves qui atteignent un cer-
tain niveau et qu’on ne peut par conséquent en tirer qu’un
portrait incomplet de la situation. Car les élèves les plus
faibles ont souvent déjà pris du retard ou décroché. Et
comme ces enfants proviennent de façon disproportionnée
de milieux défavorisés, ces examens ne peuvent révéler les
véritables inégalités en matière de rendement scolaire.
Les auteurs proposent donc une autre méthode
« fondée sur la population » qui s’intéresse au rendement
de tous les enfants d’un âge donné, qu’ils fréquentent
l’école ou non. Ils expliquent comment établir une telle
base de données pour dresser un portrait plus complet du
rendement scolaire, et présentent les résultats clés tirés de
l’expérience manitobaine. Ils visent ainsi un double
objectif : offrir un modèle aux autorités ayant la capacité
d’appliquer une méthode semblable dans leur province ou
district scolaire, et faire valoir les avantages de cette
approche pour les chercheurs, éducateurs et décideurs.
Selon l’une des principales conclusions de leur étude, les
disparités socio-économiques sont nettement supérieures à
celles que révèlent l’approche classique. Si l’on se fie par
exemple aux données sur les élèves ayant passé le test (soit
les données généralement utilisées), on observe que
75 p. cent des élèves des quartiers les plus défavorisés de
Winnipeg et plus de 90 p. cent de ceux qui vivent dans les
quartiers les mieux nantis ont réussi l’examen de langue de
12eannée (secondaire V). Mais selon l’approche fondée sur
Résumé
30
Summary
school-based tests) shows that 75 percent of students from
deprived neighbourhoods in Winnipeg and over 90 percent
of students from better off neighbourhoods passed the grade
12 language arts test. In contrast, the population-based
approach, which includes all kids who should have been
writing the test, reveals a much steeper gradient: only about
25 percent of youths living in socioeconomically poor areas
wrote and passed the test at an age-appropriate time, com-
pared with 75 percent of youths from more affluent areas.
This steeper gradient is apparent early on: by grade 3, chil-
dren from the deprived neighbourhoods are already much
less likely to be performing well. The population-based
approach also demonstrates that gender differences in edu-
cational outcomes are more pronounced, in favour of girls,
than conventional provincial tests suggest, especially for
kids from socioeconomically deprived areas.
The research discussed in this report demonstrates that
traditional methods of assessing how socioeconomic
background is related to educational achievement under-
estimate the strength of this relationship. This contributes
to the failure to develop policies that would enable chil-
dren from socioeconomically deprived backgrounds to
overcome these disadvantages. Based on their findings,
the authors recommend that:
•
Provinces make a priority of developing their capability to
track children’s progress through the system
. They observe
that schools and policy-makers have typically focused on
who is in the classrooms, but argue that information
about those who are not in school (and who should be) is
a missing piece of the educational achievement picture.
•
The design of social programs incorporate a needs-based,
universal approach
. "Although a higher percentage of
socioeconomically deprived students have poor educa-
tional outcomes, a larger number of students who per-
form poorly live in the better off areas. Therefore,
programs that are directed only at poor neighbourhoods
would not substantially reduce low performance rates,
which is the rationale behind universal programs.
Targeting within the framework of a universal approach
should ensure that children with the greatest need receive
the extra support they need to improve their outcomes.
•
Provinces develop policies aimed at changing the trajecto-
ries of disadvantaged children within and also outside the
school system
, for example, by means of good early child-
hood care and educational programs, parenting programs
and programs to reduce the high school dropout rate.
Research demonstrates children’s academic perform-
ance increases with improved socioeconomic status.
Education itself is often seen as a means of leveling
this gradient. Indeed, our knowledge-based economy
emphasizes the importance of education to enhance employ-
ment opportunities and economic success for all. With the
increasing demand that educational systems be accountable
for student outcomes, policy initiatives that report student
performance and compare educational results regionally and
internationally are now common.
As Marni Brownell, Noralou Roos, Randy Fransoo and
their colleagues note in this study, most Canadian
provinces have some form of achievement testing at vari-
ous stages to assess curriculum-based standards. Often
used to highlight differences in performance across
schools or school districts, these tests are frequently the
only information schools have to monitor the outcomes
of students from different socioeconomic backgrounds.
The authors question whether the way the information
from these tools is reported is adequate for assessing
socioeconomic disparities in students’ performance. They
point out that the tests are typically administered only to
those who reach a specific grade, and they thus offer an
incomplete picture of student outcomes. Poor-performing
students may have already dropped behind or out of
school entirely. And since these poor performers are dis-
proportionately students from disadvantaged back-
grounds, the results from school-based testing do not
capture the real inequalities in educational achievement.
They propose an alternative, population-based approach
that focuses on the achievement of all children of a given
age, regardless of where, or whether, they are enrolled in the
school system. They describe the development and use of
population-based databases to draw a more complete picture
of educational outcomes, and they present key results from
one such data repository in Manitoba. Their purpose is
twofold: to provide a model for those jurisdictions that have
the potential to implement similar population-based meth-
ods in their own provinces or school districts, and to outline
the insights and implications of population-based work for
researchers, educators and policy-makers.
One key result from their study is that the socioeconomic
disparities of educational outcomes are far greater than had
been previously realized based on traditional school-based
testing. For instance, using the information on those present
to write the test (the information generally presented on
Summary Is the Class Half Empty?
A Population-Based Perspective on Socioeconomic Status
and Educational Outcomes
by Marni Brownell, Noralou Roos, Randy Fransoo et al.
