Criminology Essay Questions: Family Size, Type & Student Achievement

Criminology Essay Questions
Please answer the following questions using APA citation in
one or two paragraphs:
1. In what fundamental ways does conflict theory differ from
the other theories we have covered (choice, trait, social
structure, social process)?
2. Which social process theory does the best job of explaining
adult criminality? Which social process theory does the best job
of explaining juvenile delinquency? (These cannot be the same
theories.) What do both of these theories have in common?
Family Size, Family Type and Student Achievement:
Cross-National Differences and the Role of
Socioeconomic and School factors
GARY N.MARKS*
BNTRODUCnON
The finding that students from larger families have less
favorable educational outcomes is
well established in the United States (Blake, 1989; Mare and
Chen, 1986; Powell and Parcel,
1999). Negative effects for family size or the tiumber of
siblings on educational attainment
have been also found in Australia, Finland, Hong Kong and
Israel (Le and Miller, 2001; Post
and Pong, 1998; Riala, et al., 2003; Shavit and Pierce, 1991).

With regard to family type, it is
generally concluded that in the United States children from
divorced families show poorer
educational outcomes than children from intact families (Amato,
2000; Jeynes, 2002:13-18).
Lower educational attainments of students from divorced or
single-patent families have also
been found in Finland and Great Britain (Powell and Parcel,
1999; Riala, et al., 2003). In the
United States, children from reconstituted families — that is,
families with a stepparent —
tend to have lower educational attainments than children from
two-parent families, and, in
quite often, single-parent families (Biblarz and Raferty, 1999;
Jeynes, 1999).
It is not possible to conclude if the effects of family size and
type on educational outcomes
are similar or very different across countries, even with a large
number of single country
studies, due to differences in sampling and measurement.
However, cross-national
comparisons are possible with international studies of student
achievement, which select
comparable samples and use identical outcome measures. In the
first international reading
study, Thomdike (1973:74-79) reported consistently negative
correlations between the number
of siblings and reading achievement among 14-year-olds. The
median correlation was -0.11,
with stronger negative effects in Scotland, England and
Hungary, but very weak correlations
in other countries. In the first international science study, the
negative correlation between
family size and science achievement was strongest iti Scotland,
England and Japan, and

weakest in Belgium, Italy and Sweden (Comber and Keeves,
1973:258). The more recent
international achievement studies have not been employed to
extensively examine the
relationship between family size and achievement. However,
they have been used to
investigate the effects of single-parent families. Using data
from the Third International
Mathematics and Science Study (TIMSS), Pong et al. (2003)
found negative effects on
•Melbourne Institute for Applied Economic and Social
Research, University of Melboume, Vietoria 3010,
Australia
* Australian Council for Educational Research, 347 Camberwell
Rd. Camberwell, Vietoria 3124, Australia
2 Journal of Comparative Family Studies
achievement in mathematics and science for a single-parent
family in most ofthe 12 eountries
examined. The largest effects were found for the United States
and New Zealand. In most
countries in the OECD's 2000 Program for International Student
Assessment (PISA), students
from single-parent households had lower reading scores than
other students. Larger
differences were found in the United States, Finland, the United
Kingdom and the Netherlands
(OECD,2001:152,194,292).
One explanation for differences in educational outcomes
according to family size or type is

simply socioeconomic background. Larger and single-parent
families tend to have lower
socioeconomic status, so the effects of family size and family
type may be due largely to
socioeconomic background. In the United States, socioeconomic
status and race accounted
for most of the lower scores of eighth grade students from
single-parent families (Finn and
Owings, 1994). Similarly, Thompson et al. (1994) concluded
that economic disadvantage was
responsible for the poorer outcomes of children from single-
parent families. Downey (1995a)
found that parents' economic and cultural resources, together
with their participation in their
child's activities, largely explained achievement differences
between students from step-
and intact families. Jeynes (2002:72-77) found that post-divorce
socioeconomic status almost
completely explained the negative effects of divorce on
educational attainment.
Blake (1989) formulated the resource dilution hypothesis to
explain the finding that students
from larger families perform less well academically. Larger
families will have less material
resources for a given income level and parents have less time
spend on each child. Downey
(1995b) found that measures of economic resources and time
spent talking with the student
could account for the effects of sibship size, largely confirming
the dilution hypothesis.
Although Downey (2001) notes problems with the resources
dilution theory, he concludes
that it useful for explaining the inverse relationship between
family size and achievement in
the United States.

Educational systems may also play a role. Students from larger
and non-intact families tend
to be concentrated in less demanding school programs (or
schools) and therefore have
weaker educational outcomes. For the United States, Pong
(1997; 1998) noted that students
from single-parent families are clustered in particular schools
and these schools tend to have
lower educational attainments. The clustering of students from
larger, single-parent or
reconstituted families may be particularly important in
European countries with tracked
education systems, where there are larger achievement
differences between schools.
Endeavoring to explain differences hetween countries in the
effects of family type, Schiller et
al. (2002) concluded that the benefits of living in a traditional
(intact) family were stronger in
more-economically developed economies. They speculated that
greater resources were
required to educate children in economically developed
countries. Riala et al. (2003), after
finding only weak effects for a single-parent family in Finland,
concluded that the effects of
family type are likely to be smaller in welfare states with highly
educated populations. Pong
(2003) concluded that differences in the government provision
of resources to single-parent
families accounted for differences between countries.
The main purpose of this paper is to cross-nationally compare
the effects of family size and

Family size. Family type and Student Achievement 3
family type on student achievement, and to examine the extent
that these effects can be
accounted for by socioeconomic background, resources in the
home and school factors.
The research questions addressed in this study are:
What are the cross-national patterns in the effects of family size
and family type on
student achievement in reading and mathematics?
To what extent can the effects of family size and family type be
attributed to
socioeconomic background?
Is the resource dilution hypothesis supported in most countries?
In other words, do
more limited material resources and social resources (including
parent time spent with
the child) account for the negative relationship between family
size and student
achievement?
Are students from larger and non-traditional families more
likely to be found in
academically weaker locations in the school system, especially
in countries with tracked
school systems?
* Can cross-national differences in the effects of family size
and family type be attributed
to economic development, the size of the welfare state or other
characteristics of
countries?

This study addresses these questions with data from 30
countries. In contrast to the OECD
(2002b) and the Pong et al. (2003) studies of family effects, this
study examines the effects of
reconstituted families as well as single-parent families. A much
stronger measure of
socioeconomic background (father's and mother's occupation
and education) is used than
was possible in the Pong et al. (2003) study. Furthermore, the
study distinguishes between
socioeconomic background and the material resources
(possessions) in the home because
the resource-dilution hypothesis directly applies to material
resources in the home; larger
families will have less of them.
DATA AND MEASURES
The data is from the OECD 2000 Program for International,
Student Assessment (PISA)
study that examined student achievement in reading,
mathematics and science for over
172,000 15-year-old students in 6,000 schools across 32
countries. Participating in the survey
were all OECD countries except Turkey, and several non-OECD
countries: Brazil, Latvia and
the Russian Federation. Within each country, a two-stage
sampling procedure was employed,
first randomly selecting schools with probabilities proportional
to size and second, randomly
selecting 15-year-old students. In some countries;schools were
stratified by type or location.
Details on the sampling and procedures can be found in the
initial and technical reports
(OECD, 2001; OECD, 2002a). Japan was excluded from the

analyses for this paper because
there was too much missing data on the components of
socioeconomic background, parents'
occupations and education. Liechtenstein was also excluded,
because of the small sample
size.
MEASURES
Family Size and Family Type
The measure of 'family size' was constructed from a question on
the number of the student's
brothers and sisters. The question asked 'How many brothers
and sisters do you have?' and
the students were asked to distinguish siblings of older, younger
and the same age. The
question did not exclude stepbrothers and stepsisters. Summary
statistics on family size are
presented in Table 1. In almost all countries, the modal number
of siblings is one or two, with
the exception of Mexico, where the modal number of siblings is
three. The column headed
'Mean' shows that the largest families of 15-year-olds are in
Mexico, followed by Ireland,
Iceland, the United States and Brazil. The smallest families are
in Italy and Korea.
'Family type' is comprised of four categories: intact, single-
parent, reconstituted and other
families. 'Intact' is defined as when the student lives in the same

household as both parents;
where on the questionnaire the student indicated they were
living with their mother and their
father. 'Single-parent' families refer to both single-mother and
single-father families.
'Reconstituted' families comprise families where the student is
living with a parent and a
stepparent. In these cases, students indicated they were living
with a mother or father and a
stepmother or stepfather. 'Other' is a residual group which
includes students living with two
stepparents of opposite sex (32 per cent), students living with
one or more grandparents but
no parent or stepparent (30 per cent) and students living with
siblings but without parents,
stepparents or grandparents (38 per cent). Table 1 shows the
unweighted frequency
distributions for family type. In most countries between 70 and
80 per cent of 15-year-olds
live in intact families. Korea shows the highest proportion at 87
per cent and the United
States shows the lowest proportion at around 50 per cent. The
proportion of students living
in single-parent households was under 10 per cent in Greece,
Korea and the Netherlands,
over 20 per cent, in Latvia, New Zealand and the United States,
and between 10 and 20 per
cent in the other countries. The proportion living in
reconstituted families is highest in the
United States at around 15 per cent. In Australia, Denmark,
Iceland, Latvia and New Zealand
over 10 per cent of 15 year-olds live in reconstituted families.
The proportion living in
reconstituted families is very low in Greece, Ireland, Italy,
Korea and Mexico. In the other
countries the proportion is between 5 and 10 per cent. The

proportions living in 'other'
family types are much lower, below 2 per cent in all countries
except Brazil and the United
States.
Reading and Mathematics Achievement
The two measures of student performance analyzed here are
reading achievement and
mathematics achievement. Item Response Theory (IRT)
modeling was used to create scores
standardized at an international OECD mean of 500 and
standard deviation of 100. The
country means and standard deviations can be found in the
OECD's initial PISA report
(OECD, 2001:253,259). Students' scores are in the form of five
plausible values rather than a
single score. The technical report (OECD, 2002a) details the
development and construction
of the achievement measures.
Family size. Family type and Student Achievement
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Family size, Family type and Student Achievement 7
Socioeconomic Background
Socioeconomic background is a composite measure comprising
parental occupational status
and educational attainment. If data on one or other variable was
missing, information on the
other variables was used to construct the njeasure. Parental
occupation was coded according
to the International Standard Classification of Occupation 1988
(ISCO-88), as provided by
the International Labour Office. ISCO-88 is a four-digit
hierarchical coding schema compdsitig
390 different occupational categories. The parental occupation
measures are based on the
International Socioeconomic Index (ISEI) index, which ranges
from zero to 100 based on
ISCO-88 codes. Ganzeboom and Treiman (1996) provide details
on its construction and list
ISCO-88 occupational titles with their respective ISEI scores.
Information on the educational attainment of each parent was
collected by two questions.
The first asked for the parent's level of school education
completed. A follow-up question
asked about whether the parent had completed a post-secondary
qualification. The responses

to these questions were classified according to the International
Standard Classification of
Education (ISCED) schema (OECD, 1999). Parental education
was coded as one of seven
categories: No Schooling, Primary School, Middle Secondary
School, Higher Secondary
School (Non- Academic), Higher Secondary School (Academic),
Tertiary Education (Non-
Academic), and Tertiary Education (Academic). Continuous
measures were constructed by
optimal scaling, which changes the ordinal and cardinal
properties of the measure to maximize
the relationship of father's or mother's education with student
achievement.
Resources
'Material resources' is a summary measure based on the
possessions and educational
resources in the home. Possessions include the presence or
absence at the student's home
of a dishwasher, their own room and a link to the Internet; and
the number of household
mobile phones, televisions, computers, bathrooms and cars.
Educational resources include
possession of a dictionary, a quiet place to study, a desk for
study and textbooks, and the
number of calculators in the home. The logic of this measure is
that in larger families students
are less likely to have as many of these material resources.
The measure 'Social Resources' was constructed from a question
that asked how often do
the parents discuss the student's progress at school, how often
the family eats their main
meal around a table, and how often the parents spend time just

talking to the student These
social resources provide an index of parental time spent with
students on their school work
and more generally. The three items were isolated from
principal component analysis. Social
resources were not included in the analyses of family type,
since there is no theoretical
rationale for its inclusion.
Academic Location
Academic location is defined by the student's' school and the
student's location within the
school. Individual schools were identified from the data and
multilevel modeling was used to
control for between-school differences in achievement!
Location within schools was
ascertained by grade and school program.
All students were asked their grade at school. The grade
variable was scored relative to the
modal grade ofthe country. If the students were in the modal
grade they were given a score
of zero for grade, a score of 1 if one grade above the modal
grade, a score of -1 if one grade
below the modal grade, and so on. Information on school
program was elicited by a single
question asking students what type of program they were in at
school. The response categories
were appropriate to the national context but also corresponded
to the categories in the

OECD's 1999 International Standard Classification of Education
(ISCED). This classification
separates academic, vocational and work preparation programs
at two levels: upper and
middle secondary school. A variable 'school program' was
constructed comprising the
following categories: Academic Program (Lower Level), Non-
Academic Program (Lower Level),
Academic Program (Higher Level) and Non-Academic Program
(Higher Level). In countries
where there was no data on program differentiation within
schools (Canada, Finland, Iceland
and Norway), the measure of academic location was based only
on grade.
Analyses
These analyses allow examination of the effects of family size
and family type with and
without controls for socioeconomic background, resources, and
academic location. The
extent that the effects for family size and family type decline
when controlling for these
factors indicates their importance. For example, if the effects
for family type are reduced to
statistical insignificance when controlling for socioeconomic
background, then it can be
concluded that socioeconomic background 'accounts' for the
relationship. Similarly, the
resource dilution hypothesis would be supported if the effects of
family size were not
statistically significant when controlling for material and social
resources.
The effects on family size and type are presented as regression
coefficients that refiect the

(average) change in achievement score for a unit change or
difference in the independent
variable. For family size, the effect refiects the change in
achievement score for one additional
sibling. For family type, the effects for single-parent,
reconstituted and 'other' family types
are relative to students from intact families. The differences are
exactly the same as obtained
by comparing the mean achievement scores of students from
each group.
The standard errors associated with the regression coefficients
have been adjusted to take
into account the cluster design of the sample and sample
stratification (if employed). Each
regression coefficient and standard error was calculated by
averaging the results obtained
fi-om separate analyses ofthe five plausible values (obtained
from IRT modeling). The statistical
significance of the effects is indicated in the standard way. All
analyses were weighted to
refiect the population of 15-year-old students in each country.
RESULTS
Number of Siblings
Table 2 presents the effects of number of siblings on reading
achievement, with and without
controls for socioeconomic background, resources and school
factors. The first column

shows each country's unadjusted or total effects for one sibling.
Column 2 shows the
coefficients when socioeconomic background is taken into
account. The coefficients in
Column 3 are net of socioeconomic background and material
resources. The coefficients in
Column 4 were estimated after, the further addition of social
resources. The final column
shows the effects of one sibling on reading achievement net of
socioeconomic background,
material and social resources, and academic location.
In all countries except Iceland, the effect of the number of
siblings is negative and statistically
significant. This means that each additional sibling is associated
with lower reading scores.
Its effect was particularly strong in Portugal, where one sibling
was associated with an
average reading score 21 points lower. By extension, 2 siblings
reduces the score by 42 score
points and 3 siblings 63 score points. The correlation between
the number of siblings and
reading achievement in Portugal was about 0.26 so its effect is
not trivial. Relatively strong
effects for the number of siblings were also found for Belgium,
the Czech Republic and Italy
(-18 score points) and Hungary, Germany, Greece, and New
Zealand. Besides Iceland, the
countries showing the weakest effects for number of siblings
were Finland, Denmark, Canada
and Korea.
In most countries, the effect of the number of siblings on
reading achievement declined after
taking into account the student's socioeconomic background.
Declines were found in almost

all countries, except those with relatively small initial effects.
The effect of number of siblings
was reduced by over 40 per cent in several countries: Austria,
Brazil, the Czech Republic,
France, Hungary, Korea, Mexico, Poland, Switzerland and the
United Kingdom. In contrast,'
socioeconomic background had little impact on the effect of the
number of siblings in Italy,'
Luxembourg and Russia. For the Netherlands, the effect of the
number of siblings was not
statistically significant when controlling for socioeconomic
background. However, in most
countries much of the impact of family size on reading
achievement can be attributed to
students' socioeconomic background. In only 6 of the 30
countries examined was the effect
for the number of siblings on reading achievement, net of
socioeconomic background, greater
than 10 score points. Before controlling for socioeconomic
background, its effect was above
10 score points in 17 of the 30 countries.
The next step in the analyses was to test the resource dilution
hypothesis by examining the
impact of material and social resources on the effects of family
size. Neither had much impact.
In almost all countries the effect of the number of siblings on
reading scores declined only
marginally. After adding for material resources, the effects of
the number of siblings declined
by up to only 3 score points. The addition of social resources
produced a further decline
again of up to only 3 score points. In most countries the
declines were much smaller. The
exceptions were the Czech Republic where the effect declined
from 11 to 5 score points. So in

most countries the effects of family size are not closely
associated with material and social
resources.
Taking into account the distribution of students across schools
and the academic location of
students within schools produced more substantial declines.
Declines were observed in
most countries, especially in European countries with tracked
school systems: for example,
Austria, Belgium, the Czech Republic, Greece, Hungary, Italy
and Portugal. Smaller declines'
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were found in countries with less differentiated school systems.
Therefore, in many countries
especially those with tracked school systems, students from
larger families tend to be in the
less academic locations in the school system.
Table 3 presents the results for the same series of analyses, but
for mathematics rather than
reading. Generally, the pattern of results is similar. In most
countries, the unadjusted effects
of the number of siblings on mathematics achievement were
very similar to that for reading
achievement. Exceptions were Korea, where the effect ofthe
number of siblings was much
greater for mathematics than for reading, and Switzerland,
where the effect of family size on
mathematics achievement was not significant but the effect on
reading was negative 10
score points. The extent that socioeconomic background
accounted for the effects of family
size on mathematics achievement was almost identical to that
for reading. Material and social
resources had little impact on the effect of the number of
siblings (except in the Czech
Republic and Portugal) and, when controlling for academic
location, the net effects for

number of siblings were quite small. The impact of academic
location on the effect of family
size does not appear to be stronger for mathematics than for
reading.
Family Type
Students from intact families (living with both parents) have
higher scores than students
from single-parent, reconstituted or other types of families.
None ofthe 30 countries examined
showed, for both reading and mathematics, a statistically
significant effect indicating that
students from intact families had lower average scores than
students from the other family
types (Table 4). For reading, students from single-parent
families had significantly lower
scores in 18 countries and students from reconstituted families
had lower scores in 26
countries. For mathematics, students from single-parent families
had significantly lower
scores in 21 countries and students from reconstituted families
had significantly lower scores
in a slightly different group of 21 countries.
The largest effects for a single-parent family were found for the
United States where, on
average, students from single-parent family had lower scores
that students from intact families
— 50 score points lower for reading, and 53 score points lower
for mathematics. These are
large effects, considering that 100 score points approximates
one standard deviation. The
United States, then, has both the largest proportion of 15-year-
olds living in single-parent
families and the strongest effects for single-parent families.

Other countries with large effects
for a single-parent family were the Netherlands (34 score points
in reading and 44 score
points in mathematics) and the United Kingdom (34 score points
in readitig and 31 in
mathematics). Moderate to large differences were also found in
Belgium, Finland, France,
Ireland, New Zealand, Norway and Sweden. There were no
significant differences between
students from single-parent and intact families, for both reading
and mathematics, in Austria,
Brazil, the Czech Republic, Greece, Iceland, Russia and
Switzerland. In Mexico, Poland and
Portugal there were significant differences for mathematics but
not for reading. In Latvia and
Luxembourg, the effect for a single-parent family was
significant for reading but not for
mathematics.
The largest differences in reading performance between students
from reconstituted and
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intact families were found in the United States (46 score
points), Belgium (34), Australia (33),
New Zealand (30), Poland (29), Canada (28) and Norway (25).
In four countries — Brazil,
Greece, Latvia and Portugal — there was no significant
difference in average reading scores
between students from reconstituted and intact families. In
many countries — Australia,
Austria, Canada, Germany, Hungary, Iceland, Luxembourg,
Mexico, Poland, Spain and
Switzerland — the difference in average score for reading
between students from reconstituted
and intact families was substantially greater than differences
between students from single-
parent and intact families. In other countries the effects were
comparable. In few countries —
Denmark, the Netherlands and the United Kingdom — the effect
of a reconstituted family
was substantially less than that for a single-parent family.
For mathematics, the findings were only a little different from
those for reading. Countries
showing the largest significant differences between students
from reconstituted and intact
families were the United States (43 score points), Belgium (37),
New Zealand (34), Hungary
(31), Switzerland (30), Norway (29) and Latvia (28). Compared
to reading, a larger group of
countries showed no significant differences in mathematics
achievement between students
from reconstituted and intact families: Brazil, Greece, Ireland,
Italy, the Netherlands, Poland,
Portugal, Russia and Spain.
Table 4 shows that in almost all countries the small groups of

students from 'other' family
types have substantially lower scores in both reading and
mathematics than students from
intact families. The effects for 'other' family type are often
much larger than the effects for
single-parent or reconstituted families. Again, the largest
effects are for the United States,
where this group is proportionally largest. Since there too few
students living in 'other'
family types for stable estimates, this group is not included in
the subsequent analyses
discussed below.
Socioeconomic Background
In most countries socioeconomic background reduced the effect
of a single-parent family,
but sizable effects remained (compare Table 5 to Table 4).
Adding socioeconomic background
to the analysis reduced the effect of living in a single-parent
family on reading achievement
by up to only 5 score points in 1.9 of the 30 countries. Larger
declines were found in Belgium,
Korea, Ireland, the Netherlands, and the United States. When
controlling for socioeconomic
background, the effects of a single-parent family on reading
achievement became insignificant
only in Australia and Hungary.
For mathematics the findings were very similar. In most
countries, socioeconomic background
reduced the effects for a single-parent family but does not
account for the relationship. In the
21 countries with significant effects for a single-parent family,
controlling for socioeconomic
background effect reduced the effect to statistical insignificance

only in Australia. In 18 of
the 30 countries the decline was less than 4 score points. In
most countries sizable effects for
living in a single-parent family remained when controlling for
socioeconomic background.
Socioeconomic background has less impact on achievement
differences between students
from reconstituted and intact families. The only countries where
the initial effect was at least
moderate (over 20 score points) and the addition of
socioeconomic background produced a
Table 5
DIFFERENCES IN READING AND MATHEMATICS SCORES
BY FAMILY TYPE
(NET OF SOCIOECONOMIC BACKGROUND)
Australia
Austria
Belgium
Brazil
Canada
Czech Republic
Denmark
Finland
France
Germany
Greece
Hungary
Iceland

Ireland
Italy
Korea
Latvia
Luxembourg
Mexico
Netherlands
New Zealand
Norway
Poland
Portugal
Russian Federation
Spain
Sweden
Switzerland
United Kingdom
United States
Reading 1
Single-parent
-6.3
-5.5
-19.8***
-8.6*
-10.1***
-1.7
-14.7**
-21.5**
-20 7***
-9.4
-5.8
-5.4

-2.5
-18.7***
-10.8**
-10.9*
-8.5
-17.0**
-2.1
-24.0**
-23.4***
-20.0***
4.4
-5.4
-0.1
-9.3**
-18.2***
-7.2
-29 5***
-39.0***
Reconstituted
-24.7***
-20.8*** 1
-20.2*** 1
-7.5
-22.1***
4.3
-9.4*
-18.5**

-16.4***
-24.8***
-11.3
-16.7**
-10.9*
-32.1**
-33.8**
-25.5***
-10.9
-30.7***
-15.4*
-18.7*
-21 3***
-17.1**
-22.7
-12.3
4.1
-26.8***
-15.2***
-25.8***
-14.0**
-33.1***
Mathematics
Single-parent
-6.1
-13.5*
-16.9**
-16.6*
-16.4
-10.9
-19 3***
-17.6***
-21.6***

-14.2**
-16.8
-10.1*
2.9
-21.1***
-15.7***
-16.0*
-2.5
-11.7
-10.3*
1 -31.6**
-23.4***
1 .30.5***
1 -21.9*
1 -14.5*
1 -7.6
1 -12.3*
I -18.5***
1 -13.0*
1 -27 9***
1 -45.7***
Reconstituted
-12.6
-224**
-20.2**
-15.8*
-19 5***
-10.2
-11.9*
-21.9***

-18.2**
-22.8**
-31.6
-26.4***
-13.5*
-7.5
-17.8
-23.2**
-27.7**
-28.6**
-20.2*
-94
-25.5***
-24.0***
-18.7
-18.5
5.3
-13.9
-15.4**
-33 1***
-13.1*
-32.1***
Note: Comparison with Intact Families. *0.0t<P<0.05, **0.00t
<P<0.01 ***P<O.OOt
substantial decline in the effects of a reconstituted family type
were Australia, Belgium, New
Zealand, Norway and the United States. Only in Belgium,
however, was the decline more
than 40 per cent. Almost identical results were obtained for
mathematics.

Material Resources
More substantial declines for the effect of a single-parent
family on reading achievement
were found with the addition of material resources: in Belgium
(from 20 to 10 score points),
Canada (from 10 score points to statistical insignificance),
Denmark (from 15 to statistical
insignificance), France (21 to 10), Korea (1 1 to statistical
insignificance), Luxembourg (17 to
statistical insignificance), the Netherlands (24 to 15), New
Zealand (23 to 9), Norway (20 to
11) and the United States (39 to 27). In many countries,
material resources also reduced the
effects of a single-parent family on mathematics achievement
(compare Table 6 to Table 5).
This implies that the lower scores of students from single-parent
families can be attributed
more to differences in wealth and educational resources than to
socioeconomic status.
In contrast, adding material resources to the analysis did not
produce as large a decline in the
effect of a reconstituted family. For example, compare the
declines in the effects of a single-
parent and a reconstituted family on reading in Belgium,
Canada, Denmark, Ireland, Korea,
Luxembourg, New Zealand, Sweden, Switzerland and the United
States. After controlling for
socioeconomic background and material resources, the effects
of a reconstituted family on

reading remained substantial in several countries: Italy (a 35
score point difference), Ireland
(29), Luxembourg (27), the United States (26), Spain (24),
Korea (24), Switzerland (24), Australia
(21) and Germany (20). In contrast, only the United Kingdom
and the United States show
effects of a single-parent family greater than 20 score points
with the same controls. So
generally, material factors play a large role in the lower scores
of students from single-parent
than from reconstituted families.
Academic Location
After controlling for socioeconomic background and material
resources, the effects of a
single-parent family were already quite weak in most countries.
Among countries with relatively
substantial and significant effects controlling for academic
location substantially reduced
the effect for a single-parent family on reading achievement in
the Netherlands, produced
moderate declines in Finland, the United Kingdom and United
States and had no impact in
Sweden and Norway.
Controlling for academic location substantially reduced the
effect for a reconstituted family
especially in countries with tracked school systems (compare
Table 7 to Table 6). This was
particularly evident in Austria, Belgium and Germany. In
contrast, controlling for school
factors had little impact on the remaining effects of family type
in Norway and Sweden, and
a small or moderate impact in Finland, New Zealand, the United
Kingdom and the United

States. These countries primarily have comprehensive systems.
So in countries with highly
tracked educational systems, students from non-intact families
are more likely to be found in
the academically weaker locations in the tracked school system.
DISCUSSION
A substantial proportion ofthe effect of family size on reading
and mathematics achievement
can, in many countries, be attributed to socioeconomic
background. In almost all countries,
the effect of family size declined by between a quarter and a
half when taking into account
socioeconomic background. Therefore, miich of the association
between family size and
educational outcomes is simply due to the correspondence
between larger families and lower
socioeconomic status. In contrast, material resources and social
resources made little additional
impact on the effects of family size. These variables were
included to test Blake's resource
Table 6
BY FAMILY TYPE
(NET OF SOCIOECONOMIC BACKGROUND AND
MATERIAL RESOURCES)
Australia
Austria

Belgium
Brazil
Canada
Czech Republic
Denmark
Finland
France
Germany
Greece
Hungary
Iceland
Ireland
Italy
Korea
Latvia
Luxembourg
Mexico
Netherlands
New Zealand
Norway
Poland
Portugal
Russian Federation
Spain
Sweden
Switzerland
United Kingdom
United States
Reading
Single-parent
5.6
0.7
-9.6*

-2.0
4.1
4.6
-8.4
-17.4**
-9.5*
0.5
1.6
-2.4
-0.7
-13.2*
.-8.4*
-3.8
A.5
-3.2
1.9
-15.4*
-9.1*
-11.3*
-0.3
1.4
1.9
-6.2*
-13.4**
-0.2
-24.1***
-26.6***

Reconstituted
-20.6***
-16.8**
-14.5**
-5.5
-18.5***
. -3.7
-7.0
-16.9**
-10.7**
-19.9**
-5.4
-15.2**
-9.8
-28.8*
-35.2**
-23.8***
-8.2
-26.6***
-13.8
-11.7
-16.1**
-10.2
-18.3
-8.4
-3.3
-24.4**
-12.6**
-23.4***

-12.2**
-26.4***
Mathematics
Single-parent
3.6
-42
-5.7
-6.0
-11.0***
4.2
-13.0*
-10.4*
-10.1*
-6.4
-8.6
-6.4
2.5
-12.4*
-13.6***
4.7
2.0
2.0
-5.7
-20.2
9.0
-22.8***
-17.4
-7.5

-2.7
-8.7
-8.8
-6.6
-22 9***
-29.0***
Reconstituted
-10.7
-17.0*
-11.5
-13.3
-16.9***
-10.3
-8.6
-19.5**
. -11.2*
-21.7**
-22.5
-23.6***
-13.0*
4.4
-20.3
-20.8*
-22.8**
-23.2*
-20.0*
-0.7
-21.2**
-16.4*

-14.3
-14.6
6.0
-10.6
-10.1
-30.0***
-11.7
-23.0***
Note: Comparison with Intact Families. * 0.0t<P<0.05, **
O.OOt <P<O.Ot *** P<0.001
dilution hypothesis (1989), since, other things equal, larger
families have less material resources
and parents in larger families have less time to spend with each
child. However, these analyses
found that material and social resources did not help account for
the relationship between
family size and achievement so the resource dilution hypothesis
was not supported.
In many countries the effects of a single-parent family were
substantially reduced or
insignificant when controlling for socioeconomic background
and material resources. Often,
material resources had a larger impact, suggesting that part of
reason for the lower achievements
of students from single-parent families is the lower levels of
wealth and educational resources.
Table 7

BY FAMILY TYPE
(NET OF SOCIOECONOMIC BACKGROUIVD,
MATERIAL RESOURCES AND ACADEMIC LOCATION)
Australia
Austria
Belgitim
Brazil
Canada
Czech Republic
Denmark
Finland
France
Germany
Greece
Hungary
Iceland
Ireland
Italy
Korea
Latvia
Luxembourg
Mexico
Netherlands
New Zealand
Norway
Poland
Portugal
Russian Federation
Spain
Sweden
Switzerland
United Kingdom

United States
Reading
Single-parent
3.1
6.1
2.7
4.0
-3.6*
3.4
-5.4
-12.0***
0.5
5.7*
-0.7
6.9**
-0.6
-7.6
A 8
5.9
0.6
7.6
7.8**
-0.8
-9.7*
-11.1*
4.7
4.5

2.0
-0.9
-12.8*
5.0
-20.3***
-19.7***
Reconstituted
-15.3***
-0.1
6.7*
4.5
-13.3***
1.6
-5.3
-11.1*
6.6*
-2.1
-0.8
-2.9
-11.6*
-18.1*
-14.6*
-17.1**
-0.7
-10.3*
-2.7
-3.7

-14.3**
-9.1
-9.3
5.6
-1.6
-5.8
-13.0**
-7.8*
.12.4***
-23.0***
I Mathematics
Single-parent
1.7
1 4.9
1 2.4
4.8
-9.9***
-6.3
-9.8*
-6.8
-0.6
4.1
-7.9
4.4
2.2
-9.8
-7.3*

9.9
4.5
8.2
-0.7
-6.2
-7.1
.21.7***
-7.4
-6.2
-2.8
A.6
-7.6
-0.2
.19.7***
-20.4***
Reconstituted
-6.3
-1.5
2.9
-4.9
.141***
-3.3
-7.7
-16.4**
3.2
-5.1
-6.6

-14.8**
-13.5*
-2.2
-6.0
-13.3
-16.4*
-8.8
-8.3
5.4
-18.6**
-15.7**
-0.3
2.8
5.7
3.8
-9.5
-18.4**
-10.3*
-18.6***
Note: Comparison with Intact Families. * 0.01<P<0.05, **
0.001 <P<0.01 *** P<0.001
In contrast, sizable negative effects of a reconstituted family
remained after controlling for
both soeioeconomic background and material resources
indicating that economic factors
play a smaller role in the weaker performance of students from
reconstituted families. One
possibility is that their weaker performance is due to the often
problematic relationships
between stepchildren and stepparents.

Countries that show stronger (or weaker) effects for family type
are not the same countries
that show stronger (or weaker) effects for family size. For
example, Finland, Norway and
Sweden show stronger effects of family type but relatively weak
effects for family size. The
countries that show weak effects for family type — Brazil, the
Czech Republic, Greece,
Poland, Portugal and Russia — are different from the countries
that show weak effects for
family size, namely Canada, Denmark, Finland, Iceland, Japan
and Korea. The effect of family
size was strongest in Portugal and fairly strong in Brazil and
Mexico. So it is not the case that
the detrimental effects of larger families are stronger in more-
economically developed
countries. The more-economically developed countries tend to
show weaker effects for
family size, although there are notable exceptions such as
Belgium, Italy and the United
States. More economically developed countries tend to show
stronger effects for family
type supporting Schiller et al.'s (2002) argument that the
benefits of living in an intact family
tend to be stronger in more-economically developed economies.
These analyses do mot
support the contention that effects of family type are weakest in
countries with larger welfare
sectors: Belgium, Finland, Norway and Sweden show relatively
strong effects of family type.

REFERENCES
Amato, P. R.
2000 "The Consequences of Divorce for Adults and Chitdren."
Joumat of Marriage and the
Famity 62(November): 1269-1287.
Biblarz, T. J. and Raferty, A.
1999 "Famity Structure, Educationat Attainment and
Socioeconomic Success: Rethinking the
"Pathology of Matriarchy"." American Joumat of Sociology
105(2): 321-365.
Btake,J.
1989 Famity Size and Achievement Califomia: University of
Califomia Press.
Comber, L. C. and Keeves, J. P.
1973 Science Education in Nineteen Countries: Intemational
Studies in Evatuation I.: Intemationat
Association for the Evatuation of Educationat Achievement.
Downey, D. B.
1995a "Understanding Academic Achievement among Children
in Stephousehotds: The Role of
Parental Resources, Sex of Stepparent, and Sex of Chitd."
Sociat Forces 73(3): 875-894.
1995b "When bigger is not better: Family size, parental
resources, and children's, educational
performance." American Sociotogicat Review 60: 747-761.

2001 "Number of Siblings and Intettectuat Development: The
Resource Dilution Explanation."
American Psychologist 56(6-7): 497-504.
Finn, J. D. and Owings, M. F.
1994 "Famity Structure and School Performance in Eighth
Grade." Joumat of Research and
Devetopment in Education 27(3): 176-187.
Ganzeboom, H. B. and Treiman, D. J.
1996 "Internationally Comparable Measures of Occupationat
Status for the 1988 Intemationat
Standard Classifications of Occupations." Sociat Science
Research 25:201-239.
Jeynes, W.
2002 Divorce, Famity Structure, and the Academic Success of
Children New York: the Haworth
Press: The Haworth Press.
Jeynes, W.H.
1999 "Effects of remarriage fottowing divorce on the academic
achievement of chitdren." Joumat
of Youth &Adotescence 28(3): 385-393.
Le, A. T. and Mitler, R
2001 'Educational Attainment In Australia: A Cohort Analysis.'

Longitudinal Surveys of
Australian Youth Research Reports no. 25, Melbourne:
Austratian Council for Educationat
Research
Mare, R. D. and Chen, M. D.
1986 "Further Evidence on Sibstiip Size and Educational
Stratification." American Sociological
Review 51(3): 403-412.
OECD
1999 Classifying Educational Programmes. Manual for ISCED-
97 Implementation in OECD
Countries. Paris: Organisation for Economic Co-operation and
Development.
2001 Knowledge and Skills for Life. First Results from the
OECD Programme for Intemational
Student Assessment. Paris: Organisation for Economic Co-
operation and Development.
2002a PISA 2000 Technical Report. Paris: Organisation for
Economic Co-operation and
Development.
2002b Reading for Change. Performance and Engagement across
Countries. Results from PISA
2000 Paris: Organisation for Economic Co-operation and
Development.
Pong, S.-L.
1997 "Family Structure, Schoot Context, and Eight Grade Math
and Reading Achievement."

Journal of Marriage and the Family 59(3): 734-746.
Pong, S.-l.
1998 "The school compositional effect of single-parenthood on
tOth-grade achievement."
Sociotogy of Education 71 (Jan): 23-42.
Pong, S.-L., Dronkers, J. and Hampden-Thompson, G.
2003 "Famity Policies and Children's School Achievement in
Single- versus Two-Parent
Families." Journal of Marriage and Family 65(3): 681 -699.
Post, D. and Pong, S.-l.
1998 "The Waning Effect of Sibship Composition on Schoot
Attainment in Hong Kong."
Comparative Education Review 42(2): 99-117.
Powell, M. A. and Parcel, T. L.
1999 Parental Work, Family Size and Social Capital Effects on
Earty Adolescent Educational
Outcomes: The United States and Britain Compared. Pp. 1-30 in
T. L. Parcel (ed) Research
in the Sociology of Work, Vol. 7.
Riala, K., Isohanni, I., Jokelainen, J., Jones, P B. and Isohanni,
M.
2003 "The relationship between childhood famity background
and educational performance,
with special reference to singte-parent families: A longitudinal
study." Sociat Psychology
of Education 6(4): 349-365.

Schilter, K., Khmelkov, V. T. and Wang, X.-Q.
2002 "Economic Development and Effects of Family
Characteristics on Mathematics
Achievement." Journal of Marriage and the Family 64(August):
730-742.
Shavit, Y. and Pierce, J. L.
1991 "Sibship Size and Educational Attainment in Nuclear and
Extended Families: Arabs and
Jews in Israel." American Sociological Review 56(June): 321-
330.
Thomson, E,, Hanson, T. L. and McLanahan, S. S.
1994 "Family Structure and Child Weil-Being: Economic
Resources vs. Parent Socialization "
Sociat Forces 73(1): 221-242.
Thomdike, R. L. • o j i/ i m
1973 Reading Comprehension Education in Fifteen Countries.
An Empmcat Study. Vol. Ill
New York: John Witey & Sons.

HUDE 200
Fall 2015
Introduction to Research
Guidelines for Article Analysis Assignment
Directions: Read and write an analysis of an empirical article on
your research topic. This article should be as close as possible
to your research topic of interest.
The article analysis should be NO MORE than 3 pages in
length, typed double-spaced, 12-point font, with 1-inch margins.
The purpose of the article analysis is to summarize the main
points of the article and evaluate the quality of the report. Be
sure to utilize a scientific research article – an article in a
journal that reports the results of an original study, and has
introduction, method, results and discussion sections. Consider
the questions below in your analysis of each section of the
article.
The assignment is DUE: 10/2/15, 11:59PM, and should be
submitted to Blackboard only, do not turn in a hard copy.
Below are key points to address in your analysis of each section
of the research article, but also include additional points of
analysis that you deem appropriate.
Reference
Provide the complete citation for the article, in proper APA
format.
Introduction
1. Does the introduction provide a strong rationale for why the
study is needed?
2. Are the research questions and hypotheses clearly
articulated? What is the research question(s)?
3. Is the review of the literature clear, comprehensive,

organized, and relevant to the research questions and purpose of
study?
Method
1. Is the method described in enough detail that replication is
possible without further information?
2. Subjects/Participants
a.) Are subject/participant recruitment and selection methods
described?
b.) What sampling technique was used and is it appropriate in
terms of the population to which the researcher wished to
generalize?
c.) Are characteristics of the sample described adequately?
3. Design
a.) What type of research design was utilized in the study? (e.g.,
survey, quasi-experimental)
b.) If appropriate, was a control group used?
c.) If an experimental study, were subjects randomly assigned to
groups?
4. Variables and Measures
a.) What variables were measured in the study?
b.) Do the measures match the research questions being
addressed?
Results
1. Does the results section contain a clear and logical summary
of the findings (could you understand it?)?
2. Does the results section include the results of all (statistical)
analyses?
3. Were tests of significance used and reported appropriately?
4. Do the authors report means and standard deviations (if

relevant) so that the reader can examine whether statistical
significant differences are large enough to be meaningful?
5. For a qualitative study, is enough evidence provided? Do the
authors present themes from the data?
6. Is the researcher sufficiently objective in reporting the
results?
Discussion
1. Does the discussion section offer interpretations for all of the
important results?
2. Do the authors consider alternative explanations for the
findings?
3. Do the authors discuss which hypotheses were supported?
4. Do the authors make appropriate generalizations about the
findings? Do the authors include limitations of the study?
Adapted from Cone & Foster (1993) Dissertations and theses
from start to finish

Criminology Essay Questions: Family Size, Type & Student Achievement

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