Ethnic Hostility among Ethnic Majority and Minority Groups

theoretical construct ‘previously demonstrated academic ability’ is not ideal since they are based
on self-reports. Our imperfect measurement of ability may have led us to underestimate ability’s
explanatory power for differences in success probabilities across ascribed characteristics. On the
other hand, we used three different indicators of ability to explain success probabilities instead
of just one. Our results indicate that ability is not a perfect indicator for success probabilities
and other factors may infl uence students’ estimations of future success as well. In relation to
this, we hypothesised that especially students from higher social origins and native Dutch ground
their success probabilities on effort next to ability and hence that the relationship between
ability and expectations of success would be weaker among these groups. We did however not
fi nd corroborative evidence for this hypothesis, possibly because ability as operationalised in this
study is already a refl ection of both ability and effort.
We examined the school decision taken after university-preparatory secondary education
for a specifi c track of higher education. We distinguished four tracks, which differ in level
(university versus professional college) and fi eld of study (science versus non-science). We found
supportive evidence for the relative risk aversion mechanism: students with higher educated
parents have stronger university aspirations than students with lesser educated parents, and
these differences in aspirations explain some 50 per cent of the effect of parental education
on the choice between the two levels of higher education. Moreover, differences in educational
aspirations fully explain why women are less likely than men to opt for schooling at a university
rather than at a professional college, at least in 1995 and 1997. Nowadays, women are more likely
than men to opt for university schooling (Statistics Netherlands, 2007). Future research should
examine whether this is due to a change in educational aspirations.
Parents’ contributions to cover study costs, whether the student lives at home, and
students’ eagerness to fi nish school as soon as possible – both factors which we assume are related
to the perceived direct and indirect costs of studying for the student – explain about 25 per cent
of the effect of parental education and income on schooling level choice. However, these factors
do not explain the effect of sex and ethnic origin on the decision between university–non-science
and professional college–non-science. This is possibly because differences in perceived study
costs between men and women students and across ethnic groups are small (after controlling
for parental income). With respect to the chosen fi eld of study, only living at home contributes
to the explanatory model; however, it does not explain the effect of ascribed characteristics on
fi eld choice. Science fi elds are considered to be more diffi cult than non-science fi elds. Students
who choose a diffi cult fi eld may have more need to budget their time and therefore decide to
remain living at home. Alternatively, science and non-science students may simply have different
residence preferences.
The further students come in their educational career, the weaker the association is
between social origin and ability, due to the selection processes encountered previously in the
educational career. But even among students who successfully completed a higher track of secondary
education, those from more advantaged backgrounds have signifi cantly better demonstrated ability.
Since we fi nd a signifi cant relationship – although admittedly not a very strong relationship,
ability and hence success probabilities should explain the effect of social origin on track choice