Educational Research - the Ethics and Aesthetics of Statistics

34 M. Depaepe
tapping other sources alongside the rather deficient basic statistical material. To
what extent can statistics (here considered primarily as cliometrics) as a technique
and/or as a method bring the historicity of studied dynamics to the surface? To what
extent, in other words, is historical statistics able to take into account the studied
processes and the changes in the social context that accompany these processes
and/or to keep them under control?
3.3.2 Too A-Historical?
I have already raised the question about the possible a-historicity of some of the
indicators and/or parameters used in order to map social status, the degree of education
and the relationship between them. Obviously, 40 years ago, graduating from
a university or an institute meant a lot more than it does today. Also the completion
of secondary education, which was quasi-universalized since the extension of
compulsory education in 1983 (De Ceulaer, 1990), had different connotations in
1960 than it does now. At that time, having completed lower secondary education,
one could, for example, easily obtain a position as a clerk in some form of public
service (see Depaepe et al., 1992). So should one continue to use these educational
levels supra-historically in order to measure the degree of schooling or people’s
social status? Of course, the same question applies to the profession of the father or
the first profession of the respondent, which are taken as indicators of the place of
the respondents on the social ladder. Professions and their prestige are themselves
subject to sociohistorical fluctuations, and the factors that cause these fluctuations,
as we have tried to clarify with respect to teaching profession (Depaepe & Simon,
1997), are not only very numerous but do not necessarily operate in the same upward
or downward direction of greater or lesser prestige.
Moreover, it is questionable as to whether or not the social dynamic of intergenerational
mobility can be grasped with the rough categorization or hierarchization
of the professions that are considered in the studies cited here. Such studies do
not go much further than the crude differentiation between blue-collar worker and
white-collar worker (see Tan, 1998, 177 ff.; possibly ‘higher-level white-collar
worker’, see Groenez, 2008, 3 ff.), supplemented or not with the distinction
between self-employed and having no profession (see Verbergt, et al., 2009, 3ff.).
Do these crude categories permit sufficient determination of the group-specific
expansion of the participation of the blue-collar workers in the higher educational
levels with which the democratization of education is ultimately operationalized
(Groenez, 2008, pp. 3–4)? Not only has the category ‘blue-collar worker’ taken on
different meanings over the last few decades but this specific group has also taken
on a totally different quantitative form in absolute but also and primarily in relative
terms with respect to the middle-class groups. Even if quantitative adjustments can
be made by carefully considered statistical operations, it is still much more difficult
to make qualitative adjustments.
When approaching the quantitative aspect, Groenez tries to distinguish relative
from structural mobility by means of the application of an odds ratio. This
yields some fascinating formulas 2 and the construction of gender-differentiated