207.full

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.

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


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


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).


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.



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


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.



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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