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Previous School Results and SocialBackground: Compensation and ImperfectInformation in Educational Transitions
Fabrizio Bernardi1,* and Hector Cebolla-Boado2
Abstract: In this article, we analyse whether previous school results have a social background-specific
impact on a students decision to continue in schooling. We refer to the model proposed by Breen and
Goldthorpe (1997) and scrutinize the theoretical underpinnings of the interaction between previous
school performance and educational choices. We provide two sets of predictions. First, a compensatory
effect might occur if inequality is greater among the worst-performing students than among others. In
this case, students from socio-economically advantaged backgrounds with poor school results would still
move to higher educational levels, whereas students from socio-economically disadvantaged back-
grounds with poor school results would drop out. Second, inequality might be higher among average
performers. Both good and poor school results send stronger messages and clearer information than
scores in the middle of the distribution. If individuals from different socio-economic backgrounds
handle imperfect information differently, then the impact of social background could be larger on
average grades than on good or poor ones. To test these hypotheses, we used the French Panel dEle`ves
du Second Degre and focused on social background differences in the decision to opt for the academic
or the vocational track after the completion of compulsory education. Our findings support the
hypothesis of a compensatory effect. In the conclusion, we discuss further general implications of our
results for research on educational inequality.
Introduction
A key tenet in the research on educational inequality is
that grades, as well as any alternative proxy of previous
school performance, are used by families to infer the
probability of success when facing critical branching
points in the education system (Boudon, 1974). Little
attention has, however, been paid to differences in the
impact of academic performance on future educational
choices across social backgrounds. It is true, on the one
hand, that some studies have discussed the empirical
relevance of an interaction between social background
and academic performance, either as a built-in compo-
nent of the specific decomposition method employed, or
as robustness checks. Yet, on the other hand, the
theoretical reasons as to why previous school results
might impact differently depending on social back-
ground have not been fully scrutinized. The main
contribution of the present article is to fill this gap in
the literature and to provide behavioural evidence on
how families of diverse social standings react differently
to similar childrens performance in school. As we argue,
our findings also hold important implications for the
model of educational transitions proposed by Breen and
Goldthorpe (1997).The main question that we address in this article is
whether previous school results have a social background
specific impact on a students decision to continue
in schooling. We provide two sets of predictions. A
compensatory effect occurs if the transition probabilities
for upper-class students are less dependent on previous
performance than those of students of lower socio-
economic standing. In that case, students of higher
socio-economic standing with poor school results still
proceed to higher educational levels or onto more
prestigious educational tracks, whereas lower-class
1SPS, EUI, Via dei Roccettini 9, San Domenico di Fiesole, 50014 Florence, Italy; 2UNED, Sociology department II,
Calle Obispo Trejo s/n, 28040 Madrid, Spain. *Corresponding author. Email: [email protected]
European Sociological Review VOLUME 30 NUMBER 2 2014 207217 207DOI:10.1093/esr/jct029, available online at www.esr.oxfordjournals.org
Online publication 11 October 2013
The Author 2013. Published by Oxford University Press. All rights reserved.For permissions, please e-mail: [email protected]. Submitted: March 2013; revised: July 2013; accepted: August 2013.
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students with poor school results are more prone todrop out or to opt for less-demanding educationaltracks. Social background inequality in educationaltransitions would then be higher among poorly per-forming students. A compensatory effect might comeabout because upper-class students have a strongerincentive to pursue ambitious school careers to avoidsocial demotion, largely independent of the low estimatesof the likelihood of their success (Lucas, 2009).Moreover, upper-class families have the necessary eco-nomic, social, and cultural resources to compensate forprevious poor school results.
Alternatively, inequality might be higher among aver-age performers. The results on the extremes of theachievement distribution might send stronger and clearermessages than scores in the middle of the distribution.When students attain average results, their families mightbe less able to infer from their childs current perform-ance their chances of succeeding at the next stage, whichcan amplify the impact of social origin.
To test these predictions, we used the French PaneldEle`ves du Second Degre, a longitudinal cohort studythat followed students joining compulsory secondaryschool in 1995. We focused on social class differences inthe decision to opt for the academic or vocational trackafter the completion of compulsory education.Additionally, we examined whether and how thesedifferences are conditioned by previous performance.
The remainder of the article is structured as follows:In the next section, we present the theory andhypotheses that drive our work. A short description ofthe French school system follows. The fourth section isdevoted to the presentation of our dataset, followed by adiscussion of the empirical findings. The concludingsection provides a summary of our results and adiscussion of their implications for the Breen andGoldthorpe (1997) model and for social stratificationresearch.
Relative Risk Aversion, SubjectiveProbability of Success, andResources
The Breen and Goldthorpe model (1997) (henceforth,BG model) proposes three mechanisms through whichclass differences in educational outcomes might origin-ate. These mechanisms are Relative Risk Aversion (RRA),differences in abilities and expectations of success, anddifferences in resources. We elaborate on each of thesemechanisms to understand whether and why the impactof previous results on decisions to continue in schoolmight vary depending on social background.
Relative Risk Aversion
A central assumption in the BG model is that students
and their families aim to achieve an educational level
that minimizes the risk of downward social mobility. A
corollary of this assumption is that students of higher
socio-economic standing will continue in education
when their probability of accessing the higher social
classes, either after completion of the next educational
level or after failing to do so, is higher than the
probability of accessing the higher social classes after
dropping directly out of education. Formally:
i 1 i > 1where i is the expected probability of success incompleting the next educational level; is the probabil-ity of accessing the higher social classes if the next
educational level is completed; (1i) is the probabilityof failing to complete the next educational level; is theprobability of accessing the service class despite not
having completed the next educational level; and is theprobability of accessing the higher social classes having
dropped out of education.Based on (1), Lucas (2009) demonstrates that the RRA
implies that students of higher socio-economic standing
might discontinue education only under specific condi-
tions, namely, when is smaller than .1 This indicatesthat the students might drop out only if they think that
their chances of occupational success are higher if they
leave education than if they stay in school and fail. Even
in that case, the students would still stay in education if
i and were sufficiently high. In any case, upper-classstudents of higher socio-economic standing will leave
school only when they perceive that their chances of
occupational success, and of avoiding downward mobil-
ity, are higher by leaving than by staying in school
(regardless of whether they fail or complete the next
educational level). This specific situation is labelled by
Lucas (2009) as the Gates Gambit, as the story of the
famous college dropout, Bill Gates, exemplifies. Despite a
high probability of success in education (i), the expectedoccupation returns without education () might behigher than the estimated future returns, both in the
event of failure () or success () in completinguniversity education.
Lucas (2009) formal analysis provided us with the
insight that for the large majority of students of higher
socio-economic standing, their decision to continue or
not in schooling is largely independent of the probability
of success at the next educational level. Except under the
very specific conditions epitomized by the Gates Gambit,
the aversion to downward mobility will always make it
more convenient for students of higher socio-economic
208 BERNARDI AND CEBOLLA-BOADO
-
standing to stay in school, regardless of their previous
performance.
The Differences in Abilities and the
Probability of Success
As previously mentioned, the subjective probability offuture success in education, i, is one of the keyparameters in the BG model. In general terms, the higheri, the higher the probability of continuing in education.Moreover, the subjective probability of future success isinterpreted as a function of manifested abilities in a
previous examination or the final grades at the previous
educational level (Breen and Goldthorpe, 1997).Formally,
i g ai 2where ai refers to previous school results.
A rather undertheorized assumption of the BG model
is that the function g is the same for all social classes. Inother words, when given similar school results, families
of different social classes would infer a similar subjective
probability of success at the next educational level.However, if one follows Breen (1999), the subjective
probability of success at the next educational level can beconceived of as a function of two factors: the individual
effort a student has made so far, and an ascriptive factorrelated to the individuals innate ability. Thus, a family
interprets previous school results as a combination of
effort and ability. Formally,
i g ai gai Ii ei 3where Ii stands for individual ability and ei represents
effort. Framed in this way, class-specific differences inschool continuation rates might also stem from different
values attributed to and . A poor performance mightbe disregarded as an indicator of likely subsequent failurethe smaller is, or if one believes that the poorperformance was caused by limited effort, which can becorrected in the future. Alternatively, if poor perform-
ance is interpreted as a reflection of limited individual
abilitythat is, if more weight is given to Ii (large )then there is less room for improvement at the next
educational level. Recent experimental work in socialpsychology shows that academic success among high-
status groups and failure among low-status groups areattributed to ability, whereas academic failure among
high-status and success among low-status groups tend to
be attributed to effort (Iatridis and Fousiani, 2009). In anutshell, if the view that poor school performance of
upper-class students is interpreted as the result of a lackof effort, its negative implication on school continuation
decisions can be expected to be smaller.
Another mechanism that could have an impact is the
information that school results convey to families. Both
good and poor school results send clear messages to
families concerning the likelihood of their children
succeeding at higher stages of the educational system,
while scores in the middle of the distribution might be
more difficult to interpret. When faced with middling
results, families of lower socio-economic standing might
interpret this differently to those of higher standing. In a
scenario of incomplete information, lower-class families
might overestimate the level of selectivity of the next
educational level, undercutting their childs potential
ambition to pursue further education. Formally,
i g ai,k 4where k is the perceived threshold in academic perform-
ance that has to be met to complete the next educational
level. The subjective probability of future success i willthen depend on the comparison between previous school
performance and k. Some uncertainty about the exact
value of k can, however, be supposed. Students with very
high or low previous performance are less likely to be
influenced by this uncertainty, the former group being
convinced of their ability to surpass the threshold as
opposed to what happens within the latter group. We
can also factor in the idea that upper-class families are
likely to possess a better knowledge about k, given their
own school experience, their higher level of involvement
in their childrens schooling, and their more frequent
interactions with teachers (Lareau, 1987). The crucial
point, then, is whether lower-class families overestimate
or underestimate k. If self-justification strategies are
assumed, one can expect that parents who have not
completed a given level of education will tend to
overestimate k as a way to justify their low educational
achievement.2 To sum up, if high- and low-performing
students are not affected by the uncertainty in k, while
lower-class families tend to overestimate k, then larger
class inequality can be expected among students with
average school performances.
Resources
Differences in resources do not play a key role in the BG
and are mainly conceived as economic resources to meet
the costs of education. Cultural and social resources,
however, in addition to economic ones, might play a
crucial role in compensating the effect of previous failure
or mediocre performance at school. For example,
because of their superior financial and cultural resources,
upper-class families could provide extra support to their
childrens schooling. These families can, for instance, pay
for private tuition or help with homework assistance.
PREVIOUS SCHOOL RESULTS AND SOCIAL BACKGROUND 209
-
Additionally, their knowledge of the education system
and their social contacts can also help to identify the
ideal school for their offspring (for example, less selective
institutions with fewer students and special
programmes).Differences in economic, cultural, and social resources
across social classes would then complement the RRA
mechanism and the micro-psychological mechanism for
rationalization of a previous failure discussed in the
previous section. To summarize, parents of higher socio-
economic standing have great interest in avoiding
downward social mobility and tend to interpret a
previous failure as the result of a lack of effort. They
thus believe that the lack of effort can be compensated
for, and also have the resources to pursue such
compensation.
Summary of Hypotheses
Empirical tests of the BG model have modelled the
effects of motivational factors related to the RRA
mechanism and the effects of observed school perform-
ance in an additive manner (Need and de Jong, 2001;
Van de Werfhorst and Hofstede, 2007; Gabay-Egozi,
Shavit and Yaish, 2010). However, our previous dis-
cussion of the BG model suggests different mechanisms
that could possibly invalidate the assumption that school
performance and social background effect related to
status maintenance affect transitions in an additive
manner. We call these mechanisms compensatory
effects and incomplete information. These mechanisms
imply an interaction between the parameters modelling
performance and the social background in making actual
choices. In other words, when facing similar school
results, people of different classes might behave differ-
ently and, accordingly, make different school continu-
ation choices.A compensatory effect occurs if the upper-class students
move onto the next educational level (or onto a more
demanding academic track), disregarding low levels of
previous performance. This effect is predicted by the
RRA mechanism. In almost all situations, the fear of
downward mobility for upper-class students will make it
more attractive to continue in school, regardless of their
previous performance and their subjectively estimated
probability of failure. In contrast to upper-class students,
for those of lower socio-economic standing, the BG
model implies that past performance and its impact on
the subjective estimation of the probability of success is a
key parameter in their decision to continue in schooling
or not. Moreover, those of higher standing tend to
interpret school performance in terms of effort instead of
innate ability, thus making school continuation more
likely for this group, despite previous poor school
results. Finally, advantaged students have the social,
cultural, and economic resources to pursue compensa-
tion strategies. Figure 1 provides a graphic illustration of
the compensatory effect. The Y-axis refers to the
probability of staying in school, while the X-one refers
to previous performance at school. Figure 1 shows that
the probability for the upper-class group is rather
inelastic to previous performance. This graphically
summarizes our first hypothesis, namely, the compensa-
tory effect, according to which the largest inequality in
the probability of school continuation between classes
should be observed among the low-performing students.Alternatively, inequality might be higher in the middle
ranks of the range of grades. The specific cause of this is
that whereas good and bad grades send clear messages to
families regarding estimated chances in subsequent stages
of the educational system, scores in the middle of the
distribution are more difficult to interpret. If facing
imperfect information, families of lower standing could
over-estimate k and the level of selectivity of the next
educational level. Figure 2 illustrates this second hy-
pothesis. klower and kupper refer to these perceived
thresholds for those of lower and higher socio-economic
standing, respectively. The probability of the children of
lower-standing families making the transition remains
low until the grades surpass the threshold klower. In
contrast, upper-class families set the threshold at a lower
level, and their probability of making the transition
begins to rise accordingly for a lower value of school
performance. As a consequence, a larger inequality
should be expected for average academic performance.
This summarizes our incomplete information hypothesis.
The French Educational System
In France, compulsory education covers elementary
(ecole elementaire) and lower secondary school (colle`ge)
up to age 16. Throughout this period, the system is
comprehensively organized. Post-compulsory upper sec-
ondary education is subsequently divided into three
tracks. The lycee general et technologique (general and
technological upper secondary school) provides general
and abstract training and represents the most straight-
forward path to university. The lycee professionnel
provides the Brevet detudes professionnelles (BEP) after
2 years. Students on this track can proceed to the
adaptation course (1 year) that bridges to the profes-
sional and technical lycee, although this alternative is
scarcely used. The other vocational credential is the
Certificat daptitude professionnelle (CAP), which prepares
the student for a specific occupation and is a direct path
210 BERNARDI AND CEBOLLA-BOADO
-
to the labour market. This track does not allow the
possibility of a Baccalaureat (BAC) degree.The selection of students at the end of lower
secondary education onto the academic track (General
or Technological Lycees) or the vocational one (BEP and
CAP) is the critical junction of the French school system.
Previous studies have indeed shown that the outcome of
this educational transition largely conditions the later
opportunities to access university, and that large differ-
ences exist between the social classes of origin in the
distribution of students between the academic and
vocational tracks (Merle, 2002).The tracking of students onto the academic and
vocational tracks is decided during the so-called proce`s
dorientation, which takes place at the end the final year
of colle`ge. After consultation with the families, a class
council formed by teachers and inspectors makes
decisions based on the students previous academic
achievement and the explicit wishes of the families. The
students academic achievement is evaluated through anational examination called Brevet des colle`ges as well astheir school results in the last year of colle`ge. The aim ofthe Brevet is to certify the level of academic achievementat the end of colle`ge, but its results do not formallycondition access to post-compulsory upper education.The proce`s dorientation was intended to reduce classbias in the distribution of students across differenttracks (Duru-Bellat and Van Zanten, 1999). However, anumber of studies have shown that the families explicitpreferences are given greater weighting and that thisamplifies social background inequality (Roux andDavaillon, 2001; Merle, 2002).
Data and Variables
The Panel dEle`ves du Second Degre (19952001) sampleda cohort of 17,830 students who started lower secondaryschool in 1995. The questionnaire de recrutement wascompleted in 1995 using administrative files. It includesbasic demographic information, such as sex, place anddate of birth, and nationality. A number of follow-upquestionnaires collected yearly information on academicprogress and school careerssuivi de la scolarite delele`ve. At the end of lower secondary schooling (3e`me),the heads of the schools completed another question-naire with detailed information concerning grades andthe result of the selective process that links lower andupper secondary schooling (procedure dorientation). Afollow-up questionnaire a year later allowed the head ofschools to check whether students ultimately droppedout or accepted the placement proposed at the end ofcompulsory schooling.
We have restricted the analysis to students born inFrance (N 17,161). The bottom line of Table 1 reportsthe loss of cases from the original to the analyticalsample. The sizeable reduction in the number of cases inthe analytic sample (N 12,670) is due to the largenumber of observations with missing information on thegrades at the end of lower secondary schooling (Brevetscores). However, it is reassuring that the distribution ofthe primary independent variables (gender and socialclass of origin) in Table 1 is very similar in the analyticsample and in the original sample. Moreover, wereplicated all of the analyses, including an additionalcategory for those cases with missing values on Brevet.Our primary finding also turns out to be highly robustin this larger sample (N 15,741; see online Table A1).Thus, we are confident that our conclusions, based onthe analytic sample, are reliable.
Our dependent variable is the track that the studentfollowed in upper secondary school. As we have arguedin the previous section, Table 1 shows that 40 per cent
Lower class
Upper class
Previous grades kupper klower
Probability of making the transition
Figure 2 Incomplete information: inequality is greater foraverage grades
Previous grades
Probability of making the transition
Lower class
Upper class
Figure 1 Compensatory class effect: inequality is greateramong those with poor grades
PREVIOUS SCHOOL RESULTS AND SOCIAL BACKGROUND 211
-
of the students who did not drop out went intovocational training; in contrast, 60 per cent of thestudents opted for the academic track. Our dependentvariable takes the value of 1 if the student proceedstowards the academic track (Seconde Generale etTechnologique) and 0 if the student chooses any of thevocational tracks (professional lycee, first-year BEP, orCAP).
As for our independent variables, we use the averagegrades obtained in the Brevet des Colle`ges forMathematics and French as the key indicators ofprevious school performance. The mean of Brevetscores can range from 0 to 20. In our sample, theminimum value is 4, the maximum value is 17, andthe average value is 11. In addition to the continuousvalue for the individual average in the Brevet scores, wehave defined three dummy variables that refer to thedistribution of the Brevet scores in tertiles. Thus, anindividual receives a score of 1 on the dummy firsttertile if his/her average in Brevet score in French andMath falls within the first tertile of the Brevet scoredistribution.3 Social class of origin refers to the occupa-tion of the head of the household when the student was12 years old, and it is coded using the Erikson and
Goldthorpe class scheme with six categories. These arethe upper class (that includes professionals and man-agers), routine non-manual employees of higher grade,petty-bourgeoisie (small proprietors with and withoutemployees), farmers, routine employees of lower grade,and skilled and unskilled manual workers. In comment-ing on the results, we focus on the comparison betweenthe top and the bottom categories, i.e., the upper classand the skilled and unskilled manual workers, thattogether include 50 per cent of the population.
We estimated a number of linear probability models(LPMs) with robust standard errors and logit models.The coefficients of the LPM are almost identical to theaverage marginal effects of the logit model. The advan-tage of the LPM over the logit model is not only that theinterpretation of marginal effect of the interactions thatare at the core of our analysis is much more straight-forward (Norton, Wang and Ai, 2004) but also that theyhelp to compare nested non-linear models (Mood,2010).
We have also conducted a number of robustnesschecks that include the following: a different definitionof the dependent variable, considering the preferencesexpressed by the families at the beginning of the
Table 1 Descriptive statistics: original sample (students born in France only), sample at the end of lowersecondary education (ninth grade), and analytic sample with valid information on Brevet
Originalsample
End of 3e`me End of 3e`me
dropout excludedAnalyticsample
Dependent variableAcademic track 54.1 55.9 61.1Vocational track 42.7 44.1 38.9Drop-out 3.2
Independent variablesGender (female) 48.3 48.9 49.2 51.1
Social class of originUpper class 14.4 14.9 15.0 16.1Routine employees, higher grade 17.3 17.8 18.0 19.2Petty-bourgeoisie 9.0 9.2 9.1 9.1Farmer 3.0 3.1 3.1 3.3Routine employees, lower grade 17.9 17.7 17.4 17.0Skilled and unskilled workers 34.5 34.2 34.5 33.1Inactivity 2.9 2.5 2.3 1.9Missing social class 1.0 0.3 0.6 0.6Brevet score (average) 11.0
Average Brevet within the1st tertile of the Brevet distribution 8.02nd tertile of the Brevet distribution 10.93rd tertile of the Brevet distribution 14.1
Number of observations 17,161 16,265 15,741 12,670
Source: Panel dEle`ves du Second Degre (19952001).
212 BERNARDI AND CEBOLLA-BOADO
-
orientation process instead of the final outcome; a
different treatment of the missing values in the Brevet
scores; a different conceptualization of social background
that also considers the highest level of education among
parents; the inclusion of those who have dropped out of
the education system; the replication of the models using
dummies for quartiles of the brevet distribution instead
of tertiles; and the replication of the results using the
average marginal effects (AME) of a logit model. The
results of these parallel analyses are available in the
supplementary online appendix, and they suggest that
the findings presented in the next section are robust.
Results
In Table 2, we present the results of our LPM models.
The first model includes only social class of origin and
sex. The second model adds school performance as
measured by the average Brevet score. The third model
breaks down the grades into three dummies that
Table 2 Transition to the academic track in France; linear probability model
Model 1 Model 2 Model 3 Model 4 Model 5
Gender (Female) 0.11** 0.04** 0.05** 0.04** 0.05**Social class of origin
Upper class (reference)Routine employees, higher grade 0.17** 0.10** 0.11** 0.64** 0.15**Petty-bourgeoisie 0.27** 0.13** 0.15** 0.82** 0.20**Farmer 0.30** 0.22** 0.24** 0.93** 0.33**Routine employees, lower grade 0.37** 0.20** 0.22** 0.86** 0.29**Skilled and unskilled workers 0.47** 0.27** 0.30** 1.05** 0.40**No activity 0.60** 0.33** 0.37** 0.99** 0.56**
Previous school resultsBrevet score 0.09** 0.05**
Position in the Brevet distribution1st tertile 0.39** 0.28**2nd tertile (reference)3rd tertile 0.23** 0.08**
InteractionsRoutine employees (high)Brevet 0.04**Petty-bourgeoisieBrevet 0.06**FarmerBrevet 0.07**Routine employees (low)Brevet 0.06**Skilled/unskilled workerBrevet 0.06**No activityBrevet 0.03**Routine employees (high) 1st tertile 0.15**Petty-bourgeoisie 1st tertile 0.13**Farmer 1st tertile 0.13*Routine employees (low) 1st tertile 0.12**Skilled/unskilled worker 1st tertile 0.08*No activity 1st tertile 0.08Routine employees (high) 3rd tertile 0.11**Petty-bourgeoisie 3rd tertile 0.13**Farmer 3rd tertile 0.24**Routine employees (low) 3rd tertile 0.19**Skilled/unskilled worker 3rd tertile 0.26**No activity 3rd tertile 0.30**
Constant 0.84** 0.29** 0.81** 0.24** 0.88**N 12,670 12,670 12,670 12,670 12,670BIC 15,970 11,737 11,920 11,531 11,838
*P < 0.05; **P < 0.01.
Note: The models include a residual category of respondents with missing social class, not shown here.
Source: Panel dEle`ves du Second Degre (19952001).
PREVIOUS SCHOOL RESULTS AND SOCIAL BACKGROUND 213
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correspond to tertiles in the distribution of grades (the
middle one being the reference category). In Models 4and 5, the class of origin interacts with the average Brevetscore and with the tertile dummies.
Model 2 indicates that approximately one-half of theobserved class inequality in Model 1 is due to thedifference in school results. For instance, the coefficient
for the skilled and unskilled workers declines from 0.47to 0.27 (a reduction of 43 per cent) once the Brevet iscontrolled for.4 The only exceptions are farmers, for
whom the reduction is somewhat smaller (from 0.30 to0.22, i.e., a reduction of 27 percentage points).
Model 3 specifies school results as dummy variables
that refer to the tertile distribution. The estimates forsocial class are very close to the estimates of Model 2.Next, in Model 4, we add the interaction effects between
the Brevet score and the dummies for social class. Theseinteraction effects are positive and statistically significant.This result indicates that inequality, with respect to the
service class, is largest among the worst achievers andbecomes progressively smaller as the values of the meanBrevet increase. This finding is in line with the hypoth-
esis of a compensatory class effect discussed in thesecond section. However, the specification of the meanBrevet as a continuous variable in Model 4 does not
allow testing for non-linearity in the class-specific impactof previous school results. For this reason, Model 5breaks down the grade distribution into tertiles, and it
checks for non-linearity in the class-specific influence ofgrades on the type of transition made in uppersecondary school.
With respect to the service class, the effects of thesocial class dummies in Model 5 express the disadvantageamong those with middling academic performance (that
is, among those with a mean Brevet in the second tertile).Thus, for a male student from an upper-class family witha Brevet score within the range of the second tertile, the
probability of choosing the academic track is 88 per cent(i.e., the constant term). For a male student from aworking-class background in the second tertile, the same
probability is 48 per cent (8840). Following on, theinteraction effects between the social-class dummies andthe dummies for the tertile distribution of Brevet are
negative in the case of the first tertile and positive in thecase of the third tertile. These results suggest that theclass inequality observed for the second tertile increases
among the worst-performing students and decreasesamong the best-performing. The same pattern is observedfor other social classes. Thus, no support is found for the
incomplete information hypothesis that would suggest alarger inequality in the middle of the grade distribution.
If that were the case, one would also observe positiveinteraction effects for the first tertile.
Finally, very similar conclusions are drawn if onefocuses on the predicted probabilities for differentcombinations of the class of origin and school resultsusing a logit model (Table 3). For all social classes, thelargest gap compared with service-class students isobserved among the worst-performing students (i.e.,those in the first tertile). The gap progressively reducesfor the students in the second tertile, and it almostdisappears among the best-performing students. Thepattern is particularly accentuated for students comingfrom white-collar or self-employed families.
Conclusions
We are now in a position to answer our initial researchquestion: do grades affect educational transitions differ-ently depending on social background? The answer is aclear yes. The results presented in the previous sectionsuggest that when compared with students of othersocial origins, upper-class students in France are lessaffected by previous school performance in choosing theacademic track or vocational track. In particular, upper-class students with below-average grades have a higherprobability of taking the academic track than studentswith similar grades from other social classes. As aconsequence, the largest class inequality is concentratedamong students with previously poor academic perform-ance. Among students of higher socio-economic standingwith below-average results, almost two in three students(60 per cent) move onto the academic track, whereas thesame is true of only one in five students (20 per cent)whose parents are routine employees of low grade or onein seven (15 per cent) students whose parents aremanual workers (Table 3). The difference between socialclasses is much smaller among high-performing students.Thus, we find evidence of a compensatory class effect,while not finding support for the incomplete informa-tion hypothesis, which suggests that inequality should belarger in the middle of the distribution of school results.
The observed compensatory class effect is in line withthe prediction of the BG model. As highlighted by Lucas(2009), the RRA mechanism implies that for most of thestudents of higher socio-economic standing, the subject-ive probability of success proves irrelevant for theirschool continuation decision, while it is a key parameterin the choice of middle- and lower-class students.
In addition to the motivational factor explained by theRRA mechanism, the two other mechanisms that arepart of the BG model might also contribute to theemergence of a compensatory class effect. First, socialclasses apparently differ in the way they interpret schoolperformance and infer expected probability of success,attributing different weighting to effort and ability as
214 BERNARDI AND CEBOLLA-BOADO
-
causes of school results. Recent experimental evidence
suggests that failure of upper-class students tends to be
interpreted as a consequence of poor effort, whereas the
failure of working-class students is perceived as an
indicator of low ability (Iatridis and Fousiani, 2009). The
crux of the argument is that whereas it is possible to
change and increase the level of effort, an increase in
performance is more complicated (if at all possible) in
the case of ability. Second, upper-class families have the
economic, social, and cultural resources to correct for
previous academic failure and improve the efforts of
their children.To conclude, we have three final remarks on how
common the French compensatory class effect might be,
its applicability to other research problems, and its
implications for the empirical test of the BG model and
the somewhat related area of research on primary and
secondary effects.First, we suspect that the compensatory class effect
found at the end of lower secondary school in France is
rather pervasive and similarly applicable to other edu-
cational transitions in other countries. Indeed, there is
sparse evidence that appears to support this claim. For
instance, a larger social background inequality in the
decision to continue in schooling among low-performing
students is observed in disparate and polar contexts,
such as the Soviet Unions Leningrad in the late 60s
(Yanowitch, 1977: p. 65) and the United States in the
late 70s (Carneiro and Heckman, 2003; Figure 2.7: p.
108). However, the last word on this issue can only be
offered when systematic replications have been per-
formed in different countries. In this respect, we would
expect that the compensatory effect is larger for those
educational transitions whose outcomes entail higher risk
of social downward mobility. Therefore, the compensa-
tory effect is possibly more relevant at earlier educational
junctions, when compared with choices about tertiary
education. Moreover, we would expect that it is smaller
for those educational transitions that are more strictly
regulated and formally dependent on previous educa-
tional performance. To put it another way, the com-
pensatory effect will be larger in those educational
systems and for those educational transitions that allow
more space for manoeuvre to families. This latter
expectation goes, however, with the caveat that even
where progress in education is most formally regulated,
the crucial idea underlying the compensatory effect is
that those of higher socio-economic standing will find
other channels to compensate a previous failure, and
effectively maintain their advantage (Lucas, 2001).5 For
instance, they might disproportionately take advantage of
second-opportunity education or recur to schooling
abroad.Second, we believe that the compensatory effect does
not apply solely to the interplay between previous grades
and school continuation decisions. It can naturally be
generalized to other situations, such as the consequences
of retention in those educational systems where retaking
is common, or to placement in a less prestigious
educational setting in a tracked system. There is evidence
demonstrating that the negative consequences of reten-
tion are smaller (Gambetta, 1987: pp. 121122) and that
movements from less to more prestigious tracks are
more common for students from more advantaged
backgrounds (Jacob and Tieben, 2009; Tables 3 and 4).
The compensatory effect can also manifest itself outside
the educational system. In its most general formulation,
the effect would state that whenever a problematic event
occurs, its negative implications will be much more
limited for those of the upper class. Poor grades are the
specific case studied in this article, but the compensatory
effect could also be relevant for other events known to
have negative consequences for the educational and
occupational outcome of an individual, such as juvenile
arrest, early pregnancy, or parental divorce. The com-
pensatory class effect, thus, depicts a general mechanism
Table 3 Predicted probability of probabilities of the transition to the academic track in France, by previousschool results and class of origin logit model
Brevet score in the . . .First tertile Second tertile Third tertile
Upper class 0.63 [0.590.67] 0.91 [0.900.93] 0.98 [0.980.99]Routine employees, higher grade 0.34 [0.320.37] 0.76 [0.730.78] 0.94 [0.940.95]Petty-bourgeoisie 0.29 [0.260.32] 0.71 [0.670.74] 0.93 [0.920.94]Farmer 0.19 [0.150.22] 0.58 [0.520.64] 0.88 [0.850.91]Routine employees, lower grade 0.21 [0.190.23] 0.61 [0.590.64] 0.90 [0.880.91]Skilled and unskilled workers 0.15 [0.140.16] 0.51 [0.490.53] 0.85 [0.830.87]
Confidence intervals in squared brackets.
Source: Panel dEle`ves du Second Degre (19952001).
PREVIOUS SCHOOL RESULTS AND SOCIAL BACKGROUND 215
-
that potentially underlies the making of social inequality
in many dimensions over life course.6
Finally, the existence of an interaction between social
background and school performance or, less technically,
the fact that social classes respond differently to previous
school performance in their school continuation decision
has important implications for empirical tests of the BG
model and the related area of research on primary and
secondary effects. Various studies have confirmed the
behavioural predictions of this rational choice model of
education; however, the (relatively) few studies that have
directly investigated motivational mechanisms find less
consistent results, particularly with regard to the social
demotion avoidance mechanism (Need and de Jong,
2001; Stocke, 2007; van de Werfhorst and Hofstede, 2007;
Gabay-Egozi, Shavit and Yaish, 2010). However, these
articles have modelled the effects of motivational factors
related to the RRA mechanism and subjective probability
of success (or observed school performance) in an
additive manner. Because the elasticity of grades varies
by social class and because service-class students in
particular are largely unaffected by previous performance
in their school continuation decision (as actually pre-
dicted by the RRA mechanism), these tests might be
somewhat off target. The same applies to those recent
studies that have investigated the primary and secondary
effects as additive effects and, once controlled for
previous school performance, interpret the effect of
social background as secondary effects (Cebolla-Boado,
2011; Schindler and Lorz, 2012; Barg, 2013). If, as our
findings appear to suggest, secondary effects are primarily
concentrated among students with below-average per-
formance, then an additive specification might produce
biased estimates. We hope that our research might make
other researchers more aware of the fact that social classes
do not apparently respond in the same way to previous
school performance in their school continuation decision.
Notes
1 There is no space here to develop the formal
demonstration, but see Lucas (2009: pp. 482483).
2 Research on risk perception indeed suggests that
people tend to exaggerate risks that are new or
unfamiliar (Slovic, 2000). That would be the case
for the risk of failure at the next educational level
for those parents who have not attended it.
3 The cutoff points for the first tertile are 1 and 9.7,
for the second tertile 9.7 and 12, and for the third
tertile 12 and 19.5. These cutoff points are based on
the sample distribution of the average scores on
Brevet. The three tertiles, however, almost perfectly
overlap with three broad categories that have a
clearer meaningful interpretation. A score 12 is considered satisfactory or good. We have
replicated the analysis also using these more sub-
stantive criteria for the definition of the categories
and the results (available on request) do not change.
4 A similar result for the cohort of students who
started lower secondary education in 1995 is also
reported by Ichou and Vallet (2013). Using different
decomposition techniques, they find that about one-
half of the observed inequality in the transition to
post-compulsory education between upper- and
working-class pupils is due to differences in previ-
ous academic performance.
5 On a theoretical level, the compensatory class effect
discussed in this article can thus be fruitfully framed
at the interconnection between the BG and effec-
tively maintained inequality (EMI) models. Lucas
(2009: p. 506) makes the case that the two theories
are complementary. We also believe that focusing
on how social classes react to a previous educational
failure provides an advantageous perspective to
integrate the two theories and to understand class-
based strategies to maintain and reproduce inequal-
ity. Draconian word limits prevent us from further
elaborating on this point.
6 However, a negative event does not randomly occur.
This posits a serious problem of endogeneity for the
study of the compensatory effect as defined in this
article. See Morgan (2012) for a discussion and
Bernardi (2012) for an attempt to address empir-
ically this problem.
Supplementary Data
Supplementary data are available at ESR online.
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