THREE-GENERATION MODELS
FOR THE TRANSMISSION OF CREDENTIALS
IN THE NETHERLANDS
Wout Ultee
Maarten Wolbers
Jochem Tolsma
Radboud University Nijmegen
The Netherlands
Unfinished version, May 2012
Paper for the meeting of the Research Committee on Social Stratification and Mobility of
the International Sociological Association (RC28) held May 10-13, 2012 in Hong Kong
at the Chinese University of Hong Kong.
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The Netherlands: less and less a class society, more and more a credential society?
In 1979 a book appeared with a profound impact on the field of societal stratification, and
a year later two books came out with the same effect. The most influential of them, at
least as far as research goes, was Goldthorpe’s Class structure and social mobility in
modern Britain from 1980. Goldthorpe’s book looked back from 1972, the year the
book’s data were collected, on Britain since World War II. So, it dealt with a Goin’ back
question, and the upshot of its findings was that Britain remained a class society, as
indicated by a strong link between father’s and son’s class. A person’s class was coded in
a specially designed schema, with classes partially ordered from higher to lower.
The second prominent book from 1980 was Collins’ The credential society. While
Goldthorpe looked back, Collins asked What’s it gonna be? Collins framed questions in
terms of a new dimension of stratification coming to full bloom in societies like the
United States: the credentials of people who for a shorter or longer period in their lives
attended school, with better jobs going to those with higher credentials.
Goldthorpe found no trend towards more relative father-son class mobility in
Britain. This finding occasioned a growth industry in the field of societal stratification:
ascertaining for other technologically highly developed societies the extent of father-son
class mobility, in contrast to movement along a metric for occupational prestige (Erikson
& Goldthorpe 1992). The main finding, pertaining to longer a time span than the one
covered by Goldthorpe’s data and to post-1972 decades, is that several European nations,
including the Netherlands, witnessed an increase in social fluidity (Breen 2004).
However, it should be added that no sociologist predicts the year in which societies will
have become completely fluid. It is taken for granted that at least some class stability will
remain, and, indeed, the effect of father’s class on son’s class remains quite potent.
The various interpretations of the finding of more class mobility highlight the
import of educational credentials for class destination. Yet, if the link between father’s
class and son’s education weakens, and the bond between son’s education and class
tightens, no prediction is obtained on the total strength of the relation between father’s
class and son’s class. Indeed, the factors messing up the link between a person’s
education and class include short term fluctuations in a country’s unemployment rate, as
well as technologically driven long term changes in its occupational structure.
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Following up on the theme of the credential society, it has been found for eight
European countries that the link between class origins and educational attainment
decreased (Breen, Luijkx, Müller & Pollak 2009). However, if education is as important
as Collins maintains, it becomes paramount not only the explain a son’s level of
education by class origin (Breen, Luijkx, Müller & Pollak take for five countries parental
education as a control), but to give priority to the study of the link between father’s
education and son’s education. This link, the total effect of father’s on son’s education is
interesting on its own. So, do technologically highly developed and longstanding
democratic nations witness a shift from class societies towards credential societies?
Cultural reproduction, the homogamy hypothesis and the grandparents hypothesis
If the characterization of the future of contemporary technologically highly developed
societies as credential societies is apt, the paramount questions are about father-son
educational mobility and stability. These questions should, at least nowadays, be
expanded into questions about mother-son educational mobility, as well as questions
about mother-daughter and mother-son educational mobility. Such an extension is indeed
possible, since women in general do have credentials, whereas the extent to which they
have a job (and a class position all their own) still varies from society to society.
We do not expect that trends in these other kinds of educational mobility are the
same as those in father-son educational mobility. The introduction of stipends will have
had different effects for men and women. Before state ran stipend programs, only sons of
highly educated fathers attended university. The impact of stipends on the children of
highly educated fathers will have been that their daughters now went on to university too.
The impact of stipends on the children of lowly educated fathers will have been quite
different: at first solely their sons will have opted for university, and only later their
daughters. So, upon the arrival of stipends, differences in the level of education attained
by sons, will have narrowed between the lower and upper echelons of a society; whereas
differences in the level of education attained by daughters will have increased between a
society’s upper and lower strata. It may be expected too that a mother’s level of education
is more influential on that of her daughters, and a father’s level of education on that of his
sons. But that is a subsidiary hypothesis.
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One of the prime, but in the field of societal stratification often overlooked,
changes in technologically advanced societies since World War 2 has been the increase in
the life span of their inhabitants. This delays the transfer of wealth to later generations.
Other things remaining equal (which they do not), transmission in the higher echelons of
is postponed. In addition, because of the introduction of all kinds of stipends for lower
class persons when pursuing credentials, parents from higher social classes will not be
able to maintain their children at this level to the same extent as before stipend schemes.
So, despite the finding that intergenerational class mobility is on the rise, the question
remains why there still is a non-negligible relation between origin and destination in most
technologically advanced societies.
Here Bourdieu’s La Distinction from 1979 becomes pertinent. It may be taken as
addressing the question of why a strong relationship obtains between the education of
parents and the education of their children, the question as the core of the theme of the
credential society. The marxist explanation for limited class mobility invokes the
inheritance of capital by children upon the death of their parents and payment of parents
for the education of their children. Bourdieu added to this hypothesis on the transfer of
material resources, hypotheses on the transmission of cultural resources. According to
one of them, a lower yield of material resources is compensated by a higher yield of
cultural resources. This thesis filled the gap left by longstanding marxist theories that do
not address the surprisingly small effects of stipends for children from lower origins.
Less often perceived was the gap in marxist theories created by the general
increase in life span: if parents live longer, children will receive their due share of the
patrimony later in life. However, the idea of cultural capital fills this gap. If parents are
less likely to die before a child reaches maturity, more cultural resources will be
transferred. And, since a person’s grandparents live longer too and grandparents spend
time with their grandchildren especially after retiring from the labor force because of the
pension systems in technologically advanced societies, more cultural resources will be
transferred from grandparents to grandchildren. So, in a full-fledged credential society, a
person’s level of education will not only depend upon the level of education of her or his
parents, but also upon the level of education of her or his grandparents.
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The present paper focuses on the extent to which the contemporary Netherlands is
credentialist, in the sense of educational transmission. It does so by studying not only
father-son, but also father-daughter, mother-son and mother-daughter educational
mobility. It deals too with criticisms of the idea of cultural resources. Following Halsey,
Heath & Ridge (1980), whatever cultural resources are, children acquire more of them if
their parents have a higher level of education, this paper does so by bringing in the
education of grandparents: children acquire more cultural resources if their grandparents,
in addition to their parents, have a higher level of education..
Mare (2011) pleads pleads for three-generation studies in the field of societal
stratification. He accepts that in the large middle ground of a society’s social scale, only
parental background is important, but maintains that at the top and bottom of the social
scale grandparents might be influential too. For the bottom of the scale, Mare was
invoking the persistent effects of race in the USA after the abolition of slavery 150 years
ago, and for its top, the prospects offered by the genealogies available for China, the
agrarian state with the longest uninterrupted existence in the history of human societies.
Mare’s ideas predict an interaction effect of parental and grandparental education
on third generation credentials: the combined effect of the two factors is stronger than
that of each one taken on its own. We hold that direct effects of grandparents occur in all
technologically advanced because of the lengthening of the life span and retirement
schemes for the elderly. We leave the direction of the interaction effect open, but point
out that in the Netherlands, when explaining a child’s education, mother’s high level of
education compensates for father’s limited education (De Graaf & Kraaykamp 2001).
The first criticisms of Bourdieu’s idea of cultural resources took that notion as a
conspiracy theory: how on earth could schools keep certain types of children out? The
later, more attractive, reading of Bourdieu postulated higher-class parents pursuing the
interest of their children by rearranging their own resources, investing less of their wealth
in obtaining credentials because its yield had been lowered by stipends, and investing
more of their time in the transfer of cultural resources, because parents of lower origin,
after the introduction of stipends, still do not have them. Our hypotheses about the latter
transfer invoke unintended consequences of the lengthening of the life span in
technologically advanced societies, particularly for persons part of their upper strata.
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Bourdieu’s books are rightly infamous for their unclear prose. The term ‘the
theory of cultural reproduction’ seems to be shorthand for the hypothesis that father’s
high social origin occasions his son to have a higher social destination, because fathers
transfer cultural resources to their sons. More precisely, before the introduction of a
stipends system in a country, fathers transmitted material resources to their children, but
as the yield of these remittances declined, fathers compensated by transmitting more
cultural resources. Our reading of Bourdieu’s 1979 book, begins with the recognition that
the question it addresses is more sophisticated than the question raised by Boudon in his
1974 book.
Both French sociologists agreed that social mobility, until then, had not increased
in the various European countries. For Boudon this was a puzzle because of educational
expansion: how is it possible that educational expansion did not lead to more upward
mobility? His short answer was that precisely because education was expanding so much
(not only among persons of lower class origins, but also among them of upper class
origins), social mobility remained largely unchanged. Bourdieu accepted that education
had been expanding, but pressed the question further. Educational growth was occasioned
by the introduction in most technologically advanced societies of stipends paid to
students of lower class origins out off general taxes. Of course, stipends were there too
for children of upper class origins. But material resources were not decisive in obtaining
a credential, cultural resources were so, and in this respect the upper strata of
technologically advanced societies still had the upper hand. We here claim that with the
lengthening of the life span, in a society’s upper strata more cultural resources are being
transmitted, not only from parents to children, but also to them from their grandparents.
Yet is should be clear that according to Bourdieu other mechanisms are involved
in the reproduction of inequalities from generation to generation. To paraphrase
Bourdieu’s terminological fog, apart from the reproduction of inequalities, there is the
reconstitution of inequalities. It is not fathers who have sons, men marry first, and then
their wife bears children. If marriage follows the principle of panmixia, inequalities may
be transmitted from fathers to their children and from mothers to their children, but all
children then wind up with the same amount of material and cultural resources.
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Since panmixia is obviously not the case, the extent to which educational
homogamy prevails in a society, becomes a prime topic when studying the reproduction
of inequalities form generation to generation. Indeed, Bourdieu studied educational
homogamy. An interesting follow-up question therefore is to what extent any total effect
of grandparental education upon child’s education is mediated not only be the level of
education of the child’s father, but also by the education of the child’s mother, with the
effect of grandparental education on the education of the wife of the father, being part of
the indirect effect of grandparental education on child’s education.
Against common criticism of Bourdieu’s opus, we point out that the transmission
of cultural resources need not be restricted to such items as historical knowledge, art and
languages. Common sense and casual observation suggest that mathematics and science
may be transmitted in this way too. When departing on holiday in the family car, the
driver may assign a child the task of computing the number of hours before the next gas
stop. Giving children money to but clothes helps too. Shared experiments with a
chemistry box might affect education, as well as having children repair the flat tire of
their bicycle themselves. These forms of informal learning need not be restricted to ties
with parents, mingling with grandparents might have such effects too.
Data
In this paper we analyse data from five strongly similar surveys, the Netherlands Family
Surveys conducted in 1992, 1998, 2000, 2003 and 2009 (Ultee and Ganzeboom 1992, De
Graaf et al 1998, 2000, 2003, and Kraaykamp et al. 2009). Each survey involves a new
random sample of primary respondents from all adult Dutch inhabitants in the survey
year. The number of primary respondents, interviewed face-to-face, each time was
around 1,000. We speak of primary respondents, since we also interviewed their present
partner (whether married or common law). We sent a mail questionnaire too to a parent
of the primary respondent (if one were still alive) and to a child (if one were above the
age of 25). The surveys ascertained for primary respondents and partners full educational
and occupational histories. Each person was asked after the education and occupation of
their father and mother, as well as the education and occupation of all of their children.
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In the simple tables and the statistical models to be presented, the parents (second
generation) are our primary respondents and their partner, the grandparents (first
generation) are the parents of the primary respondents and their partners, and the persons
whose level of education is being explained (third generation) are the children of our
primary respondents and their partner. Since we interviewed both primary respondents as
well as their partner about their mother and father, we are able to estimate statistical
models including all four grandparents. And since primary respondents and their partner
may have more than one child having finished school, primary respondents may feature
more than one time in the dataset to be modelled. They appear as often as they have
grown-up children. For that reason, we estimated in SPSS clustered standard errors. All
in all we the tables and models refer to 2,400 cases. Of these 1,253 are men and 1,147
women. The oldest birth cohort refers to 1940-1969 and comprises 1,208 cases, the
youngest to 1970-1984 and 1,192 cases. We deleted cases with at least one missing value.
Our educational classification consisted of six levels: elementary education (lo),
lower secondary education (lbo/mavo), higher secondary vocational education (mbo),
higher secondary general education (havo/vwo), lower tertiary education (hbo) and
higher tertiary education (wo). In the models, the standard number of years for obtaining
a person’s degree is explained by the standard number of years studied by their parents
and by their grandparents.
Featherman & Kelley (1974) have pointed at the possibility of complicating
effects of measurement error when estimating three-generation models. Their argument is
that errors in the measure for second generation education, are picked up by the measure
for first generation education, leading to a misleading direct effect of first generation
education on third generation education. We here maintain that in our models, the
measure least tainted by error is that for second generation education, with the error in the
measures of first and third generation education being higher and more or less the same.
This is an advantage of the design we used. Whereas in the first three generation studies
(Mukherjee 1954) grown-ups report on the education of their parents and grandparents,
here the second generation reports on the first one and the third one. We think the idea of
measurement error in the second generation being picked up by an even more faulty
measure for the first generation, quite farfetched.
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If our samples had been large enough, we might have been able to replace in our
statistical models the level of education of the first generation as reported by the second
generation, by a measure reported by the first generation. In the same way, the measure
for the education of the third generation, as reported by the second generation, might
have been replaced by a measure for the third generation as reported by the third
generation. After all, we sent out mail questionnaires to parents and children of primary
respondents. As was to be expected, in most cases, if children replied, grandparents were
already dead, and if grandparents replied, children were not old enough yet. However, we
will report on correlations between double measures and on differences in averages.
Table 1 presents the average number of years of education for the first, second
and third generation. It does so for two cohorts and for or men and women. It also gives
the percent with tertiary education. The third generation, both males and females, is more
educated than the second generation, and the second generation more than the third
generation. In the cohort born between 1970 and 1984, the level of education is higher
than in the 1940-1969 cohort. In the later cohort fathers have more education than in the
earlier cohort, and the same goes for mothers. This pattern is visible too when comparing
the education of father’s father, father’s mother, mother’s father and mother’s mother.
Tabular analysis
In Table 2a we present a cross classification of the education in the third generation by
the education of the second generation. Education is dichotomized as no tertiary versus
tertiary education. Whether we take the second generation as mothers or as fathers, in
both cases the odds ratio is about five. If years of schooling for the second and third
generation are correlated, the coefficient turns out to be between 0.35 and 0.40.
According to Table 2b, the odds ratio for the association between second and third
generation education is higher (ten or more), and the correlation coefficient is higher too
(above 0.40). According to table 2c there is a bivariate association between education in
the third and the second generation. That association, whether indicated by odds ratio’s or
correlation coefficients, is lower than the comparable measures for first and second
generation associations and for second and third generation associations.
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The prime question is of course that of the association between education in the
first and third generation after holding constant the education in the second generation.
Table 3 answers this question. If the second generation, measured as father’s education or
as mother’s education, is low in education, then we find an odds ratio indicating that
more education in the third generation, net of education in the second generation, makes
for more education in the third generation. When focussing on father’s education, the
odds ratio is 2.1, when paying attention to mother’s education 1.6. In both cases
correlations between third and first generation education in years, after partialling out
second generation education, are significant. But if the second generation, whether
mother’s or father’s education is high, there is no trace of an association between
education in the first and third generation. The odds ratio’s turn out to be 1.1 and 1.0.
These findings deserve careful consideration. Whereas the line of thought
advocated by Mare predicts that the combined effect of parental and grandparental
education is stronger than that of each of these factors taken on their own, we find that at
least in the Netherlands in the second half of the 20th century, a grandparent with a high
level of education does not make a difference if the parental level of education is high.
Here we have an instance in which an association gets specified in Lazarsfeld’s terms.
Logistic regression models
In Table 4 we present the fit and logit parameters of various logistic regression models,
with the log odds of having tertiary education or not as the phenomenon to be predicted.
Since we are able to include not only father’s education and mother’s education, but also
the education of father’s father and father’s mother, as well as the education of mother’s
father and mother’s mother, we estimated no less than twelve models. We did so for all
third generation persons, but also separately for third generation men and third generation
women. And we did so separately for the 1940-1969 and the 1970-1984 birth cohort.
We first comment on the parameters for all persons from the third generation, all
men from it, and all women from it. In model with one predictor, father’s education,
father’s father’s education, mother’s education, mother’s father’s education and mother’s
mother’s education all have a significant effect, but not father’s mother’s education. In
none of the presented models with two predictors the factor referring to the third
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generation remains significant. This means that the total significant effect of the first
generation mainly consists of indirect effect, effect by way of effect of the second
generation. We estimated one model with four predictors, father’s education, father’s
father’s education, mother’s education and mother’s father’s education, and in this model
both father’s education and mother’s education have a significant effect. The three
generation hypothesis does not fare well.
We now comment on the models for the two cohorts. These models yield a quite
different picture. There are significant changes from cohort to cohort, the effect of
father’s education has declined, and that of mother’s education too. But the effect of
father’s father’s education has become significant. In one model with two predictors for
the 1970-1984 birth cohort, a second generation and a third generation predictor has
effects: education in the third generation is higher if father’s education is higher and, net
of that, if father’s father’s education is higher.
Linear regression models
Table 5 presents parameters of linear regression models. We take them as more finetuned than the logistic regression models. We do not comment as yet on models for men
and for women, and for the earlier and later birth cohort. Given the number of cases, the
power of the models is quite low.
For all third generation cases, in a model with two predictors, father’s education
and father’s father’s education have a significant, direct, effect on years of education in
the third generation. In a model with two additional predictors, mother’s education and
mother’s father’s education, no longer a direct effect of father’s father’s education is
found, but a direct effect of mother’s education. This suggests that the direct effect of
father’s father’s education ahs become indirect, and affects the third generation by way of
mother’s education. Here we see that the ‘reconstitution of inequalities’ in marriages
contributes to the ‘reproduction of inequalities’ in two ways. It does so by way of a direct
effect of mother’s education, but it also does so by way of an indirect effect of father’s
father’s education on mother’s education. That is, the extent to which a man (father)
makes a good match in terms of credential, not only is higher if his education higher, but
also and net of this, if the education of his father is higher.
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How much measurement error?
It will be generally agreed that proxy measures, report by a person on another person, are
more contaminated than measures of a person’s education by that person her- or himself.
In the models we estimated until now, we used proxy measures for education in the first
and in the third generation. Since we not only interviewed primary respondents and their
partner, but also avail of mail-questionnaires completed by a parent and a child of the
primary respondent, we are able to say something about differences between proxyscores and direct scores. To this effect, we made Table 6. Note that it refers to one of our
five surveys only. We have not yet matched all the follow-up files to the initial files. This
is not only a big job, but we also would like to gain an impression of possibilities and
difficulties first, that is before estimating models that in some way or other replace
proximate scores by direct scores.
Table 6 report on the average number of years of education of the three
generations, and on the percent having obtained a tertiary degree. Whereas parent report
about their children that 41% has a tertiary education, these children do so for 36 % only.
This difference is significant. We find one other significant difference: whereas 20 % of
the parents report that mother’s father had a tertiary education, according to that
grandparent this is 13 %. When considering differences in reported levels of education in
terms of years normally spent in school, we find one significant difference: a parent
report a higher level of education for het mother’s father than the mother’s father does
himself. We regard the correlations between the proxy and the direct measures in terms
of years of schooling as quite low, but we confess that we do not have a feel of what
might be expected here. In contrast, the similarity in the percent with a tertiary degree
seems quite high.
To be finished.
Conclusion
In the present paper we found for the Netherlands in the second part of the 20th century
no direct effect of the education of a person’s grandparents on the level of education of
that person, when taking into account father’s level of education and mother’s level of
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education. However, the association between grandfather’s education and this person’s
education is significant, suggesting that this total effect consists of indirect effects.
Our models indicated that at least for the Netherlands the total effect of the
education of a person’s grandfather may be one the rise. This increase is taking place
while the effect of mother’s and father’s education is going down.
One upshot of our models is that models for a child’s level of education that only
include father’s and father’s father’s education, may provide a distorted image of what is
going on: there may be no direct effect of the first generation on the third generation, but
an effect of the first generation on the female part of the second generation and an effect
of mother’s education on the third generation. This is an argument for more recursive
modelling.
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