EXPLAINING SOCIAL EXCLUSION - Institut für Soziologie

International Journal of Sociology and Social Policy 102
on the causes of transitions. There are some life-course sociologists
who claim that trajectories are not adequately treated by this kind of
methodology (Abbott and Hrycak 1990). Knowing a lot about transitions
without knowing much about trajectories is like seeing the trees
but not the wood.
Using optimal matching analysis we want to see whether there
are types of careers that show a pattern of exclusion. The focus of this
method is not on single transitions but on whole occupational sequences
and their comparison. For example three sequences of different
persons could look like this: CCUD; CUUD; CCCC, where C
indicates the state "constant Status employment position", U refers to
"unemployed" and D indicates "downward mobility". As each letter is
a measurement of one month the sequence CCCC is an equivalent to
four months in a constant employment position. Optimal matching refers
to a distance measure that is calculated by a comparison of each
sequence with any other. In our example a visual inspection shows that
the sequence CCUD is more similar to the sequence CUUD than to the
sequence CCCC; and CCCC is more similar to CCUD than to CUUD.
With large data sets and long sequences visual inspection is not possible.
Optimal matching computes a matrix of similarity values between
each sequence of the data set. In a second step these distances can be
used in cluster analysis in order to find groups with similar employment
sequences.
In our analysis, states of employment were differentiated into
the following categories: constant Status positions; small downward
mobility positions with a 5-10% lower occupational prestige than the
certificate; large downward mobility positions with a more than 10%
lower occupational prestige, and likewise defined small and large upward
mobility positions. Mobility was measured by comparing the
time-specific prestige score (Ganzeboom and Treiman 1996) with the
prestige score of qualification (according to occupation-specific
graduation or apprenticeship certificate). "Constant Status position"
refers to equivalent values of these two prestige scores. Three states of
non-employment were included: unemployment, studying, and other
kinds of non-employment, which mainly consist of spells of retraining
Volume 21 Number 4/5/6 2001 103
or housewife positions. Similarity distances won by optimal matching
algorithms were clustered afterwards with the Ward algorithm. A four
cluster solution was chosen, which showed distinct patterns of career.
Within these four clusters two favourable and two unfavourable
or ambivalent clusters can be seen. The favourable clusters were called
"in constant position" and "the big winners". The unfavourable and the
ambivalent clusters were labelled "the big loss" and "the risky decisions".
The figures two to five show the aggregate time dependent distributions
of our eight states within each cluster.
100%
80%
60%
40%
20%
0%
Figure 2: Career types, cluster 1: In Constant Position
• unemployment
D non-employment
ü studying
• large dow nw ard mobility
• small dow nw ard mobility
D constant position
M large upw ard mobility
D small upw ard mobility
Time in Months
N=880 47.3%
Special Collaborative Centre 186: East German Career Study
The biggest cluster is "in constant position" with 47% of the
sample. The main characteristic of this group is quite permanent employment
without a change of Status. There are few changes in this
cluster: After 10 months, more than 90% of the persons in this cluster
are employed in positions with a prestige Status that is identical or very