European Sociological Review

doi:10.1093/esr/jcn018 24:527-542, 2008. First published 6 Mar 2008; Eur. Sociol. Rev.

Geert Driessen, Peter Sleegers and Frederik Smit The Transition from Primary to Secondary Education: Meritocracy and Ethnicity

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The Transition from Primaryto Secondary Education:Meritocracy and EthnicityGeert Driessen, Peter Sleegers and Frederik Smit

The aim of this study was to better understand the influence of pupil background

characteristics (e.g. gender, SES, ethnicity), various cognitive, and non-cognitive

competencies (e.g. school performance, study attitude) and a number of class and

school characteristics (e.g. socio-ethnic class composition, degree of urbanization) on

the transition of children from primary to secondary education in the Netherlands.

In the final grade of Dutch primary school, pupils are advised with regard to the type

of secondary education considered most appropriate for them. Recent data from the

national large-scale PRIMA cohort study, which includes more than 8,000 pupils and

500 classes, were used to examine differences in the levels of recommendation provided.

The results showed the phenomenon of over-recommending or, in other words, groups of

pupils receiving an educational recommendation, which is higher than justified by their

school performance, to no longer exist. Pupil achievement appeared to be the most

important factor for the explanation of the level of recommendation, which clearly

provides support for the meritocratic principle.

Introduction

The majority of West European countries has experi-enced a massive influx of non-western immigrantssince the middle of the previous century. A sharedcharacteristic of many of these immigrants is that they

have received little or no education and are oftenilliterate, which holds for guest workers in particular(Koopmans and Stratham, 2000; EUMC, 2004). Over

the years, it has become apparent that the educationalposition of the children of such immigrants leavesmuch to be desired (Gillborn and Mirza, 2000;

Schnepf, 2004; OECD, 2006). Despite the attempts ofpolicymakers to combat the educational disadvantageof these groups, relatively little progress can be

detected and one certainly cannot speak of substantialimprovements in their social position (Karsten, 2006;Driessen and Dekkers, 2007).

Viewed from a meritocratic perspective, this situa-

tion is problematic as the occupation of a particular

social position should be determined only by the

talents, capacities, and efforts of the individual (i.e.

his or her ‘merits’). Competencies should thus play a

critical role in the social positions of people and not

factors such as gender, origin, or ethnicity. Research

nevertheless shows that pupils coming from lower

social milieus, which frequently include the children of

non-western immigrants, must demonstrate substan-

tially more ‘merit’ than children coming from more

privileged milieus to acquire comparable starting

positions in society (Breen and Goldthorpe, 2001;

Goldthorpe and Jackson, 2006). Politicians and policy-

makers in most western countries frequently assert that

one can speak of increased meritocratization, but the

results of empirical research raise some major doubts

about these assertions. Research into factors that

European Sociological Review VOLUME 24 NUMBER 4 2008 527–542 527

DOI:10.1093/esr/jcn018, available online at www.esr.oxfordjournals.org

Online publication 6 March 2008

� The Author 2008. Published by Oxford University Press. All rights reserved.For permissions, please e-mail: journals.permissions@oxfordjournals.org

appear to influence the reduction of educationalinequality is, therefore, called for also to gain insightinto the mechanisms of intergenerational mobility.

In the present article, an important step in theschool careers of Dutch children, namely the transitionfrom primary to secondary school, was studied. Thetype of secondary education recommended by theprimary schools is of particular interest because thisrecommendation together with the final choice ofsecondary education determine the societal prospectsof the children to a large extent.

Within the framework of Dutch research on theestablishment of recommendations for secondaryeducation, the so-called phenomenon of ‘over-recommending’ for particularly minority children inthe Netherlands has been observed since the end of the1980s (Driessen, 1991). Given comparable achieve-ment, that is, minority children are actually givena higher educational recommendation than non-minority children. From a theoretical perspective,however, over-recommending represents a deviationfrom the meritocratic principle and thus constitutes aform of positive discrimination with alternativeexplanations nevertheless available for the deviation.In a broad interpretation of the meritocratic principle,both cognitive and non-cognitive competencies areused to determine educational recommendations. Thecharacterization of non-cognitive competencies may bequite broad, but various aspects of motivation andeffort are typically meant by the term ‘non-cognitivecompetencies’. In a narrow interpretation of themeritocratic principle, only cognitive competencies—that is, school test performance—are used to determineeducational recommendations (Tesser and Iedema,2001). According to the latter approach, the correla-tion between performance and educational recommen-dation should be 100 per cent (i.e. perfect). Accordingto the broad approach, this need not be the case asmotivation and effort (i.e. non-cognitive competencies)can also contribute either directly or indirectly toeducational recommendations and thus influence theassociation between cognitive competencies and educa-tional recommendations. And when the association ofcognitive (and possibly non-cognitive) competencieswith educational recommendations is not perfect,one can often speak of ‘over-recommending’. Theopposite of over-recommending, namely ‘under-recommending’, also exists. One can speak of under-recommending when lower types of educationare recommended than justified by the capacities ofthe pupil or pupils. In this context, over- and under-recommending always are relative phenomena and,therefore, depend on which group is taken as the norm

(Claassen and Mulder, 2003). It is nevertheless striking

that, in contrast to the phenomenon of under-

recommending and its consequences, the phenomenon

of over-recommending and its possible consequences

has received very little attention in the Netherlands

(Koeslag and Dronkers, 1994).When compared with the results of research

conducted on educational recommendations in the

1980s and 1990s, recent research shows substantial

decreases in the incidence of over-recommending for

minority pupils in the Netherlands (Claassen and

Mulder, 2003; Luyten and Bosker, 2004). In order to

determine the extent to which we can speak of a

change of trend, the most recent national data on the

educational advising of primary-school pupils were

analysed. In the present article, the results of these

analyses are described and thereby the state-of-the-art

with regard to the over-recommending of minority

pupils in the Netherlands and the question of

whether we can speak—or still speak—of such over-

recommending, i.e. positive discrimination.

The EducationalRecommendation

The Practice of Recommending

Dutch primary education (LO) is for 4- to 12-year-old

and consists of 8 grades. When the children are in the

final grade they are given a recommendation with

respect to the most suitable type of secondary

education. In the secondary education system today,

all pupils receive a basic secondary education during

the first year or two, which means a national common

core curriculum with only a difference in the level of

the subject matter. In actual practice, however, the

pupils are pre-sorted right from the beginning of

secondary school into separate tracks. With regard to

those tracks it is relevant to note that the Dutch

education structure has changed repeatedly during the

past decades; for purposes of clarity and comparability,

in this article we will use the old terms and

abbreviations for the different levels of secondary

education: individualized pre-vocational education

(IBO), pre-vocational education (VBO), junior general

secondary education (MAVO), senior general second-

ary education (HAVO), and pre-university education

(VWO). Depending on the level of secondary educa-

tion attended, pupils can progress to a middle-level

vocational or general education (MBO) or a higher

level education (HO: higher professional education or

university education) (MECS, 2005). On grounds of

528 DRIESSEN, SLEEGERS AND SMIT

efficiency, the current policy is intended to discouragethe stacking of educational programmes (e.g. MAVOfollowed by HAVO, HAVO followed by VWO).Because of the hierarchical nature of the Dutchschool system, therefore, it is crucial that the mostappropriate—in other words, highest—educationalrecommendation be provided for the transition fromprimary to secondary school at the end of primaryschool.

In practice, the recommendation includes threeelements, not only (i) cognitive competences (perfor-mance, test results), but also (ii) non-cognitive factorssuch as attitudes, motivation, and interests, and(iii) the teacher’s judgements with regard to thechild’s home situation (i.e. socio-ethnic milieu,which, e.g. forms the basis for the aspiration levelsset by the teacher). For admission to MAVO, HAVO,and VWO, i.e. the general, non-vocational types, pupilsmust be assessed to establish their suitability. Thecommonest method of assessment is for pupils to betested halfway through the final year of primary school,using tests developed centrally to gauge pupils’ level ofknowledge and understanding. The test employed forthis assessment by over 90 per cent of all primaryschools is the CITO (Central Institute of TestDevelopment) primary school leavers’ attainment test.

Under the auspices of the head of the school,primary schools advise parents as to the type ofsecondary education most suited to their child. Parentshave the right to choose a secondary school for theirchild, but the school decides whether or not to admitthe child. Secondary schools for MAVO, HAVO, andVWO may demand a minimum score on the CITOtest. To help schools and parents, CITO has con-structed standard tables in which the relation betweenspecific (ranges of) test scores and the recommenda-tion for the most suitable type of secondary school isindicated. In the case of IBO and VBO, schools are notobliged to consider in advance whether the child cancope with the course, but they may do so if they wish.

Various parties are thus involved in the formulationof an educational recommendation. The pupils them-selves have certain desires or preferences, just as theirparents. The teachers often weigh the level ofperformance against the socio-ethnic composition ofthe class during their formulation of recommendationsfor individual pupils. In addition, the admissionpolicies of secondary schools, the degree of communityurbanization (and related to this the availability ofschools and the socio-ethnic composition of theneighbourhood), and any agreements which havebeen made between school administrations withregard to the admission and distribution of pupils

within a region can all play a role. The advising of

pupils on the verge of entering secondary school is

thus a complicated process involving various forces,which can sometimes lead to undesired effects.

Information on decision processes of school directo-

rates is virtually absent, not only in the Netherlands

but also in other countries as well (West and Pennell,1998; Schnepf, 2002; Driessen, 2005).

Over-recommending, which is the central topic inthis study, has been associated with the ethnic minority

background of the child since the end of the 1980s. In

particular, Turkish and Moroccan pupils with the same

levels of performance as other pupils have been foundto be given a higher level of educational recommenda-

tion. In contrast to pupils advised in keeping with their

actual performance, over-recommended pupils start

with an immediate lag and over-recommending has,therefore, been placed in a negative light. According to

Tesser and Iedema (2001), such delays explain their

lower marks and higher rates of drop out fromsecondary school. Mulder (1993) nevertheless argues

that the less successful school careers of minority

pupils may be more a consequence of the selection of

an overly high type of secondary school than thereceipt of an overly high educational recommendation;

that is, an overly high type of secondary education may

be forced upon the pupil by parents who may certainly

have the pupil’s best interests in mind but do not havesufficient insight into what is needed for the pupil to

live up to such expectations (Van der Veen, 2001; Smit

et al., 2005). Many pupils who start out too high—thatis, higher than the educational recommendation

provided by the primary school—indeed end up

repeating a year. The choice of an overly high type

of secondary education can also lead to reducedmotivation and inferior performance. Van der Werf

and Kuyper (2004) have also observed in recent

research that schools are providing increasingly

higher recommendations—due in part to pressurefrom parents who apparently do not want their

children to end up in the lowest levels of secondary

education. Nevertheless, there are also signs that over-

recommending may not always turn out negatively.In hindsight, that is, over-recommending can be seen

to provide a clear challenge and stimulus for at least

some children to fulfil their ambitions or even surpassthese (Hustinx, 2002).

Explanations for Over-recommending

Alternative explanations for the ‘ethnic over-recommending’ observed within the Dutch situation

have been put forth. The explanations concern the levels

MERITOCRACY AND ETHNICITY 529

of the pupil, the class and the school, the broader context,

and the inter-relations between the different levels.

Pupil level

A frequently offered explanation for over-recommend-

ing is that teachers explicitly take the negative effects of

the children’s immigrant past into consideration.

Despite the poor Dutch language skills of some

pupils, for example, the teachers trust that the

intellectual capacities of the children are sufficient to

handle a higher type of secondary education. The

teachers thus allow educational potential to weigh

heavier than actual performance on a language test.

It is also conceivable that the teachers weigh such

non-cognitive aspects as motivation and effort heavier

in some cases as well. These pupils are thus given

the benefit of the doubt. It is also possible that teachers

are afraid of discriminating and, therefore, display

what can be considered politically correct behaviour.

There is, in fact, an increased mention of discrimina-

tion these days but then positive discrimination.

And within the framework of counteracting educa-

tional delays and particularly when the positive

discrimination has no negative effects for other

pupils, it may be relatively easy to accept (Driessen,

1991). Therefore, we expect that pupils from ethnic

minorities will receive a recommendation for second-

ary education that is higher than that of other groups

of pupils with the same cognitive and non-cognitive

competencies.

Class/school level

An alternative explanation for ethnic over-recommend-

ing concerns the cognitive composition of the class. It

is well-known that teacher judgements of individual

pupils can be influenced by the level of the other

children in the class or a so-called frog-pond effect

(Davis, 1966). Teachers thus, appear to rank order

their pupils for purposes of evaluation which means

that the slightly better children in a class with a

generally lower cognitive level will be more easily given

a higher recommendation than children showing

otherwise comparable performance, but in a class

with a generally higher cognitive level (Mulder

and Tesser, 1992; Brandsma and Doolaard, 1999).

The cognitive level of the class is associated, in turn,

with the social and ethnic composition of the pupil

population (Driessen, 2002). Minority children and

children from lower social-economic milieus perform

lower on average than native-Dutch children

and children from higher social-economic milieus.

To the extent that we can speak of a concentration

of minority children and/or children from a lowersocial-economic milieu within a single class, the levelof class performance will be lower and, as a directconsequence of the aforementioned frog-pond effect,over-recommending may be more likely to occur.From this, we thus expect that children in a class witha lower cognitive level will receive a recommendationfor secondary education that is higher than that ofpupils with similar cognitive and non-cognitivecompetencies in classes with a higher cognitive level.

Context level

Dronkers et al. (1998) found a higher incidence ofover-recommending in big cities even after variouspupil and school characteristics were taken intoconsideration. According to these authors, this can beattributed to the assertive lifestyle and competitiveclimate which characterize big cities and the pressurewhich these place on parents. Differences in advisingwith regard to secondary education choices can also betraced back to the small percentage of low educatednative-Dutch parents, the large percentage of minorityparents, and the predominance of non-denominationalschools in big cities. Following this line of reasoning,we expect that children in big cities will receive arecommendation for secondary education that ishigher than pupils with the same cognitive and non-cognitive competencies living in other parts of thecountry.

Recent Developments

While the aforementioned results suggest that ethnicover-recommending takes place in the Netherlands,the results of some more recent longitudinal analysesof educational advising in the Netherlands provide amore subtle picture. In fact, Claassen and Mulder(2003) report that the over-recommending observedin 1988 and 1992 reverted to under-recommending in2000. These results suggest a change of trend in theNetherlands. These recent findings also confirm resultsof research into educational advising in other WestEuropean countries such as Germany and Switzerlandwhere one can speak of to a certain extent comparablesecondary education system (Kristen, 2000; Schnepf,2002; Imdorf, 2003).1 Kristen (2000) found that Italianand Turkish children of guestworkers in Germany werereferred significantly more frequently than theirclassmates to the lowest form of secondary education,after the language and maths achievement of thechildren had been taken into account. In addition tothis negative ethnic effect at the level of the pupil,she also found a negative effect at the level of the

530 DRIESSEN, SLEEGERS AND SMIT

class: the more minority children in the class, the lowerthe educational recommendation. These results werenot confirmed, however, by another German researchconducted by Schnepf (2002) who used the maths,science, and reading tests from the Programme ofInternational Student Assessment (PISA) and theTrends in International Mathematics and ScienceStudy (TIMSS). Research by Imdorf (2003) hasshown under-recommending to also occur for thechildren of guestworkers in Switzerland, which also hasa tracked secondary education system. Given equalachievement, both boys and the children of guest-workers were generally referred to lower tracks thangirls and native-Swiss children, which indicates under-recommending.

One possible explanation for this reversal from over-to under-recommending in the Netherlands may lie inthe fact that big cities have made some proceduralagreements over the past few years to better attuneeducational recommendations to achievement (Tesserand Iedema, 2001). Some other factors may also be atwork, however. Lower levels of educational recom-mendation can also be expected to occur as teachersacquire greater experience with minority children andthus better insight into their capacities and prospects.The political climate has also changed considerably inthe Netherlands under the influence of the (highlycontroversial) politician Pim Fortuyn during the pastfew years and opened up public debate on topicswhich were previously taboo. In the discussion of amulti-cultural Dutch society, for example, the reserve,which was previously exercised with respect to theimposition of strict requirements and fears of beingaccused of discrimination have decreased markedly.Finally, it is also possible that schools are under greaterpressure to perform and, therefore, apply morestringent admission policies as a result of the market-ization of education and its accompanying develop-ments of accountability and competition (Teelkenet al., 2005).

In order to determine if the observed shift fromover-recommending to under-recommending in theNetherlands is still the case, the most recent nationaldata were analysed. In contrast to the analysesconducted previously, however, some new elementswere added to the present analyses. In addition tocognitive competencies, non-cognitive competenciesare now taken into account. In doing this, we haveadopted both a strict and a broad interpretation ofthe meritocratic principle. The focus of much of theresearch to date has been upon predominantlythe relations between pupil performance and educa-tional recommendation. In the present analyses,

the influences of various environmental factors

(e.g. the class, the school) are also taken into

consideration, therefore. New in this light is attention

to the cognitive level of the class as a whole. Relative to

previous studies, the content of the present study has

thus been broadened.

Methods

Samples

The data from the fifth measurement point for the

Dutch Primary Education (PRIMA) study from 2002

to 2003 were used for purposes of the present study.

PRIMA is a large-scale, national cohort study among

600 primary schools in the Netherlands (which is

almost 10 per cent of all Dutch primary schools).

The study includes 60,000 pupils from the Dutch

equivalent of kindergarten and grades 2, 4, and 6 with

sixth grade constituting the final year of primary

school in the Netherlands. Information on not only the

pupils but also parents, teachers, and school adminis-

trations has been included in the study. The total

PRIMA sample can be further subdivided into a

nationally representative sample of 420 primary

schools and a supplemental sample of 180 schools

with an over-representation of pupils from disadvan-

taged situations (Driessen et al., 2004; Van der Slik

et al., 2006). The first part of the present analyses

which was intended to gain insight into the distribu-

tions of the variables and bivariate associations

between the variables was conducted on the sixth

grade pupils from the representative sample. The

second part of the analyses which was intended

to get a better understanding of the multivariate

associations between the different variables was con-

ducted on the entire sample. The representative sample

used in the descriptive analyses contained 5,664 pupils

from 497 sixth grade classes. The total sample used in

the multivariate analyses contained 7,883 pupils from

519 sixth grade classes.

Measurement Instruments

The data were collected using different measurement

instruments. Background information on the pupils

and their parents was provided by the different school

administrations, and this information was then used

to calculate class averages. Different intelligence tests

and achievement tests were administered to the pupils.

The pupils were also asked to answer some

questions about the transition from primary to

MERITOCRACY AND ETHNICITY 531

secondary education. The schools reported the level of

educational recommendation provided for the pupils.

The teachers evaluated the pupils with regard to a

number of non-cognitive competencies. And informa-

tion on the background characteristics of the schools

was obtained from the databases of the Ministry of

Education.The final set of variables can be divided into four

blocks, namely cognitive competencies, non-cognitive

competencies, background characteristics of the pupils,

and background characteristics of the classes/schools.

In Tables 1 and 2, the different competencies and

characteristics are briefly described.The distributions for the pupil background char-

acteristics and the class/school background character-

istics within the representative sample are also

presented in Table 2.

Design of the Analyses

Analyses of variance were primarily used for the

descriptive analyses. To start with, the educational

recommendation was bivariately related to the various

cognitive and non-cognitive competencies. Thereafter,

educational recommendation and competencies were

analysed in relation to the characteristics of the pupils

and the characteristics of the classes/schools. Because

of the hierarchical nature of the Dutch school system

and the strong linear correlation between the pupils’

scores on ability tests such as the CITO primary school

leavers’ test and the recommendation for the most

suitable type of secondary school (see above), res-

earchers into Dutch school careers have always treated

educational recommendation as an interval variable

(Dronkers et al., 1998; Brandsma and Doolard, 1999).

Table 1 Operationalization of educational recommendation, cognitive competencies, and non-cognitivecompetencies

Educational recommendation Categories

Recommendation Categories: (1) IBO, (2) VBO, (3) MAVO,(4) HAVO, (5) VWO

Cognitive competencies Categories/scales

Intelligence Non-verbal intelligence test. Sum score for 34 itemsSchool career Categories: (1) delayed, (2) non-delayedLanguage performance Language test. Proficiency score based upon 64 itemsMaths performance Maths test. Proficiency score based upon 120 itemsReading performance Reading test. Proficiency score based upon 50 items

Non-cognitive competencies Categories/scalesEthnic breach (¼ linguistic—cultural

difference between the home andschool situations)a

Teacher judgement. Score based upon 3 items; for example:‘A language other than Dutch is spoken in this family’ (a¼ 0.89).Range: (1) definitely untrue – (5) definitely true

Home climate (¼ educationallysupportive home climate)a

Teacher judgement. Score based upon 4 items; for example:‘Learning and curiosity are encouraged in this family’ (a¼ 0.87).Range: (1) definitely untrue – (5) definitely true

Self-confidence Teacher judgement. Score based upon 3 items; for example:‘The pupil is anxious or afraid’ (a¼ 0.85). Range:(1) definitely untrue – (5) definitely true

Study attitude Teacher judgement. Score based upon 4 items; for example:‘Quickly thinks that he/she is done with work’ (a¼ 0.81).Range: (1) definitely untrue – (5) definitely true

Social behaviour Teacher judgement. Score based upon 4 items; for example:‘Is often cheeky’ (a¼ 0.83). Range: (1) definitely untrue –(5) definitely true

Addressable in Dutch Teacher judgement. Range: (1) very poor – (5) very goodEffort Pupil judgement. Score based upon 8 items; for example:

‘I work hard at school’ (a¼ 0.72). Range: (1) (almost)never – (4) (almost) always

aEthnic breach and home climate are not really non-cognitive pupil competencies but, rather circumstances. In connection with the readability

of the present text, they have nevertheless been subsumed under non-cognitive competencies.

532 DRIESSEN, SLEEGERS AND SMIT

We will follow this convention and treat recommenda-

tion, the dependent variable, as an interval variable.

Given the nested structure of the data, i.e. pupils

within classes, multi-level regression analyses were

conducted to analyse the multivariate associations

between the different variables (Rasbash et al., 2004).

More specifically, it was attempted to predict educa-

tional recommendation on the basis of the various

competencies and background characteristics.Given the large numbers of pupils and classes, the

usual levels of significance do not say much; associa-

tions may quickly reach significance but have little or

no relevance. For this reason, the emphasis in the

descriptive analyses was placed upon the strength of

the observed associations or the so-called eta coeffi-

cient. Cohen (1988) calls an association of 0.10 ‘weak’;

an association of 0.30 ‘medium’; and an association of

0.50 ‘strong.’ An eta of 0.15 (or 42 per cent explained

variance) is frequently taken to be the lower limit for

the relevance of an association (Bosker et al., 2001).

Results

Description of the Educational

Recommendations

In the upper part of Table 3, the percentages for the

different categories of educational recommendation are

shown. In the lower part of Table 3, the means and

standard deviations for educational recommendation

and a number of the cognitive and non-cognitivecompetencies are presented. The correlations (r) of thevarious competencies with educational recommenda-tion are also presented.

On average, the children studied here received amiddle-level (i.e. MAVO) educational recommenda-tion. More than 80 per cent of the pupils had a non-delayed school career; 20 per cent of the pupils hadstayed back a year or skipped a year on at least oneoccasion. One can speak of a moderately strongeducationally supportive home climate on average.The score for ethnic breach shows linguistic andcultural differences to only characterize the homeversus school environments to a limited extent. Onaverage, it was possible or very possible to address thepupils in Dutch. The amount of effort on the part ofthe pupils was generally judged to be good just as theirself-confidence and social behaviour; their studyattitudes were, according to the teachers, somewhatweaker. The final column in Table 3 shows moderateto strong associations between the various competen-cies and educational recommendation; cognitive com-petencies clearly correlated more strongly witheducational recommendation than non-cognitivecompetencies.

In the subsequent analyses, the associations betweeneducational recommendation, cognitive competencies,and non-cognitive competencies—on the one hand—and the background characteristics of the pupils,classes, and schools—on the other hand—wereexamined. Whether relevant differences (i.e. an

Table 2 Operationalization of pupil background characteristics and class/school background characteristics(with distributions for the representative sample presented in brackets)

Background characteristics of pupils Categories and distributions

Gender (1) boy (50%), (2) girl (50%)Parental education (1) LO (7%), (2) VBO (23%), (3) MBO (41%), (4) HO (29%)Ethnicity (1) native-Dutch (82%), (2) mixed native-Dutch and minority

(5%), (3) Surinamese and Antillean (2%), (4) Turkish [4%],(5) Moroccan (3%), (6) other ethnic background (4%)

Background characteristics of classes/schools Categories and distributionsPercentage native-Dutch disadvantaged

(¼low SES) pupils in the classMean¼ 18%; three categories used for the descriptive analyses:

(1) 0% (21%), (2) 1-24% (46%), (3)� 25% (33%).Percentage ethnic minority disadvantaged

pupils in the classMean¼ 13%; three categories used for the descriptive analyses:

(1) 0% (53%), (2) 1-24% (31%), (3)� 25% (16%).Cognitive level of the class (aggregated language

and maths scores; z-scores)Mean¼ 1.48; three categories used for the descriptive analyses:

(1) low (21%), (2) medium (36%), (3) high (43%).School denomination (1) Non-denominational [33%], (2) catholic [32%],

(3) protestant [28%], (4) other denomination [7%].Type of community (¼ degree of urbanization) (1) Four largest municipalities (Amsterdam, Rotterdam,

The Hague, Utrecht) (9%), (2) other large municipalities(11%), (3) modal (56%), (4) rural (24%).

MERITOCRACY AND ETHNICITY 533

eta� 0.15) occurred according to gender was first

examined. This generally appeared to not be the case:

The mean maths score for the boys was slightly higher

than that for the girls (120 versus 117; eta¼ 0.16); the

girls showed a slightly better study attitude than the

boys (3.6 versus 3.3; eta¼ 0.22); and the girls also

showed slightly more social behaviour than the boys

(3.8 versus 3.5; eta¼ 0.19).The differences with respect to the educa-

tional background of the parents are summarized in

Table 4.The results in the upper part of Table 4 confirm the

so-called reproduction thesis: 76 per cent of the

children of parents with only a primary education

(LO) and 70 per cent of the children of parents with

only a pre-vocational secondary education (VBO) were

found to receive a middle-level (MAVO) educational

recommendation at most; in contrast, 73 per cent of

the children of parents with a higher professional

or university education (HO) were given a relatively

high—if not the highest—level of educational recom-

mendation (HAVO or VWO) which places these

pupils—just as their parents before them—in a

position to pursue a higher level of post-secondary

education. In addition to this, there are moderately

strong to strong associations between the compe-

tencies of the pupils and parental level of education.

Table 3 Descriptive statistics for educationalrecommendation, cognitive competencies, andnon-cognitive competencies (percentages,means, standard deviations, and correlationswith educational recommendation)

Mean(%)

SD r�recommendation

RecommendationIBO (%) 6VBO (%) 17MAVO (%) 27HAVO (%) 26VWO (%) 25Average 3.5 1.2

Intelligence 26 4.2 0.43��

Non-delayed (%) 81 39.6 0.32��

Language performance 1,122 35.3 0.60��

Maths performance 118 8.9 0.73��

Reading performance 57 16.2 0.72��

Home climate 3.6 0.7 0.39��

Ethnic breach 1.7 0.9 �0.21��

Addressable in Dutch 4.5 0.5 0.29��

Effort 3.3 0.4 0.33��

Self-confidence 3.8 0.6 0.16��

Study attitude 3.4 0.7 0.37��

Social behaviour 3.7 0.6 0.17��

�P50.01, ��P50.001.

Table 4 Educational recommendation, cognitive competencies, and non-cognitive competencies accordingto parental level of education (means)

Parental level of educationLO VBO MBO HO Total eta

RecommendationIBO (%) 16 11 4 1 6 0.20��

VBO (%) 32 29 14 7 17 0.25��

MAVO (%) 28 30 31 20 27 0.11��

HAVO (%) 15 18 29 30 26 0.13��

VWO (%) 9 11 22 43 25 0.29��

Average 2.7 2.9 3.5 4.1 3.5 0.39��

Intelligence 25 25 27 28 26 0.22��

Non-delayed (%) 54 72 84 89 81 0.24��

Language performance 1,091 1,110 1,124 1,135 1,122 0.35��

Maths performance 113 115 118 122 118 0.32��

Reading performance 45 51 57 64 57 0.36��

Home climate 2.9 3.3 3.7 3.9 3.6 0.40��

Ethnic breach 3.5 1.9 1.6 1.5 1.7 0.56��

Addressable in Dutch 4.1 4.5 4.6 4.7 4.5 0.34��

Effort 3.3 3.3 3.3 3.4 3.3 0.10��

Self-confidence 3.8 3.8 3.8 3.8 3.8 0.04Study attitude 3.3 3.3 3.4 3.6 3.4 0.15��

Social behaviour 3.5 3.6 3.7 3.7 3.7 0.11��

�P50.01, ��P50.001.

534 DRIESSEN, SLEEGERS AND SMIT

The pupils varied very little with regard to such non-

cognitive capacities as effort, self-confidence, study

attitude, or social behaviour. It should be noted that

almost 50 per cent of the children of parents with only

a primary education (LO) had already experienced

educational delays while this was the case for only

about 10 per cent of the children of parents with a

higher education (HO).In Table 5, the results for educational recommenda-

tion and competencies according to ethnicity are

presented.2 Only those characteristics for which

relevant differences were detected are presented.The mixed category of ethnic background pupils

showed the highest level of educational recommenda-

tion while the Turkish and Moroccan categories clearly

showed the lowest. As expected, the differences in test

performance were most marked for language

performance.In addition to the above results, differences between

the pupils were also found to occur as a consequence

of differences in class (compositional or peer effects)

and school characteristics. With respect to the

percentage of native-Dutch disadvantaged pupils (i.e.

Dutch pupils with low SES-parents), only one difference

was found to be of relevance: pupils in classes with 0

per cent such children scored 2.1 for ethnic breach on

average; pupils in classes with 1–24 per cent such

children scored 1.6 for ethnic breach; and pupils in

classes with �25 per cent such children scored 1.7 for

ethnic breach (eta¼ 0.19).

With respect to the percentage of ethnic minority

disadvantaged pupils it appears that pupils in classes

with a greater percentage of such pupils produced

lower scores on average but then for language in

particular. In classes with 0 per cent of such minority

children, the language score was 1,126 on average; in

classes with 1–24 per cent of such children, the score

was 1,123; and in classes with �25 per cent of such

children, the score was 1,103 (eta¼ 0.22). For maths

and reading, the same dichotomy presented itself

(in both cases, eta¼ 0.16).In the analyses addressing the cognitive level of

the class, pupils in classes with a lower cognitive level

received a lower educational recommendation on

average than pupils in classes with a higher cognitive

level. This difference was particularly apparent for the

lowest and highest levels of educational recommenda-

tion (i.e. IBO and VWO, respectively). In addition,

those pupils in classes with the highest cognitive level

scored highest on all of the cognitive and non-

cognitive competencies; the maths, language, and

reading performance scores also all involved eta

coefficients of about 0.30. Once again, however, the

four non-cognitive competencies of effort, self-con-

fidence, study attitude, and social behaviour showed

no relevant differences.With respect to the denomination of the school, both

ethnic breach and addressable in Dutch pro-

duced relevant differences which were nevertheless

completely explained by the fact that the category

Table 5 Educational recommendation, cognitive competencies, and non-cognitive competencies accordingto ethnicity (means)

EthnicityNative-Dutch Mixed Surinamese/

AntilleanTurkish Moroccan Other ethnic

backgroundTotal eta

RecommendationIBO (%) 5 3 9 13 15 8 6 0.11��

VBO (%) 15 15 22 30 28 21 17 0.10��

MAVO (%) 27 25 37 28 32 24 27 0.04HAVO (%) 27 31 20 19 17 24 26 0.06��

VWO (%) 26 26 12 9 8 22 25 0.12��

Average 3.5 3.6 3.1 2.8 2.8 3.3 3.5 0.18��

Non-delayed (%) 84 80 71 62 54 62 81 0.20��

Language performance 1,126 1,125 1,105 1,085 1,095 1,109 1,122 0.29��

Maths performance 119 119 114 114 113 116 118 0.18��

Reading performance 58 59 49 45 47 53 57 0.22��

Home climate 3.7 3.5 3.1 3.0 2.8 3.2 3.6 0.34��

Ethnic breach 1.4 2.0 2.9 3.8 3.9 3.5 1.7 0.86��

Addressable in Dutch 4.6 4.5 4.3 3.9 4.1 4.3 4.5 0.42��

�P50.01, ��P50.001.

MERITOCRACY AND ETHNICITY 535

‘other denomination’ included Islamic schools inaddition to other denomination schools. These schoolsare only attended by minority children, often entailmajor discrepancies between the home and school

cultures and often involve pupils whose parents speakpoor Dutch.

With respect to the type of community (i.e. degree ofurbanization), only a few relevant differences appeared.The pupils in the four biggest cities in theNetherlands—namely Amsterdam, Rotterdam, TheHague, and Utrecht—clearly score lower on languagealthough the difference is almost completely due to thelow cognitive level of the class. Relevant differences forhome climate, ethnic breach, and addressable in Dutchwere also apparent, but clearly explained by the higherpercentages of minority disadvantaged pupils in the bigcities.

Explanation of the Educational

Recommendations

A description of the different bivariate relationsbetween the competencies and characteristics examinedin this study was presented in the preceding. In thissection, the results are reported of the multivariateanalyses conducted using the multi-level program

MLwiN (Rasbash et al., 2004). The entire PRIMAsample was used in these analyses, which entails anoverrepresentation of schools with numerous minorityand native-Dutch disadvantaged pupils. Given that ourprimary concern was to identify critical relations andnot draw representative statements, we judged the totalPRIMA sample to be most suitable. Use of this samplealso guarantees sufficient cell numbers for the relativelysmaller groups.

Two issues will be considered in the following. Thefirst is the phenomenon of over-recommending ofcertain groups of pupils relative to other groups withcomparable competencies. The second issue is the

relative influences of the different competencies andcharacteristics on recommendations for secondaryeducation. As already mentioned, three alternativegrounds for over-recommendation have been sug-gested: ethnicity, cognitive level of the class, and typeof community. In order to determine the extent ofover-recommending on each of these grounds andwhether one can thus speak of different forms of over-recommending or not, separate multi-level regressionanalyses were undertaken. First, a basic model contain-ing one of the different grounds (i.e. ethnicity, classlevel, or type of community) was tested. Next, themodels with cognitive competencies, non-cognitivecompetencies, and various background characteristics

added stepwise were consecutively tested. The results ofthese analyses showed non-cognitive competencies toprovide virtually no extra explanatory power. Non-cognitive competencies were, therefore, not included inthe definitive models. We will, however, return to thesecompetencies in our final analyses.

In Table 6, the most important results with respectto over-recommending in relation to ethnicity arepresented. The table shows the unstandardized regres-sion coefficients that indicate the number of changepoints for educational recommendation when thepredictor variables change by one point. For predictorswith a wide range of scores, these coefficients can bevery small. To create some uniformity for purposes ofpresentation, the scores for language, maths, reading,intelligence, and percentage disadvantaged pupils weredivided by 10, therefore. The results thus reflect achange of educational recommendation per 10 pointsof change in the predictor. More concretely: acoefficient of 0.05 for language means a 0.05-pointhigher educational recommendation in relation to a10-point higher language score. For the dichotomousvariables, the reference category is also always indi-cated. The parameters of a given model are comparedwith the parameters of the preceding model, andthe results are presented in Table 6. At the bottom ofthe table, the percentages of variance explained at thelevels of the class and the pupil are also reported alongwith the percentage changes when the variouscompetencies and characteristics are added stepwiseto the model.

In the first step in the multi-level analyses, the so-called empty model (model 0) was estimated. Thismodel shows 14.4 per cent of the explained variance ineducational recommendation to relate to differencesbetween the classes and the remaining 85.6 per cent torelate to differences between the pupils. When the herecentral variable of ethnicity is added to the model toproduce a new model (model 1), minority pupils arefound to receive a lower educational recommendationthan native-Dutch pupils on average. For theMoroccan and Turkish pupils, the difference is asmuch as 0.70 along a scale of 1.0–5.0 and strong,therefore. When school performance is added to theprevious model to create model 2, the low average levelof educational recommendation for the minoritychildren is now explained by the low school perfor-mance of the children. After control for schoolperformance, that is, the differences between theminority and native-Dutch pupils virtually disappear.In model 3, other pupil background characteristics areadded to the previous model. The testing of this modelshows some minor over-recommending to now occur

536 DRIESSEN, SLEEGERS AND SMIT

for Moroccan and other ethnic background pupils on

average. When the composition of the class in terms of

the percentage of minority disadvantaged pupils and

percentage of native-Dutch disadvantaged pupils is

added to the previous model to create model 4, the

extra explanatory power of the two characteristics

(0.3 per cent) is virtually zero. This final model shows

the category of other ethnic background to continue to

make a difference although the effect does not amount

to much (i.e. is less than one-sixth of a standard

deviation). Over-recommending is also found to occur

for more intelligent pupils and the children of highly

educated parents while under-recommending occurs

for pupils with delayed school careers and boys. Once

again, however, the effects are very small.Comparable analyses were next conducted with

regard to over-recommending, but then with either

the cognitive level of the class or the type of

community added first to the model. Given the

strong resemblance of the results to the results for

ethnicity, we limit ourselves to the core of the analyses

here. With respect to the cognitive level of the class,

it was found that classes with a high cognitive level

received a higher level of educational recommendation

on average (coefficient of 1.00). This is related to the

higher school performance of the pupils in these

classes. After control for school performance, in fact,

one can actually speak of under-recommending in the

classes with a high cognitive level; pupils in high

achieving classes appear to be evaluated more strin-

gently. With regard to type of community, the four

largest and other large communities were given a

slightly lower educational recommendation on average

than smaller communities (coefficients of �0.39 and

�0.48, respectively). This is due to the lower school

performance of the pupils in the four largest and

other large communities: when school performance

is controlled for, the differences between the types

Table 6 Results of multi-level analyses over-recommending to ethnicity (unstandardized regressioncoefficients)

Model0 1 2 3 4

Regression coefficientsIntercept 3.3��

Ethnicity (reference ¼ native-Dutch):Mixed 0.00 0.05 0.06 0.05Surinamese/Antillean �0.50�� 0.09 0.11 0.09Turkish �0.66�� 0.00 0.10� 0.07Moroccan �0.70�� �0.03 0.12�� 0.09Other ethnic background �0.19�� 0.13�� 0.21�� 0.19��

Language performance 0.05�� 0.05�� 0.05��

Maths performance 0.66�� 0.63�� 0.63��

Reading performance 0.25�� 0.23�� 0.23��

Intelligence 0.08�� 0.08��

School career (reference¼ non-delayed) �0.21�� �0.21��

Gender (reference¼ girl) �0.09�� �0.09��

Parental education 0.10�� 0.10��

Native-Dutch disadvantaged pupils (%) �0.03��

Minority disadvantaged pupils (%) 0.01

Explained variances (%)Class level 14.4 29.6 58.8 60.3 62.1Pupils level 85.6 1.5 70.4 71.6 71.6Total 5.5 68.7 70.0 70.2þ Class level 29.2 1.5 1.8þ Pupils level 68.9 1.2 0.0þ Total 63.2 1.3 0.3

Model fit 25,028.9 24,794.8 15,555.2 15,226.4 15,208.2Improvement 46.8 3079.9 82.2 9.1Difference df 5 3 4 2

�P50.01, ��P50.001.

MERITOCRACY AND ETHNICITY 537

of communities with regard to level of educational

recommendation disappear. Neither over- nor under-

recommending are further found to occur in relation

to the background characteristics of the pupils or the

composition of the class.The focus of the preceding analyses was on the

phenomenon of over-recommending while a few

specific instances of under-recommending were also

examined. In the following, the relative weights of the

different categories of predictors of educational

recommendation will be considered in greater detail.

In doing this, the extent to which educational

recommendation can be predicted on the basis of

‘merits’ (e.g. talent, competencies, and effort) will be

examined along with the extent to which other factors

which do not relate directly to school performance

contribute to the variance in educational recommen-

dation. In such a manner, insight can be gained into

the degree to which one can speak of a meritocratic

system of education in the Netherlands. In an effort to

attain the most parsimonious models, the analyses

were again conducted in a number of steps.3 The final

results of the analyses are presented in Table 7.The three school performance measures were

entered first to create model 1 and all proved sig-

nificant. More than two-thirds (68.6 per cent) of the

variance in educational recommendation was predicted

by these three measures. In model 2, the other two

cognitive competencies were added. Given equal school

performance, those children who were more intelligent

Table 7 Results of the multi-level analyses of the relation between educational recommendation andcognitive competencies, background characteristics, and non-cognitive competencies [unstandardized andalso in model 4 (standardized) regression coefficients]

Model0 1 2 3 4

Regression coefficientsIntercept 3.3��

Language performance 0.05�� 0.05�� 0.05�� 0.04�� (0.13)Maths performance 0.66�� 0.62�� 0.63�� 0.58�� (0.43)Reading performance 0.25�� 0.24�� 0.23�� 0.21�� (0.27)Intelligence 0.11�� 0.08�� 0.07�� (0.03)School career (reference¼ non-delayed) �0.22�� �0.21�� �0.18�� (�0.06)Gender (reference¼ girl) �0.09�� �0.04� (�0.02)Parental education 0.10�� 0.08�� (0.06)Ethnicity (reference¼ native-Dutch):

Mixed 0.06 0.09� (0.02)Surinamese/Antillean 0.11 0.15�� (0.02)Turkish 0.10� 0.17�� (0.04)Moroccan 0.12�� 0.18�� (0.04)Other ethnic background 0.21�� 0.25�� (0.05)

Home climate 0.11�� (0.06)Addressable in Dutch 0.12�� (0.05)Effort 0.20�� (0.06)Self-confidence 0.04�� (0.02)Study attitude 0.10�� (0.06)Social behaviour �0.05�� (�0.03)

Explained variances (%)Class level 14.4 58.6 59.6 60.3 61.8Pupil level 85.6 70.3 71.0 71.6 73.1Total 68.6 69.4 70.0 71.5þ Class level 1.0 0.7 1.5þ Pupil level 0.7 0.6 1.5þ Total 0.8 0.6 1.5

Model fit 25,028.9 15,579.2 15,403.1 15,226.4 14,821.1Improvement 3149.9 88.1 25.2 67.6Difference df 3 2 7 6

�P50.01, ��P50.001.

538 DRIESSEN, SLEEGERS AND SMIT

and those pupils with a normal, non-delayed school

career were found to receive relatively higher educa-

tional recommendations. In model 3, various pupil

background characteristics were added. Given equal

school performance, intelligence, and school careers, it

was found that girls, children of highly educated

parents and minority children—including primarily

those with a Moroccan or other minority back-

ground—received a relatively higher educational

recommendation on average. These results suggest

that over-recommendation for some groups of ethnic

minority pupils (Moroccan, Turkish, and other

minority pupils) still takes place, although the effects

are very small. Finally, in model 4, the significant non-

cognitive competencies of the pupils were included.

Comparison of models 3 and 4 show these character-

istics to add virtually nothing to the model: pupils

from higher social milieus, pupils who are more

addressable in Dutch, pupils who show greater effort,

have better self-confidence, have a better study

attitude, and display less socially acceptable behaviour

are given a slightly higher educational recommendation

when compared with the other pupils. These results

show that also the non-cognitive competencies (moti-

vation, attitudes, and interests) of pupils affect

educational recommendation. Taken together, how-

ever, the six non-cognitive competences analysed

account for no more than 1.5 per cent of the explained

variance. In the final column of Table 7, the

standardized coefficients are presented. Inspection of

these coefficients indicates the relative weights of the

predictors. As can be seen, maths performance is

decisive for the level of educational recommendation

followed by reading and language performance.

Comparison of models 1 and 4 clearly shows the

dominant role of school performance in educational

advising. School performance explains more than two-

thirds of the variance in educational recommendation.

Those factors which might indicate a bias in the

educational advising of the school in the form of either

over- or under-recommending on the grounds of non-

performance related considerations jointly explained

less than 3 per cent of the total variance in educational

recommending.

Discussion

In the present contribution, the recommendations for

secondary education provided during the last year of

primary school in the Netherlands stood central. The

core question was whether or not we can still speak of

over-recommending (i.e. higher types of secondary

education being recommended for certain groupsof pupils than justified by their capacities). Over-recommending represents a deviation from themeritocratic principle and, in the present research, itwas studied from three perspectives (i.e. in terms ofethnicity, type of community, and cognitive level ofthe class).

With regard to the over-recommending of minoritypupils, the existence of the phenomenon has beendemonstrated on a number of occasions since the endof the 1980s (Driessen, 1991). The results of the presentanalyses show such ‘ethnic’ over-recommending tovirtually be a thing of the past: given equal schoolperformance, the different ethnic groups received com-parable educational recommendations although oneexception does exist, namely some minimal over-recommending for the category of ‘other minoritypupils’.

Dronkers et al. (1998) discovered a different form ofover-recommending in namely big cities and even afterthe influences of various pupil and school character-istics were taken into consideration. The cause of thiswas assumed to be the more assertive urban climatewhere teachers have less authority and parents exertmore pressure on teachers. The findings of the presentresearch do not provide support for this line ofreasoning. In fact, the somewhat lower level ofeducational recommendation on average in big citiescan be completely attributed to the relatively lowerschool performance of the pupils in the cities, and onecannot speak of over-recommending. It can also benoted in this light that there is no relation to thesocial-ethnic composition of the classes: the percent-ages of minority and native-Dutch disadvantagedpupils in the classes do not in any way explain thevariation in educational recommending.

When the composition of the class in terms of theaverage level of performance for language and maths areexamined, it is often assumed that the level of theeducational recommendation provided by the teachermay depend on the relative position of the pupil withinthe class. In a class with a predominantly low level ofperformance, slightly better pupils may be more easilygiven a higher educational recommendation than otherpupils (Driessen et al., 2003). The analyses conductedhere show the pupils in classes with a high cognitive levelto indeed receive higher educational recommendations,but this is clearly due to the higher levels of schoolperformance on the part of the individual pupils in theseclasses. When school performance is controlled for,moreover, one can actually speak of under-recommend-ing in the classes with a high cognitive level: The pupilsin such classes receive a relatively lower level of

MERITOCRACY AND ETHNICITY 539

educational recommendation after school performanceis taken into consideration—which is also counter to themeritocratic principle. As mentioned earlier, theseresults are in line with findings from German researchon the transition from primary to secondary education(Kristen, 2000).

In sum, the analyses conducted here show that, tothe extent that over-recommending still occurs, it doesnot relate to ethnicity, cognitive level of the class, ortype of community. This means that the phenomenonof ethnic over-recommending as it occurred in the1980s and 1990s in the Netherlands no longer occurs.This also implies that the three hypotheses orexpectations we formulated in the introduction ofthis article have to be rejected.

In addition to the occurrence of over-recommending, the meritocratic character of theeducational recommendations provided by primaryschools was also examined. The present findings showthe school performance of pupils to be decisive for theeducational recommendations provided. The othercognitive and non-cognitive competencies and social-ethnic background characteristics of the pupils con-sidered in the present study added little or nothing tothe predictive power of school performance. Thesefindings confirm the results of other Dutch research oneducational advising conducted by Luyten and Bosker(2004). These researchers also concluded that perfor-mance weighs more heavily than social-ethnic back-ground in the determination of educationalrecommendations. This means that pupils can com-pensate for a less favourable social-ethnic backgroundwith good school performance, but a favourable social-ethnic background cannot provide solace for inferiorschool performance.

The present results suggest that the associationbetween capacities and educational recommendationshas increased over the years and that, as a result ofthese increases, the already strong meritocratic calibreof Dutch educational advising has also increased. Ofinterest, is the question whether this finding alsoapplies to other European countries. Given the some-times contradictory results of European research oneducational matters, in part owing to differences ineducation systems, additional internationally compara-tive research is, therefore, needed (cf. Hanushek andWobmann, 2006). Such research can also shed morelight on limitations of Dutch studies on educationaladvising and the methods used. One relevant issue inthis context could be the possible bias of Dutch studiesdue to the standard treatment of the dependentvariable, educational recommendation, as an intervalvariable. With the results of such research, clearer

and better insight into the meritocratic calibre ofeducational recommendations in the Netherlands andelsewhere can thus be obtained.

Notes

1. In contrast to countries such as The Netherlands,

Germany, and Switzerland, where one can speak

of a selective education system, countries such as

the UK and the US have a more comprehensive

educational system and thus less tracking. The

choice of secondary education is also made

relatively late in the school careers of pupils in

the latter countries, which means that the

phenomenon of over-recommending is less likely

to present itself or may not occur at all.

2. The Antillean and Surinamese immigrants to the

Netherlands come from former colonies. As a

result of these ties, they are often already familiar

with the Dutch language and culture. The Turkish

and Moroccan immigrants consist of mostly

guestworkers arriving in the Netherlands in the

1960s and subsequent waves of immigration for

family formation or reunification purposes. One

characteristic shared by all these immigrants is

their low level of education. The remainder of the

immigrants to the Netherlands constitute a very

heterogeneous group with respect to language,

culture, and religion. The group includes guest

workers from other western countries and refugees

or asylum seekers from the Middle East, for

example.

3. We also tested, for example, two series of

interactions. First, the interactions between par-

ental education and ethnicity, on the one hand,

and the interactions between parental education

and school performance, on the other hand, were

evaluated. Whether the effects of parental educa-

tion on school recommendation differ across the

different ethnic groups or not can be examined in

such a manner. Following this, the remaining

interaction effects were added to the model,

namely: ethnicity� gender; parental educa-

tion� gender; gender� language, maths, and

reading performance; and ethnicity� language,

maths, and reading performance. Taken together,

these 32 interactions were found to explain not

more than an additional 0.6 per cent of

the variance in educational recommendation.

540 DRIESSEN, SLEEGERS AND SMIT

The pupil characteristic of ethnic breach played

no significant role and was, therefore, not

included in the final model.

Acknowledgements

The data used in the present analyses are from theDutch cohort study Primary Education (PRIMA).This cohort study was financially supported by theFoundation for Behavioural Sciences, which is part ofthe Dutch Organization for Scientific Research(NWO).

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Authors’ Addresses

Geert Driessen (to whom correspondence should be

addressed), ITS, Radboud University Nijmegen,

PO Box 9048, 6500 KJ Nijmegen, The Netherlands.

Tel.: þ 24-3653545; Email: g.driessen@its.ru.nl;

WWW: http://www.geertdriessen.nlPeter Sleegers, SCO-Kohnstamm Instituut, University

of Amsterdam, 1090 GE Amsterdam, The

Netherlands. Email: p.j.c.sleegers@uva.nlFrederik Smit, ITS, Radboud University Nijmegen,

6500 KJ Nijmegen, The Netherlands. Email:

f.smit@its.ru.nl; www.frederiksmit.com

Manuscript received: February 2007

542 DRIESSEN, SLEEGERS AND SMIT