Isabelle Régner
email: regner@univ-tlse2.fr

Pascal Huguet

Jean-Marc Monteil

SES stereotype and ability inferences

Keywords: Socioeconomic Status, Stereotypes, Intellectual Performance

Two studies tested whether students' Socioeconomic Status (SES) and academic achievement level moderate their use of the SES stereotype (i.e., the belief that the low-SES individuals are intellectually inferior to their high-SES counterparts). In Study 1, low versus high achievers with a low versus a high SES were given social class information (derived from a pilot study) about several targets and were then asked to infer these targets' memory ability. In Study 2, participants were given memory performance information about several targets and were then asked to infer these targets' possessions and cultural activities (i.e., SES indicators). In both studies, only the low-SES students generated stereotype-consistent inferences.

Effects of Socioeconomic Status (SES) Information on Cognitive Ability Inferences:

When Low-SES Students Make Use of a Self-Threatening Stereotype.

Social class information has proved influential in social judgments situations where more individuating information on the target(s) (e.g., specific behaviors or traits) were either missing or relatively ambiguous. In [START_REF] Baron | Effects of behavioral and social class information on social judgment[END_REF] investigation, for example, students were given social class information on a nine-year old female child (the target) and were or were not faced with information on the way the target performed on several tasks (related to memory, mathematics, abstraction, etc.).

Then they were asked to rate the target's performance on those tasks. When the target performed well (answered 75% of the questions correctly) or poorly (answered 25% of the questions correctly), judgments of academic ability reflected these performances. The target's social class background had no effect. When the target performed ambiguously (answered 50% of the questions correctly), social class had a larger effect on judgments: The targets' ability was judged higher when her apparent SES was high rather than low, although the effect was not statistically reliable. The target's social class had the clearest effect on judgments of academic ability when the subjects received no stimulus information (i.e., the high-SES target was rated significantly higher in ability than the low-SES target). As noted by [START_REF] Baron | Effects of behavioral and social class information on social judgment[END_REF], this shows that the use of stereotypes is limited to conditions in which clear stimulus information relevant to the inference task is either ambiguous or absent (see also [START_REF] Darley | A hypothesis-confirming bias in labeling effects[END_REF][START_REF] Krueger | Use of categorical and individuating information in making inferences about personality[END_REF][START_REF] Locksley | Sex stereotypes and social judgment[END_REF].

The present paper focuses on the condition where the SES bias is generally maximized (i.e., when there is no individuating information on the target). Whether this bias is or is not moderated by the perceiver's SES and/or academic achievement level is our central question. [START_REF] Baron | Effects of behavioral and social class information on social judgment[END_REF] suggested that individuals make use of the SES stereotype regardless of their own SES. These authors indeed reported a SES bias in two studies among populations that themselves varied in social class composition: Participants (students) came from either a middle (Study 1) or a high (Study 2) socioeconomic background. Whereas this bias was significant with the former population, however, it was only marginally significant with the latter. Likewise, the SES bias was not significant in [START_REF] Darley | A hypothesis-confirming bias in labeling effects[END_REF] no-individuating-performance information condition (but it was in the case of ambiguous information) with participants from Princeton University. The generalizability of the SES bias, therefore, remains unclear. Overall, it seems that the high-SES students, in contrast with their middle-class counterparts, are not likely to produce the SES bias when only social class information are available. That the SES bias approached significance in Baron et al.'s (1995) Study 2 could be due to the fact that their sample included a substantial minority of participants who were more similar to those in Study 1 (i.e., students from the middle class who seemed sensitive to this bias). This is difficult to conclude, however. In past research, participants' SES was indeed not clearly specified: It was assessed from the prestige of their university and not from more typical SES indicators, such as parental occupation and housing quality.

The generalizability of the SES bias remains unclear for another reason: The low-SES Students were ignored in past research. Do these students use the SES stereotype ? At first glance, they would be especially reluctant to make use of a self-threatening stereotype which suggests that people like themselves are intellectually inferior to those from higher socioeconomic background. By definition, however, stereotypes are socially shared, and we know that this central feature per se can give the impression of objectivity or accuracy [START_REF] Hardin | Shared reality: How social verification makes the subjective objective[END_REF]. Thus, it can be assumed that even the low SES students can have a stereotypic perception of the link between SES and cognitive abilities.

Finally, one may also wonder whether the low-and high-SES students' academic performance history makes a difference in their use of the SES stereotype. Do the low-SES students who are high achievers make use of this stereotype ? The same question applies in the case of the high-SES students who are low achievers. Although the stereotypic perception of the link between SES and cognitive abilities may be especially strong for students whose SES and academic performances are consistent with the stereotype (i.e., the low achievers with a low SES as well as the high achievers with a high SES), it may be sufficiently influential in others (i.e., those whose SES and academic performances are not consistent with the stereotype). The present studies were conducted to help clarify these different issues.

Overview of the present studies

In past research on the SES bias [START_REF] Baron | Effects of behavioral and social class information on social judgment[END_REF][START_REF] Darley | A hypothesis-confirming bias in labeling effects[END_REF], participants in the no-individuating (performance) information condition were asked to infer the target's performance on the basis of its SES (low vs. high). A similar procedure, extended to multiple targets, was retained in Study 1. The reverse was done in Study 2, in which students were asked to infer the targets' SES on the basis of their performances. This latter procedure was conceived as an additional means to test the strength of the SES stereotype in students with a high versus low SES. As suggested earlier in this paper, these inferences were made in a minimal condition: Students in both studies did not have other information than those related either to the targets' SES (Study 1) or performances (Study 2). If students in this condition are sensitive to the SES bias, we would expect that 1) the higher the targets' SES, the higher the performance students would predict (Study 1), and 2) the higher the targets' memory performance, the higher the SES students would predict (Study 2). Following [START_REF] Darley | A hypothesis-confirming bias in labeling effects[END_REF] procedure, [START_REF] Baron | Effects of behavioral and social class information on social judgment[END_REF] depicted the target's SES through the general aspect of her neighborhood and school (i.e., appearing either wealthy or poor on a videotape). Several authors [START_REF] Dittmar | To have is to be: Materialism and person perception in working-class and middle-class British adolescents[END_REF][START_REF] Rosenberg | Social class and self-esteem among children and adults[END_REF][START_REF] Wiltfang | Social class and adolescents' selfesteem: Another look[END_REF], however, have shown that such SES indicators are not as meaningful for children and adolescents as for adults. As noted by these authors, adolescents are more likely to pay attention to SES differences when they are depicted through material possessions and cultural activities. Several targets varying in possessions and cultural activities, therefore, were created and then tested in a preliminary study with participants who themselves varied in SES.

Preliminary study

Method

Participants. Eighty students (42 females and 38 males, aged 13 to 16) from two French middle schools volunteered to participate in a study on "social evaluation".

Forty students had a high SES and the others a low SES, which was assessed on the basis of their parental occupation and housing quality as defined both by the French National Institute of Economic and Statistical Information and by the French Land Tax Collection Office. Parents of the low SES students were typically employed as manual laborers, low grade administrators, or unemployed, and housing quality for these families was rather low. Parents of the high SES students typically held positions such as manager, researcher, college professor, and housing for these families was rather comfortable.

Procedure. During school hours, a female experimenter met with students in a regular classroom. Students received six profile sheets, each corresponding to one of six (fictitious) targets of the same age as themselves who, it was said, have responded to several questions about their possessions and cultural activities. These questions were :

(1) "Do you go skiing ?", (2) "Do you have a minitel 1 at home ?", (3) "Do you have a calculator to do your homework ?", (4) "Do you often go to the cinema ?", (5) "Do you have a computer connected to the Internet in your bedroom ?", and ( 6) "Do you have 500 francs (about 85 US dollars) a month for your pocket money ?". The profile sheets (given in a different random order to each student) described the way each target answered each question (by "yes" or "no"). They were constructed such as: (i) The extremely low SES target responded "no" systematically, (ii) the very low SES target responded "yes" only to question 3, (iii) the low SES target responded "yes" only to questions 3 and 4, (iv) the high SES target responded "yes" to questions 1 through 4; (v) the very high SES target responded "yes" systematically except for questions 5, and (vi)

the extremely high SES target responded "yes" to each question. The rationale underlying this material was simple: The more the targets were associated with positive answers, the more their SES could be evaluated as high.

Dependent measures. Students were asked to assess each target's SES on a scale ranging from 1 (very low SES) to 7 (very high SES). Students were also asked to rate how much each indicator represented a high SES on a scale ranging from 1 (not at all) to 10 (very much). This additional measure was needed to know exactly how students perceived the weight of each SES indicator (this weight is indeed not necessarily the same for each indicator: e.g., Has the possession of a calculator the same SES meaning, compared with the possession of a computer ?).

Results and Discussion

Target SES ratings. These data were examined via a mixed Analysis of Variance (ANOVA), with students' SES (Low vs. High) as a between subject factor and the six Targets (ranging from extremely low to extremely high SES) as the repeated measure.

This analysis 2 revealed only a main effect of Targets, F (5, 390) = 1071.03, p < .0001

(h 2 = .93) (see Figure 1). Polynomial contrasts indicated that the corresponding linear trend was significant, t(80) = 57.47, p < .0001. Multiple pairwise comparisons (Bonferroni adjusted) indicated that all targets differed significantly from each other at p < .01.

Figure 1 about here

Perceived weight of indicators. These data were also examined via a mixed ANOVA, with students' SES (Low vs. High) as a between subject factor and the six Indicators as the repeated measure. This analysis revealed only a main effect of Indicators, F (5, 390) = 101.54, p < .0001 (h 2 = .57), suggesting that students did not attribute the same weight to each indicator (see table 1). Multiple pairwise comparisons (Bonferroni adjusted) revealed significant differences (p < .05) between almost all indicators. Only " computer " and " pocket money " on one hand, and " Minitel " and "cinema " on the other hand were not perceived as significantly different from one another.

Table 1 about here

As expected, the more the targets were associated with positive answers, the more their SES was evaluated as high, and this was true both for the high-and for the low-SES students. Likewise, the way students perceived each SES indicator (their weight regarding SES) was consistent with their (and with our own a priori) categorization of the targets. Taken together, these preliminary findings showed that the way the six targets were constructed made sense for the students and, therefore, could be used in further studies with similar participants. For clarity, the results of these studies (Study 1 and Study 2) will be discussed in the General Discussion section.

Study 1

Method

Participants. Sixty-eight students (33 females and 35 males, aged 13 to 16) from 3

French middle schools volunteered to take part in this study without receiving any credit for their participation. They were run in large groups ranging in size from 18 to 30 persons and were equally distributed in four conditions according to their SES (low vs.

high) and achievement level (low vs. high). Students' SES was determined as in the preliminary study, and their achievement level was based on their recent performances in Mathematics, Physics, French, History, and Foreign Language. Whereas the average grade was always under 8.5 for the low achievers, it was always above 13 for the high achievers on a scale ranging from 0 to 20 (excellent).

Procedure and Design. During school hours, a female experimenter met with students in a regular classroom. As in Baron et al.'s (1995, p. 310) investigation, participants were informed that the present study was designed to develop academic assessment procedures measuring highly specific academic skills, such as memory, in perspective with students' SES. They were then instructed to pay close attention to the way other students (the targets) of their age responded to several questions (see the preliminary study) because they would have to predict their memory ability. In order to receive honest answers, it was said that participants' answers would remain anonymous.

Dependent measures. After reading each profile sheet, all participants predicted targets' memory ability on a 6-point scale ranging from 1 (very low) to 6 (very high).

Because students may be more reluctant to make differential ratings when judging abilities rather than social attributes (Bar-Tal, Raviv & Arad, 1989), no middle point was provided so that they were forced to favor one side of the scale. Students also rated the confidence of their predictions on a 7-point scale ranging from 1 (not at all) to 7 (very much). They were then debriefed and thanked for their participation.

Expectations. If the SES stereotype about cognitive abilities is consensually used, then the higher the targets' SES, the higher memory ability the students would predict regardless of their own SES and achievement level. As suggested earlier, however, the use of this stereotype may also depend on whether it is consistent or inconsistent with the high and the low SES students' achievement level. On this alternative basis, it can be expected that only the students whose SES and achievement level are consistent with the stereotype (i.e., the low-SES students who are low achievers and the high-SES students who are high achievers) would make use of it in their predictions (i.e., would display the tendency described as general in the previous hypothesis).

Results and Discussion

Students' Predictions of targets' memory ability. These data were examined via a mixed ANOVA with students' SES (High vs. Low) and Achievement Level (High vs.

Low) as between subject factors and the six Targets (ranging from extremely low to extremely high in SES) as the within subject factor (while using the polynomial contrast method).

The three-way interaction alone was significant, F(5, 320) = 3.34, p < .006 (h 2 = .05) (see Table 2). This interaction came from the fact that the linear trend for Targets (i.e., the higher the targets' SES, the higher memory ability predicted) was significant only for the low-SES students who were low achievers, t(17) = -2.1, p < .05. The corresponding means (see first row of Table 2) increased progressively from the Extremely Low-SES Target to the High-SES Target and were quite high and homogeneous (M = 4.64 in average) from the High-SES to the Extremely High-SES Targets.

Table 2 about here

Confidence data. The same analysis (mixed ANOVA) as before was used on these data. No effects were found significant. All students were fairly confident in their predictions (M = 4.23, SD = 1.25).

That the SES bias emerged only in the low-SES students who were low achievers suggests that it can be sometimes restricted to those for whom the stereotype is both consistent with their SES and performance history and relatively self-threatening. For clarity, however, the meaning of the present finding will be examined in the general discussion section. Let us now describe the next study and related findings. Do the low-SES students who are low achievers also infer more attributes (possessions and cultural activities) for the targets whose memory ability seems to be higher ?

Study 2

Method

Participants. A new sample of sixty eight students (36 females and 32 males, aged 13 to 16) from 3 different but similar (relative to Study 1) French middle schools were selected for this second study. Once more, students were run in large groups ranging in size from 20 to 30 persons and were equally distributed in four conditions according to their SES (low vs. high) and achievement level (low vs. high), which were assessed as previously.

Procedure and Design. The general instructions were exactly identical to those in Study 1. In this new study, however, the six fictitious targets varied in their memory ability. This ability, it was said, had been assessed from a memory test (on which no information were given). Targets' score on this test ranged from 70 (the lowest score) to 110 (the highest score). The six questions pertaining to targets' SES were also presented but without providing the targets' answers.

Dependent measures. Students had to predict these answers and, therefore, had to predict targets' attributes (possessions and cultural activities). Then the sum of positive answers (or attributes), as they were weighted in the preliminary study (see Table 1),

were calculated for each Target. This sum resulted in a SES score for each target, which could vary from 0 (students predicted that the target answered "no" systematically) to 37.4 (the sum of all means in Table 1 when students predicted that the target answered "yes" systematically). Finally, students also rated the confidence of their predictions on a scale ranging from 1 (not at all) to 7 (very much).

Results and Discussion

Students' Predictions of Targets' attributes. These data were examined as before, via a mixed ANOVA with students' SES and Achievement Level as between subject factors and five Targets (ranging from 70 to 110) as the within subject factor (while using the polynomial contrast method). The main effect of Targets was significant, F (4, 256) = 7.27 p < .001 (h 2 = .10): The higher the targets' memory score, the more attributes students predicted. This linear trend, however, was qualified by an interaction between students' SES and Targets, F (4, 256) = 10.24, p < .0001 (h 2 = .14). This interaction came from the fact that the linear trend for Targets was significant only for the Low-SES students (regardless of their achievement level), t(34) = -7.23, p < .0001.

Table 3 about here

Confidence data. The same analysis (mixed ANOVA) as before was used. No effects were found significant. Once more, all students were fairly confident in their predictions (M = 4.15, SD = 1.18).

Once more, the low-SES students generated stereotype-consistent inferences: The higher the targets' memory score, the more possessions and cultural activities these students inferred. In contrast with Study 1, however, these inferences emerged regardless of the low-SES students' achievement level.

General Discussion

The present studies tested whether students' SES and academic achievement level moderate their use of the SES stereotype (i.e., the belief that the low-SES individuals are intellectually inferior to their high-SES counterparts). In Study 1, students were given social class information (i.e., possessions and cultural activities)

about several targets and were then asked to infer these targets' memory ability. In Study 2, they were given targets' memory performance information and were then asked to infer these targets' possessions and cultural activities. In both studies, only the low-SES participants generated stereotype-consistent inferences: The higher the targets' SES, the higher memory ability inferred (Study 1), and vice versa, the higher the targets' memory performance, the more possessions and cultural activities inferred (Study 2). Results differed from Study 1 to Study 2, however: Whereas these stereotypic inferences emerged only with the low-SES students who were low achievers in Study 1, they were found regardless of the low-SES students' achievement level in Study 2.

Several points must be made. First of all, the present findings can be taken as evidence that the high-SES students do not produce the SES bias when only social class information are available (Study 1). Not only did these students not infer targets' performance from their social class attributes in Study 1, but they did not make stereotype-consistent inferences either when asked to infer these attributes from targets' performance level in Study 2. Exactly how can the lack of SES bias be explained in the high-SES students ? Because they provide concrete evidence that the SES stereotype does not always depict reality, the high-SES students who are low achievers (as well as the low-SES students who were high achievers) may have been quite reluctant to use this stereotype. Although they themselves constituted stereotype-consistent evidence, however, the high-SES students who were high achievers did not use it either. It could be that the high-SES students made stereotype-consistent inferences (both in Study 1

and Study 2) but chose not to report them because of the apprehension that these inferences would be regarded as unjustified (see also [START_REF] Darley | A hypothesis-confirming bias in labeling effects[END_REF] for a similar suggestion). In line with this, [START_REF] Bar-Tal | Effects of information on student-teachers' stereotypic perception of pupils[END_REF] pointed out that whereas teachers readily use stereotypical beliefs to judge students' social attributes, they may be more reluctant to do so when judging intellectual characteristics (as apparently did the low-SES students who were high achievers). In the present case, however, the high-SES students seemed to be reluctant to make all kind of stereotype-consistent judgments! An alternative explanation is that these students did not link the targets' SES and memory ability because admitting such a link would lessen the importance of their own personal abilities. Several studies (e.g., [START_REF] Bourdieu | La distinction[END_REF][START_REF] Lorenzi-Cioldi | Individus dominants et groupes dominés[END_REF][START_REF] Lorenzi-Cioldi | Représentations sociales de catégories socio-professionnelles: Aspects méthodologiques[END_REF] indeed revealed that dominant or high-SES individuals perceive themselves as relatively unique and completely autonomous with regard to their SES and the possible advantages related to it. Not only do these individuals apply this perception to themselves, but they also minimize the role of SES as a causal factor regarding others' performances. This tendency may help explain why the high-SES students did not make stereotypic inferences in the present studies. This does not mean that the SES stereotype does never drive these students' judgments. The results of past research [START_REF] Baron | Effects of behavioral and social class information on social judgment[END_REF][START_REF] Darley | A hypothesis-confirming bias in labeling effects[END_REF] indeed suggest an intervention of the SES stereotype in the high-SES students when ambiguous performance information (about targets) are made available. Once more, however, participants' SES was not clearly specified in the previous studies. Future research, therefore, is needed to clarify this particular point.

What the present data suggest is that these students, when they are selected from typical SES indicators and then faced with a situation of judgment where only social class information is available (Study 1), are not likely to make use of the SES stereotype.

Likewise, inferring higher social class attributes from higher performances seems not typical of the high-SES students (as suggested by Study 2). Thus, an important message from our data concerns the generalizability of the SES bias when only social class information is available: This bias seems unlikely with the high-SES students in this condition, as also reported by [START_REF] Darley | A hypothesis-confirming bias in labeling effects[END_REF]. As suggested earlier in this paper, that the SES bias approached significance in Baron et al.'s (1995) Study 2 (where it was assumed that only high-SES students were selected) could be due to a substantial minority of middle-class students (who seemed more sensitive to the SES bias in their first study) who were incorrectly identified as high-SES students. Consistent with this, the use of typical SES indicators did allow us to exclude middle-class students from the group of the high-SES students, and the SES bias did not occur with this particular group.

Second, exactly how do the low-SES students behave when they are faced with only social class information had been neglected in past research. It seems now clear that in this condition the SES bias occurs with these students (as with those from the middleclass in past research), at least when they are low-achievers. At first glance, the use of a potentially self-threatening stereotype may seem surprising. That the low-SES students' academic performance history was consistent with the SES stereotype, however, may help explain this use. Furthermore, and in contrast with their high-SES counterparts, the low-SES individuals are especially likely to define themselves from the characteristics of their social groups or social categories [START_REF] Lorenzi-Cioldi | Individus dominants et groupes dominés[END_REF][START_REF] Lorenzi-Cioldi | Représentations sociales de catégories socio-professionnelles: Aspects méthodologiques[END_REF]. The low-SES students, therefore, were the most likely to admit a causal link between people's SES and cognitive abilities, as defined by the SES stereotype. The perception of this link could also correspond to a self-protective goal in the low-SES students who were low achievers. As suggested by [START_REF] Kelley | The process of causal attribution[END_REF] discounting principle, explaining people's cognitive abilities by their SES can help eliminate more individuating causes (personal abilities) for explaining one's own performances. This stereotypic link between cognitive abilities and SES seemed to be less salient in the low-SES students who were high achievers, as suggested by the lack of SES bias with these students in Study 1. In Study 2, however, both groups of students made stereotype-consistent inferences. In line with this, Croizet and Claire (1998) have shown that the SES stereotype in fact interferes with the low-SES students' intellectual performances in specific situations: These performances were inferior when the SES stereotype was made salient, compared with when it was not activated, regardless of the low-SES students' academic achievement level. Our own data can also be taken as further evidence of the strength of the SES stereotype in the low-SES students.

Third, the present studies have their own limitations. In contrast with past research on the SES bias [START_REF] Baron | Effects of behavioral and social class information on social judgment[END_REF][START_REF] Darley | A hypothesis-confirming bias in labeling effects[END_REF], these studies neglected the presence of ambiguous individuating (performance) information. As a consequence, how would the high-and low-SES students behave when faced with such information, compared with when only social class information is available, remains unclear. On this point, however, the results of past research are unclear as well. [START_REF] Darley | A hypothesis-confirming bias in labeling effects[END_REF] selected students who came from a high SES background (as assessed from the prestige of their university --Princeton), and the SES bias was significant only in this ambiguous information condition (it was not when only social class information was made available --as in the present studies). [START_REF] Baron | Effects of behavioral and social class information on social judgment[END_REF] Finally, despite their limitations, the present results have interesting implications.

One of them is related to the possible intervention of the SES stereotype in the low SES students' self-efficacy beliefs and academic achievement level. These students, especially those who are low-achievers seem to believe that students like themselves are intellectually inferior to those with higher SES. This stereotypic belief may undermine the low-SES students' level of perceived self-efficacy which, in turn, may decrease their academic performances. [START_REF] Schunk | Self-efficacy and achievement behaviors[END_REF] reported that students' belief in their efficacy for learning predicted their rate of problem solutions during instructional sessions as well as their academic skills. As revealed by regression analyses, this belief made unique contributions to increment academic attainment over and above instruction, and path analyses established the causal role of efficacy beliefs in the development of academic competencies (see also [START_REF] Multon | Relation of selfefficacy beliefs to academic outcomes: A meta-analytic investigation[END_REF][START_REF] Zimmerman | Self-efficacy and educational development[END_REF]. In a recent study [START_REF] Huguet | Social comparison choices in the classroom: further evidence for students' upward comparison tendency and its beneficial impact on performance[END_REF], these beliefs also predicted students' course grades at the second and third trimester (T2 and T3, respectively) in all academic courses. Self-efficacy beliefs also have proved influential in students' level of effort, persistence, and choice of activities (e.g., [START_REF] Schunk | Modeling and attributional feedback effect on children's achievement: A self-efficacy analysis[END_REF].

Thus, because of its influence on perceived self-efficacy, the SES stereotype may affect the low SES students' academic achievement level as well as motivation.

These students, therefore, especially those who are low-achievers (who are the most likely to make use of the SES stereotype) deserve special attention. Several strategies can be used in this perspective. For example, teachers can encourage them to compare themselves with slightly superior students from the same socioeconomic background.

These comparisons may have at least two advantages: First, by increasing the salience of inconsistent-stereotype evidence, they would help the low-SES students who are low achievers to call the SES stereotype into question (see also [START_REF] Blanton | The effects of in-group versus out-group social comparison on self-esteem in the context of a negative stereotype[END_REF] for a similar reasoning in the context of another stereotype about African-American females). In line with this, the low-SES students whose achievement level was inconsistent with this stereotype (i.e., the high-achievers) did not produce the SES bias in Study 1. Second, these comparisons would also lead to better performances.

Several studies [START_REF] Blanton | When better-than-others compare upward: Choice of comparison and comparative evaluation as independent predictors of academic performance[END_REF][START_REF] Huguet | Social presence effects in the Stroop task: Further evidence for an attentional view of social facilitation[END_REF]Huguet et al., 2001) have shown that slightly upward comparisons facilitate students' performance, at least when they are made with others who are similar on attributes perceived as related to the task at hand. The present data show that the low-SES students perceive SES as an attribute related to academic performances (a central feature of the SES stereotype). Comparing themselves with more successful others from the same socioeconomic background, therefore, would result in better performances in these students. The reasons why upward comparisons might result in improved performance are numerous. For example, observing another person who has proficiency at a task can reveal useful information about how to improve (e.g., [START_REF] Buunk | Social comparison and occupational stress: The identification-contrast model[END_REF][START_REF] Taylor | Social comparison activity under threat: Downward evaluation and upward contacts[END_REF]. Seeing another person succeed may also increase the motivation to improve [START_REF] Huguet | Social presence effects in the Stroop task: Further evidence for an attentional view of social facilitation[END_REF][START_REF] Huguet | The social influence of automatic responding: Controlling the uncontrollable[END_REF][START_REF] Seta | The impact of comparison processes on coactors' task performance[END_REF]. Finally, observing others doing well can endow individuals with a sense of their own potential (e.g., Buunk, Collins, Taylor, Van Yperen, & Dakof, 1990), and this can raise self-confidence and feelings of self-efficacy at the task.

These positive effects, however, are less likely to occur when students believe that they are not able to successfully execute the behaviors required to elevate standing relative to their more successful comparison others (i.e., those who perceive that their degree of control over their status relative to the comparison targets is relatively low;

see Huguet et al., 2001). This is why special attention should also be paid to the low-SES students' conception of intelligence: The influence of the SES stereotype may be maximized in those who perceive their intelligence as stable, compared with those who perceive it as relatively malleable. Consistent with this, recent findings [START_REF] Aronson | Reducing the effects of stereotype threat on African American college students by shaping theories of intelligence[END_REF] show that self-threatening stereotypes do no longer interfere with academic performance when students' believe that their intelligence is malleable (rather than stable). In other words, by emphasizing the malleability of intelligence, teachers may help the low-SES students (especially those who are low achievers) resist to the negative influence of the SES stereotype.

In conclusion, it can be reasonably assumed that this stereotype plays an active role in the construction of the low-SES students' academic history: Its strength among these students may lead to stereotype-consistent inferences about oneself and others, which may lead to poorer performances, which may themselves maintain the salience of the SES stereotype and its negative effects on performance, and so forth. Combined with other findings, which revealed the crucial role of students' prior academic experiences in the determination of their current classroom performances [START_REF] Brunot | Performance Feedback and Self-Focused Attention in the Classroom: When Past and Present Interact[END_REF][START_REF] Huguet | Geometry versus Drawing: Changing the meaning of the task as a means to change performance[END_REF][START_REF] Monteil | Cognitive performance and attention in the classroom: An interaction between past and present academic experiences[END_REF]Monteil & Huguet, 1999), this conclusion leads toward investigating cognition in perspective with the temporal -autobiographical dimension of human beings, that is, with their social and personal history.

Answers Pattern of the Fictitious Targets

  assumed that their students came from either a middle (Study 1) or a high (Study 2) socioeconomic background, and the clearest SES effect on judgments of academic ability was found when only social class information was provided. No doubt: Including both conditions (social class information vs. social class plus ambiguous performance information) is certainly needed when studying the role of perceivers' own SES in the SES bias. Combined with the use of typical SES indicators (as in the present studies), this inclusion would allow clearer conclusions. Past research (i.e.,[START_REF] Baron | Effects of behavioral and social class information on social judgment[END_REF] also included relatively unambiguous performance information, and the SES bias was systematically eliminated in this condition. Can such information also eliminate the SES bias in the low-SES students (especially those who are low achievers) ? This also remains an open question both in our studies and in past research.

Figure 1 :

 1 Figure 1: Students' Ratings of the Targets' SES as a Function of the Targets' Answers

  Students' Predictions of targets' memory ability (and standard deviations) as a Function of Targets' SES, and Participants' SES and Achievement Level

				Table 2
	Participants				Targets' SES
	SES	Achievement	Extremely	Very low	Low	High	Very high Extremely
		level	low	Table 1				high
			Perceived weight of Indicators
	Low	Low	2.88		3.41	4.17	4.76	4.76	4.41
		(n = 17)	(1.86)		(1.62)	(1.66)	(1.03)	(1.14)	(2.00)
							Weights
		High	3.47		4.23	4.76	4.17	3.29	3.41
	Indicators number and label			M		SD
		(n = 17)	(1.80)		(1.35)	(1.10)	(1.13)	(1.16)	(1.77)
	Item 3-A calculator				3.5 a		2.04
	Item 4-Cinema High Low	4.05		4.23	4.6 b 4.29	4.29	1.90 2.94	2.70
	Item 2-A Minitel at home				5.5 b		1.85
		(n = 17)	(1.92)		(1.35)	(1.16)	(1.10)	(1.14)	(1.57)
	Item 1-Skiing				7.0 c		1.98
	Item 5-A computer connected to Internet High 3.82	4.17	8.3 d 4.53	4.53	2.14 3.58	3.29
	Item 6-500 Francs a month for pocket money (n = 17) (1.30) (1.01)	8.5 d (1.10)	(1.00)	2.07 (1.00)	(1.57)
	Note. Means not sharing a common letter differ at p < 0.05.

Table 3

 3 Students' Predictions of Targets' SES (and standard deviations) as a Function of Targets' Memory Performance, and Participants' SES and Achievement Level

		Participants		Targets' Memory Performance
	SES	Achievement level	70	80	90	100	110
	Low	Low	11.56	12.20	17.19	21.25	23.35
		(n = 17)	(4.56)	(4.40)	(6.02)	(6.32)	(6.57)
		High	12.26	14.52	17.86	19.89	23.15
		(n = 17)	(7.78)	(4.82)	(6.90)	(6.21)	(6.74)
	High	Low	18.95	17.51	19.34	19.13	18.90
		(n = 17)	(11.52)	(6.66)	(4.79)	(5.77)	(10.14)
		High	20.43	19.93	18.46	16.46	18.65
		(n = 17)	(9.41)	(6.76)	(6.71)	(8.13)	(7.58)

NOTES

1 A minitel is a French telecommunication system home-based terminal. 2 The assumption of sphericity (evaluated via Mauchly's test) being slightly violated, the Greenhouse-Geisser index was used in the present study (cf. [START_REF] Tabachnick | Using multivariate statistics[END_REF]. Because the use of this index did not change the results, the non-adjusted values are reported here. Corresponding non-parametric tests also led to the same effects. This is also the case for all ANOVAs presented in this paper.


Keywords: Risk, uncertainty, home security, expected utility, non-expected utility, OECD

1 My thanks to Serge Pahaut for our many fruitful discussions

Introduction 2

Certain areas related to the topics under discussion here lie outside my field; for instance the evaluation of risk assessment and security deficiencies in the transport sector. What has convinced me of the importance of this subject are a few very general conclusions, indeed I would say, impressions, that I have drawn from the truly remarkable development of our powers to analyse the risk decision-making process over some years now.

In this paper, the term "lack of safety" is often used with reference to the management of risks arising from intentionally malicious acts 3 . The costs of security in this sense of the term are an element of every transport budget today. In addition to the costs of prevention, surveillance and forecasting, the costs of the potential damages arising from such acts will also have to be taken into consideration from this point onwards.

The events of 11 September 2001, which accelerated this trend, should suffice to convince us that, from now on, the consequences of such damages will be on a scale comparable to the costs of war. Some authors have taken issue with the idea that there would exist some scale chasm between these two types of phenomena. Actually, the figures for wars connected with terrorism today are reported to be somewhere well in excess of millions of billions of dollars. This is what is to be gathered from General Haig's response (2003) that terrorism is now a branch of warfare. In a sense that we have yet to define, these are strategic decisions. The criteria which, in the eyes of the US Government, linked this attack to the wars that followed have actually more to do with retaliation than with simply estimating the consequence of the costs and benefits of a prevention policy, where these can be calculated.

Hence, the additional expenditures incurred in many areas since the events of 11 September 2001 are not purely consequences that are more or less costly or more or less acceptable. That is because they are linked to the part played by these events in exposing vulnerabilities that were, and still are, largely underestimated 2 My thanks to Serge Pahaut for our many fruitful discussions together over the past few years. Nathalie Picard and Jean Picard submitted useful suggestions for improving the quality and readability of this paper. Lastly, Kurt van Dender also helped me to improve its presentation. 3 The lessons of history and anthropology warn us that we had best not draw the rash conclusion that any two things are linked unless they show a link everywhere they occur. As a concept, security actually has its roots deep in the prehistory of law. Whatever the interpretation proposed, in many civilisations it harks back to some solemnised form of public ritualised practice. Here, one should at least note that the different mutations that this family of practices has gone through extend to much more than the socially guaranteed recognition of individual entitlement as it relates to the power to buy and sell freely. In other words, while the object at stake often attracts enemies, it does not necessarily have an owner.

-and to a desire to retaliate. The fact is that the logic of deterrence -a field in which the military man is more at ease than the economist-can simply not be reduced to the calculation of prevention and surveillance costs.

Viewed in this light, it is easy to see why economists do not feel very able to contribute to the definition of deterrence policies. Nevertheless, what economists can do is to approach the problem from the other end. Instead of calculations as to the logic of the decision, they can endeavour to propose an estimate of the various costs. This was what started off discussions on the costs of the US War in Iraq in budgetary terms: with their estimate of USD 3 000 billion, [START_REF] Stiglitz | The Three Trillion Dollar War[END_REF] prompted a substantial revision of previously accepted estimates of these costs4 . This brings us up against the limitations of cost-benefits analysis, as Stiglitz concluded in a bid to counter claims that he had neglected5 the latter approach: costs were very substantially higher than had been stated by US political leaders. More importantly, with reference to benefits, Stiglitz said plainly that there were none that he could see. As we are reminded by the work of the founders of prospective analysis in economics -of whom we will say more below-the strategic approach does more than simply extend extrapolation calculations: it complements them.

Cost-benefit and prospective analysis

The aim of cost-benefit analysis is to evaluate the outcomes of a given project. Choices may be absolute (a proposed project will either be selected or not) or relative: there are two competing projects and decisionmakers must determine which alternative they consider most appropriate.

The work of planning and prospective analysis -some fine exercises of which were seen in the last century-requires that the implied relationships be handled by a less binary process. This means that there will be several series of decisions to take: which projects for which programme, when and how their execution can be slotted into a job schedule, which methods of finance seem appropriate, which supporting measures will be required, to mention but a few. This is very far from a straightforward all-or-nothing answer.

By now, we are well used to reading that putting each programme in place requires the co-ordination of a series of sub-programmes and the need for cross-transactions with other programmes. The 20 th century talked a great deal about priority ranking in this respect, a technique that ensures that nothing is missed out.

Over the past few decades we have learned to associate various sets of risks with these programmes: risks associated with fluctuations in demand, sudden changes in the costs of production factors, setbacks in completion time and the risk of seeing programmes appear which could fully or partly replace those on which firm decisions have already been taken, etc. These risks are themselves associated with others: the vagaries of the economic cycle, more or less sudden shifts in the price of raw materials, hitches in the course of the project. The list is endless, we know, but in times of escalating hostilities, any omission will only too readily be seen -with the virtue of hindsightas criminal negligence or sheer stupidity, even when the omission, whatever it was, had genuinely been said insignificant at the time.

Here, we have learned to identify some risks that are foreseeable and quantifiable and some that are foreseeable but difficult to evaluate. Lastly, as evaluation methods progress, it often seems with hindsight that other risks should have been included in an evaluation, but were simply omitted.

For instance, it has been axiomatic for centuries now that the construction costs of large-scale infrastructure projects are frequently revised upwards in the course of the project. One particular difficulty -and every error here is costly-is to ensure proper synchronisation of the work of several teams operating together: a construction site, by definition, is not like a routine production-line operation. Therefore, it is rather difficult to see how prospective cost-benefit analysis studies can quietly ignore these risks. Moreover, once built, the infrastructure will inevitably face greater intermodal competition.

Clearly, these observations are well within the grasp of any first-year student who has just signed up for an industrial economics course. They have also entered into the folklore of observers of collective decisionmaking6 . So as not to make these -suddenly more human-decision-makers look more fallible than they actually are it is only reasonable to make allowances, too, for the host of different agents involved in this kind of large-scale investment project.

Something else that we have known for centuries is that business banks are not necessarily averse to cost increases in construction programmes under way. After all, their primary function in this context is lending -not repaying. Any inconsistencies that become obvious after the event stem largely from forgetting, when we look back, that the mutual interests of the principals only ever partially coincided.

In these times of widespread crisis, the issue will not be if or how the entrepreneurs in question could or should have done more to meet specifications, often drafted after the fact, once the fatal failure has been noticed. Rather, it will be whether we can afford the time to take on board these consequences, which at one time were genuinely negligible, but later turned out to be a factor in the accelerated changes that our world is now going through.

To put it simply, assuming that whatever issue challenges us is one that is identifiable and measurable, then the new economics of risk management may well not be of any great help. For example, there is no need for experimental economics procedures to set up navy patrols around the Horn of Africa. Giving the green light to the competent admiralties should suffice.

That said, an economist's role is to acknowledge an interesting problem in that very area where his skills are seldom acknowledged, it seems, and so he would be delighted to be allowed to formalise the symmetries between the tactics available to victims, pirates and States in terms of models borrowed from game theory. However, the economist also has some more general comments to add.

The difference between deterrence and prevention, the reason that the military man will often instinctively silence the economist, does not actually come under the scope of cost-benefit analysis. This is because the military man has the resources available to calculate an escalation to extremes. Typically, this is not really reducible to the criteria an economist would use, since the military man's rationale is to break the other whatever the cost.

These tactics are indeed not unfamiliar to the economist. It is the underlying rationale, more than calculation of the relevant criteria, that may give his partners pause for thought. For instance, a firm may undercut prices in order to outdo its competitors. Certainly, an economist can help to make sure that such a strategy is as low-risk as possible. He can also describe it, since he has the experience to understand it. The aim is to describe and prevent behaviour aggressive enough for their prospective analysis to include the risk of certain mutual destruction. That is the problem we have to weigh up. Let us now state it in somewhat more provocative terms: it is the right time, and may even seem reasonable, to say that urgent consideration must be given to one straightforward question: do we really have to go grudgingly, as it were, into the globalised economy, into one crisis after another peopled by elusive enemies? The economist has a few reminders to give in this regard.

We have just seen that there is little sense in expecting any second-rate review aimed at bringing those responsible for this or that programme before the Court of History. There would be little point, for instance, in accusing mortgage-lending banks of being insensitive to the rapidly dissuavsive difficulties experienced by borrowers in meeting repayment terms. Nonetheless, it is true that the escalating defaults on mortgage payments and the growing inevitability of sales at a loss destabilised the banking market in the end. However, this crisis does not spell the end of the world. Rather, it shows the limits of the role to which economists have too often been confined as the accountants of an ill-justified and ill-run system.

On the other hand, we shall see how increasingly urgent it is to have a process that strengthens our sensitivity to the losses incurred, but also to the sacrifices made and the many reactions of the working populations mobilised in the modern economy in the wake of the shortly-expected completion of market openness policy: the foreseeable closure of those markets. Important as it was to tempt to master the management of the internal risks of a given programme or of an economy bounded by identifiable reference points, it seems every bit as misguided to want to transplant the methods of this policy to areas which, by definition, we cannot reasonably hope to control. This widespread mistake is one that we risk walking right into today because we do not know what the impact of our activities will be in the outposts of the empire, the four corners of our world. The reason is not that we are any more deserving of scorn or censure than our predecessors, it is just that the world is on the brink of rather rapid and probably rather violent change now that with the mobilisation of Indonesia, Mexico and Brazil after India and China, we have come full circle and done the rounds of all of the major labour-force and consumer catchment areas available.

It is because globalisation will soon be complete that our insensitivity to unfair terms of trade and to the predictable, but unforeseeable, reactions of those concerned is untenable. Evading the issue is a tactic that is becoming a little more antiquated each day. However, in this new world that we are being ushered into by rapid globalisation and its corollariesabout which I will say a few words-I must say from the outset how forcibly I am reminded of Popper's reference to what the barbarian King Pyrrhus of Epirus said about strategy while at war with the Romans: « Another such victory and we … are lost ».

For just a moment, we will try to see globalisation from the perspective of the 1970s. What I wish to do here is to perpetuate the spirit of open, realistic optimism that prevailed when the OECD's Interfutures exercise was conducted 33 years ago now. What were in substance the reasons adduced for this program? As you will remember, the proponents of this analysis and assessment project -holding that the internal proletariat was to be successfully integrated in modern societies, thanks to a constantly growing middle class-proposed to raise the issue of the external proletariat: «more than 120 countries with rapidly growing populations, already accounting for three-quarters of humanity, to which the industrialised nations have a collective responsibility» [START_REF] Albert | Interfuturs vingt ans après', in Décision, prospective, auto-organisation[END_REF]. But trends in both capital and migration flows over recent years demonstrate that the prevalence of an attitude of insensitivity to the changes that are happening now has sharply increased among both public opinion and decision-makers.

The insensitivity, not to say incredible hardheartedness of the past two decades has such an impact on us that we have to belabour the point, in order to make this change in ideas and attitudes more apparent. Who is so bold as to say that, over the past twenty years in a certain number of countries in Africa, there has been a decline in the number of children in school, and not just relative to the school-age population, but in absolute terms? For a generation, the dominant « Trade not Aid » motto, which promotes trade with entrepreneurs in poor countries rather than increasing up support for needy populations, has marked a retrograde trend. It seeks to extend prematurely, to countries on the farthest fringes of our economy, processes which, incidentally, our experts did not invent, but which grew out of the countries of Asia and South America: developing the local middle classes, boosting agricultural exports, freezing agrarian reforms and criticism of land redistribution. These policies have a quantified target: the sadly famous 0.7 per cent, which our governments should be earmarking for aid to the poor countries of the Third World, said by some, when it was introduced, to be a reduction compared with budgets and policies in colonial times. This is a controversy beyond the scope of this paper.

Three models for managing the future I will now turn for a moment to contrasting descriptions that address the future. Along the way, I invite you to reconsider extrapolation and strategy procedures, two familiar approaches, which many people seem to think exhaust all the possibilities. This is true, in a way, since if they are taken as opposite extremes, however artificial this often is in practice, they do appear to cover all of the approaches between them. This is a dangerous mistake to make for one simple reason: both procedures often -so often that one may ask why -omit an approach that is nevertheless common to both of them: sensitivity. Let me explain.

First, there is extrapolation, in a way the more naturalistic of the two, as we shall see. For some people, extrapolation is the driving force of forecasting. A forecaster's job is often to extrapolate trends from the known past to a future that is assumed to be uncertain. On the timescale marked out for measurements taken for this purpose, the present is ideally represented as no more than a point, which must not distort the calculations too much.

However, the present does exist; we live in it. That is why good observers, such as Jacques Lesourne, have been keen to repeat that prospective analysis, an exercise which by its very construction is oriented towards long-term, can reduce the pressure exerted on the present by the short term. Extrapolation has been criticised for ignoring freedom, disregarding the undeniable span of the present, the uncertainties related to our imperfect knowledge, etc. These criticisms are interesting, but before addressing them, I would like to give a brief description of the other family of approaches to the future.

From more "interventionist" circles, we have actually inherited a second method of matching what we see with what we forecast. Strategy, indeed, can be described as reversing the order of the ends and the means of extrapolation procedures. What it sees and faces are the objectives that can be ascribed to the future, not the data inherited from the past. What it seeks to be able to forecast are patterns of available investment that will have to be called on in the near future if a given long-term end-point is to be attainable. The challenge that strategists agree to take up is to choose among possible futures, deploying the appropriate resources to best advantage. Hence, strategists take the opposite tack to forecasters. They endeavour to find out more about the resources of an uncertain present that can be deployed to attain a future that they profess to choose.

As we have said, treating these two theories as opposites is largely artificial: good strategists must know their way around extrapolation, while forecasters have to take strategic interactions between agents into account. Consequently, as I have said, those who advocate either method to the exclusion of the other need to be taught that they are complementary. That is why I wish to say a few words about one strength they have in common. Faced with the conventional opposition of the two, my comments are intended to bring certain echoes of the word sensitivity to life again. The aim of this exercise is to help the actors pay a little closer attention to context: the set of circumstances, by definition complex and underestimated, in which any change carries major consequences.

The keyword here is sensitivity to distant, complex, barely perceptible evolutions: how does one ensure that the signals sent by a world that is in the process of delivering its own future are not unduly neglected when we are busy primarily with the forecasting or monitoring tasks that our local job requires? To state the question in more direct terms: which elasticities are weak today for decision-makers and their advisers but will be critical tomorrow, and relative to which processes? What things are we not paying attention to today, more or less intentionally, that we will inevitably have to think about tomorrow? To take a basic example, we have long counted on the low elasticity of transport demand relative to energy prices, to the point of taking this low elasticity as some sort of universal constant. If we are to survey this problem, a good questionnaire should be able to capture these potentials even before they occur. The variables to be measured and the indicators selected must be carefully calibrated so that they do not conceal what is not obvious [START_REF] Prelec | A Bayesian truth serum for subjective data[END_REF]. While not attempting to try to teach professionals how to draft questionnaires, how many thousands of very expensive ad hoc surveys have been content with reproducing what was alleged to be true?

It must be said that the extrapolation work requires a certain strength of character. It is about putting a name to developments; that is to say, about designating areas where a relevant variable, albeit a third derivative, changes sign. Incidentally, if futurists wish to extrapolate well, they must not be slow to recognise change. For instance, how many authors religiously trotted out the theory that, since transport demand was relatively inelastic to transport costs, one could ignore ranges of values and population subgroups in which highly predictable changes in attitude were already becoming apparent? Futures analysts seem to let themselves become inured to the surprising, if negligible, speed of such changes.

Strategists are more known for their insensitivity. All they can see is the objective, people say. They are capable of steamrolling everything in their path on their march towards destiny. That is certainly not wise, but excess is the hallmark of the strategist.

If there is one thing that risk analysis in major technical projects has been able to teach us over the past few decades, it is that a total lack of sensitivity makes for good actors, in the sense understood in Diderot's Paradoxe sur le comédien : « it is extreme sensibility that makes mediocre actors; it is mediocre sensibility that makes the multitude of bad actors; and it is the absolute lack of sensibility that prepares actors who shall be sublime ». The detachment of the mad scientist contrasts with the chatty tone of the newspaper columnist.

Since extrapolation seemed to ignore the freedom to change, it is quite reasonable to want to include this freedom in forecasting: one day US consumers buy fewer four-wheel drives, for example. However, it may prove decisive, as we can perhaps see more clearly today, even if we are going through a politically and intellectually retrograde period, to look for this more essential function, which I call sensitivity, preparing freedom. We will come back to this point later.

The case for institutions

An ill-defined policy is still a policy. A preference to have no policy is permissible, but in that case, one also has to wager on the chances of success of the « no-policy » option.

As Pascal, a mathematician who was also interested in the decision-making process, explained « …but you must wager. You are embarked »: there is nothing clumsily interventionist about trying to understand the dynamics of an action.

The fact is that economics is not to be confined simply to drafting recommendations for an inescapable but obscure institutional outworld. Where need be, it can also study the environment that produces these institutions, as the vector through which their recommendations are requested, As well as that, over and above the mechanisms of contractual transactions, economists are able to evaluate the impact of the statutes of institutions to which the actors belong on price-setting mechanisms: transactions are negotiated within an institutional framework that is given and liable to change.

What is an institution? Hauriou, the founder of modern institutional studies, will serve as our guide: « A little sociology leads away from the law, much sociology leads back to it ». An institution is a source of law and, at the same time, it is an actor capable of initiatives; it can more easily be described by saying what it is not. An institution is a source of standards, but is not the same as the law and not the same as a contract. A contract has value only because of the interests of the parties to it. The law assigns duties to subjects regardless of their interests. An institution carries out the duty that its mandate assigns to it.

When we speak of statutes, different information asymmetries, powers to negotiate or exercise a veto, what we are talking about are the established, stabilised components of social interactions. Should we try to ignore them? No. Classic theory allowed us to raise profound but simple questions, such as « What is the nature of the firm? », the question raised by [START_REF] Coase | The Nature of the Firm[END_REF] more than half-a-century ago. If the price mechanism were the only way to ensure co-ordination among agents, why would entities such as firms exist at all? This work, which has long been regarded as a « tour de force » of neoclassical theory, was in fact an effort to take the real world into account.

The market itself is an institution, loaded with deeply ingrained historical and local characteristics. Every country lives off a capital of established customs which account in part for the diversity of policy choices that it can make.

One of Coase's fundamental ideas is worth noting: institution is not here in order to breathe a little more soul into an inhuman market. It does more than ensure a little justice and fairness. Primarily, it plays an intrinsically economic role by helping to manage the problem of transaction costs. Contracts are not free bilateral interactions sheltered from any social influence. A world with no memory would be very costly in terms of transaction prices. After all, as the [START_REF] Olson | The Logic of Collective Action: Public Goods and the Theory of Groups[END_REF] paradox demonstrates, the production of a public good is not necessarily always promoting the self-interest of the rational individual. We know that this paradox did not hinder critical thought, as it allowed Olson to illustrate the variable weights of individual and sometimes diverging interests according to group size, for instance, leading to his famous conclusion that small groups could be more effective than large groups in mobilizing individuals. Rousseau, in his Discourse on the Origin of Inequality (1775), paints this logically consistent model: «If a deer was to be taken, everyone saw that, in order to succeed, he must abide faithfully by his post: but if a hare happened to come within the reach of any one of them, it is not to be doubted that he pursued it without scruple, and, having seized his prey, cared very little, if by so doing he caused his companions to miss theirs. »

The new institutional economics of Coase and North revisits this issue in depth since, in their work, not only do institutions influence actors, they are themselves created by the actors' efforts to reduce transaction costs. When a market that has become very fluid spawns relations that are improvised, aggressive and verging on violent, some of the actors will apply the institutional brakes necessary to curb the costs of such improvisation. Institutions, North says, are humanly devised constraints that structure political, economic and social action. In a situation of bounded rationality, he says, it is often rational to fall back on established procedure, available knowledge and a given apparatus; accounting for contingency like this gives economics access the world of ordinary humans.

Therefore, although transactions sometimes generate poverty or revolt, there are no grounds for lazily concluding that this is inevitable. Observation of the actors' behaviour shows that Coase's entrepreneur keeps processes that he could outsource inside the firm, because he sees certain inherent advantages in the firm/institution and in the relationships of synchronisation and subordination that it allows.

Decision theory and its history

« Entre ma passion pour l'histoire et celle pour la modélisation mathématique, je n'avais pas à trancher. La science économique pouvait les satisfaire toutes les deux. » Lesourne, 2000, p. 189-190. (

I did not have to decide between my passion for history and my passion for mathematical modelling, economics could satisfy them both)

Being sensitive to what one risks losing, or what one is already losing, precisely because that loss was for too long considered negligible, and being capable of doing the calculations over again, is an imperative for us today and one that economists are professionally familiar with. In order to understand what is new about this imperative for a certain number of actors battling in business or in politics, I propose to give you a brief review of some recent achievements in risk theory.

Calculating damages from events subject to any given probability distribution raises problems and the formulation of those problems has seen changes over the last few decades. At this point, I propose to make a few short comments on some aspects of these developments in thinking. Decisions on resource allocation under a risky environment often obey today the theoretical model known, in modern terms, as the « expected utility » model. This section briefly reviews the history of our ideas on this subject, which we will see, I hope, are not out of place in this discussion.

The theoretical model for expected utility, outlined by the Bernoulli family in the early years of the 18th century and formalised a century ago by Von Neumann and Morgenstern, corrected classic rationalism and the optimal application of probabilities to decision-making which had prompted the correspondence between Pascal and Fermat in the mid-17th century. The latter had confined themselves to rationalising decisions solely in terms of the expected value of the benefits associated with a set of events, each of which had a given probability.

To go back to our overview and simplify matters, let us first consider the ideal case of a world without uncertainty. If the future development in the economy is certain, it is unique and the actors have no great difficulty in knowing what it is since it can be deduced unmistakably from the present state of affairs. The revenues generated by investments are known and there is therefore no risk, no risk premium, no speculation and no insurance. However, we know that not even Robinson Crusoe lived in that kind of economy. Firms, contracts, institutions and the market can only interact in a world where there is, at the very least, chance and a way of taking it into account: through risk calculations. If allowance is made for chance, then possible events and their consequences are not ruled out, even if we follow policies aimed at excluding them or dealing with them.

Let us now review a few critical steps towards these developments in allowing for the evaluation of possibilities. For the authors who were the founders of probability calculation, Huygens and Bernoulli with Pascal and Fermat, future events are unknown but not their probabilities 7 . Does that cover everything? Do we now just have to add some detailed results into this general theory? No. A counter-example formulated by one of the active figures in the construction of probability calculations very quickly showed that rationality in these calculations could not always be recommended. The Saint Petersburg Paradox, constructed to demonstrate that although an infinite gain over the long run should, under expected value theory, prompt someone to gamble an infinite sum, observation showsunderstandably-that a rational gambler will avoid the extremes to which the rationalist decision leads and, in fact, will quite reasonably bet a relatively small amount. When presenting this paradox, « Bernoulli's nephew », Nicolas, noted at the beginning of the 18th century that if the expected utility of the gain was the only criterion used, as it was for the probability theorists of the 17th century, one would inevitably be recommending choices that no reasonable person would make in practice.

Bernoulli's conclusions were of even more value than his paradox. He concluded that a new concept, that of expected utility, should be introduced. He opened up a new field when he proposed that no estimation of risk could neglect the reverse problem: what is the gain required to furnish a given person a utility about which practically nothing certain can be said since it is so subject to change with circumstances. He continued "Thus, although a poor man generally obtains more utility than does a rich man from an equal gain, it is nevertheless conceivable, for example, that a rich prisoner who possesses two thousand ducats but needs two thousand ducats more to repurchase his freedom, will place a higher value on a gain of two thousand ducats than does another man who has less money than he. » Expected utility models will therefore take account of the decision-maker's attitude by applying a utility function U the sole basis of which are the decision-maker's wealth or gains. While Bernoulli's assertions have, of course, come in for criticism, the fact remains that he opened up a new world to us. In a sense, his intuitions are truer still today than when he first formulated them: for modernists at the end of the 20th century, a concave utility function would come to signify risk aversion; the steeper the curve the greater the aversion. Let me draw your attention to the extremely universal nature of this reasoning. This analysis of perceptions, i.e. the diminishing valuation of successive marginal utilities, enabled the construction of one of the first mathematical functions of valuation behaviour and the introduction of experimental procedures in numerous disciplines.

At this point, I would mention, if I may, the economic theory of diminishing returns on increasing investments or the physiological theory of perception as a function of increments in value of data perceptible to the senses. These highly diverse fields required relentless clarification in order to avoid the emergence of a risky «theory for everything ». We have now arrived at a threshold that enabled 19th century men of science to cross over into the New World of social science. Analysis of the types of attitude that actors have towards risk from the classic curve is not at all anachronistic. For a person who is less tolerant of risk than another, the utility function will be a concave transformation of the utility function of the latter. In the case of people with zero risk aversion, the utility curve will be linear while for others who are risk-seekers, the lack of aversion to risk will show as a convex utility function. to the real ory -in the use they do to provide guity (which ollowing the he same year heory of the Numerous empirical studies conducted in recent decades have demonstrated that there are deviations from the behaviour predicted by expected utility theory. Risk aversion as exhibited by decision-makers proves to be more complex in practice; furthermore, it is related to a new aversion, the aversion to loss, and takes account of the consequences of a sequence of gains and losses.

A short introduction to probability distortion after Kahneman and Tversky may prove useful: events that have a very low probability of occurrence, close to zero, are subjectively perceived as having a higher probability (overestimation transformation), while those with a high probability of occurrence, close to one, are subjectively perceived as having a lower probability (underestimation transformation). Hence, in order to describe the behaviour of a decision-maker in the case of a lottery (x, p), objective probability p is replaced by a probability distortion, applying a probability transformation w(.), strictly increasing over the interval [0,1] where w(0)=0 and w(1)=1. Instead of evaluating the lottery (x, p) by p U(x), it is valued as w(p) U(x), where U(.) represents the person's utility function. Tversky and [START_REF] Tversky | Advances in prospect theory: cumulative representation of uncertainty[END_REF] later extended prospect theory and found that the way in which people tended to distort the probability of an event depends on how they rank that prospect on a scale of order of preference from most to least favourable. The person then works out the cumulative probability of obtaining at least a given sum. Hence, as illustrated in the figure above, if the probability of obtaining at least 1 is actually q=15%, a person will estimate this probability as w(q)=35%, for example. Moreover, if the probability of obtaining at least 2 is actually p+q=50%, people will estimate this probability as w(p+q)=45%. The probability of obtaining between 1 and 2 will therefore be distorted from p=35% to w(p+q)-w(q)=10%.

The curve shown above plots the transformations for risk attitudes is a case of bounded rationality, as it has been known since the seminal papers by [START_REF] Simon | Models of Bounded Rationality[END_REF]. In order to plot this curve, a more complex utility function is introduced that takes other distortions related to subjective evaluation into account. First, we note an asymmetry between the perception of gains and losses: it is immediately apparent that the utility function is concave for gains and convex for losses. There is also some diminishing sensitivity: the impact of some gain variation diminishes with the distance from the reference point. Lastly, the marginal disutility of losses is greater than the marginal utility of variations of the same magnitude in gains. Calculations show that the Option A lottery offers a chance of winning EUR 145, an amount which is higher than the sure gain offered in Option B (EUR 140). The risk premium is therefore EUR 145 -EUR 140 = EUR 5. Generally, it is not enough to explain the choice of Option A by a person whose risk aversion has previously been estimated based on lotteries where the chance of winning was of the order of 50 per cent. This person shows an optimism bias, in that he pictures himself on the « winning side of the divide » and overestimates the probability of winning the « jackpot » of EUR 1 000.

Conversely, there are low-risk situations where losses can be high. Often, we find that there is a pessimism bias which makes people overestimate low probabilities of poor performance and avoid the relevant options more than they should under expected utility theory. For instance, many travellers reacted to the events of September 2001 by avoiding air transport and using the car for long-distance travel instead. As transport by car is much more dangerous than air transport in terms of accidents per kilometre travelled, this was a case of pessimism bias: the consequences were an increase in the number of deaths.

The rejection of options which carry a risk of adverse consequences is amplified by two other phenomena. Firstly, people do not like to be disappointed, i.e. to suffer consequences that leave them less well off compared with a given point of reference. This anchor point can be conditioned by on one's past experience or future expectations. Mathematically, this is reflected in a discontinuity in the derivative of the utility function in or around the reference point. In this case, the slope to the right of the reference point is less steep than the slope to the left: people are more sensitive to a change in outcome when they incur a loss (defined in relation to the reference point) than to a change in gain of the same magnitude.

From the analysis of the data gathered via http://www.RiskToleranceOnLine.com three different patterns of attitude to risk have been found, expressed here in terms of total lottery wins.

1. Risk aversion: respondents do not like risk and are ready to settle for a smaller amount than they had hoped in order to avoid putting it at risk. The reduction they accept is the risk premium. 2. Aversion to loss: with a point of reference of EUR 100, the risk premium for a lottery where there is a possibility of loss (for example, one that offers the same probability of winning EUR 90 or EUR 110) will be higher than for a wins-only lottery (for example, one that offers the same probability of winning EUR 100 or EUR 120). The same person would be ready to pay a risk premium of EUR 5 in the first instance (deterministic win of EUR 95) but only EUR 3 in the second case (deterministic gain of EUR 107). 3. Lastly, people have a tendency to distort low probabilities of very high gains (optimism bias) and high losses (pessimism bias).

Where major risks to society are concerned, a further distortion pertains. It is related to the scale of an incident and to the fact that society seems less able to tolerate major disasters than repeated incidents, even when the total number of victims is the same in both cases. This is an aggregation bias. The figure attached shows experimental data/perception pairs for a certain number of familiar causes of death.

In other words, it seems that society as a whole would more easily tolerate a series of accidents each causing minor damage than a single accident that causes major damage, even when losses are the same: for instance, judging by the various indicators that inform policy discussions or the column inches in newspapers, 5 000 road accidents each causing one death has less of an « impact » on us than five air transport accidents each causing 1 000 deaths. This comparison does not mean that we should resign ourselves to abandoning risk management policies. On the contrary, it is something that more responsible risk management should think about.

Figure 4. Déformation of deaths numbers:in abscissa, actual number of deaths per year for some sets of causes ; in ordinate, estimated number of deaths [START_REF] Lichtenstein | Judged frequency of lethal Events[END_REF].

Quite obviously, these perceptions differ from a normative (expected utility theory) and descriptive (behavioural finance theories, see [START_REF] Thaler | Advances in Behavioral Finance[END_REF] perspectives. Cost-benefit analysis proposes a method for allocating public resources to choices that offer the best combination of efficiency and equity. Resource allocation is also subject to acceptability criteria for investment decisions9 . We have seen that the public's perceptions are subject to perception bias and other anomalies which mean that it is far removed from the rational man whom classic economic theory viewed as taking decisions without bias and free of influence.

Conclusions. Any terrorist worthy of the name has something to lose I will close with these few pointers. While the logic of Aristotle described man as conceived by philosophy, now in a dramatic turnaround, we are attempting to gain a better understanding of real men and women. Psychology and economics have done better than follow this general trend in the scientific approach. Risk calculation is no longer a disembodied normative ideal. Today, it assesses the real-life contexts in which evaluation and decisions take place.

As regards economic transactions, it is institutions (whether Coase's firm, the marketplace of a provincial village or the IMF) that enable us to manage certain objectives that would not result spontaneously from social interactions.

Over the next few years, institutional creativity will be sorely needed. The stability provided will have to offset certain distortions in judgment and preferences, which psychologists and economists have learned to try to recognise today, now that we have moved on from simply establishing normative doctrines of rational action. Institutions allow us not to exploit the fact that the psychological attitudes of our partners can be taken into account10 . They guarantee the viability of situations which, without them, could be disastrous.

In periods of great instability, it can be crucial to remain capable of seeing that negligence, hostility and incompetence are labels that we choose to cling to when we stop negotiating on the basis of partners' preferences and begin to fight with them: people who are negligent, incompetent or hostile are people we no longer negotiate with. Under these conditions, the input from economists cannot be to provide weapons for archaic rituals of execution and expulsion. Before helping to stamp out or control terrorists, before working out a theory that explains the flaws that allow us to predict, repress or explain them, economic science can help us, more simply, to continue to pay attention to the instability that threatens our own analyses and to the distortions that affect our perception of what is at stake and of the probabilities in instable transactions. Hence, economics stands poised to demonstrate that it is now a human science in its own right.

There is much evidence that any group of human beings is capable of dealing with probabilities. The prehistory of games, just like that of rituals, attests to this interest11 . That is why risk -like language, tools, or kinship-can be said to be a constant of human society. This comment has relevance for more than simply theory. It has a bearing on decision-making in an unstable environment.

When groups of humans who are strangers meet, the radical instability of relationships that are neither codified nor institutionalised lead to rapid shifts in stakes that can swing from trade to war and back. A noteworthy analysis by Lévi-Strauss has provided a model for this instability 12 . It is this instability that institutions can channel. The risk of outbreaks of non-negotiable violence -certain of modalities of which have been given the name terrorism --is not external to the society we live in and therefore calls for social, political and economic solutions, not for the technical calculation of prevention or repression.

A memorable anecdote from Roman antiquity relates that pirates sailing in the vicinity of Scipio's home asked if they could pay homage to the great man (Valerius Maximus,30). Informed readers think that it was actually the victor of Carthage they wished to honour; after all, as pirates worthy of the name, they had reaped the benefits of the annihilation of the only great maritime power in the western Mediterranean. Historians shown how barbarians and pirates are invariably an integral part of the economy of the Empire that they appear to be threatening from the outside.13 That is the difficult but necessary analysis that we should preferably be capable of conducting given the extreme events that the current changes in our world are bringing about. Economics could perhaps have some suggestions on the technical problems that this change is bringing. It can most certainly set us thinking.

Figure

  Figure 1. U

Figure 2 .

 2 Figure 2. Probability wheigting function : subjective probabilities w as a function of objective probabililties p (Tversky and Kahneman 1992).

  Figure 3. income ; th point is her

For reference, the amounts are of the order of the annual GDP of the US, which is currently around USD 15 000 billion.

See the discussions on this idea in[START_REF] Viscusi | The Risks of Terrorism[END_REF].

Moreover, this is a theme that has been catalogued by folklorists: the devil offers to build a bridge when its construction falls behind schedule (Folktale AT 1191,[START_REF] Aarne | The types of the folktale[END_REF]

Expected value is obviously not necessarily part of the set of observable events. Hence, in the case of an unloaded, six-sided die, the expected value is 21/6, or 3.5, a figure which does not appear on any side of the die.

This applies particularly to public goods (transport infrastructure, environment infrastructure, etc. see de[START_REF] De Palma | La tarification des transports, Enjeux et défis[END_REF][START_REF] De Palma | Investment and the Use of Tax and Toll Revenues in the Transport Sector[END_REF]Palma et al. , 2008) )

We know that the Vienna School and von[START_REF] Mises | Nationalökonomie. Theorie Des Handelns und Wirtschaftens[END_REF], tried to draw on the logical process of human action, praxeology, to avoid over-psychologising. A properly conducted psychological experiment cannot fail to reveal why it was rational for someone to do one thing or another under this or that set of circumstances.

We could mention the outstanding work done byAscher (1991), which shows how points awarded for different outcomes of a game of chance played by the Iroquois Cayuga are proportional to the probability distributions of these outcomes.

Although this study of models was taken up again in his essay on the Nambikwara Indians and in some passages of Tristes tropiques, its first appearance was during the First World War[START_REF] Lévi-Strauss | Guerre et commerce chez les Indiens d'Amérique du Sud[END_REF]. Many political studies try to describe terrorism in terms of unstable interactions, instead of pretending to reduce it to some explaining causes such as poverty, culture, etc. Let us mention here the recent work by[START_REF] Sageman | Understanding Terror Networks[END_REF].

This is a classical subject from Roman and Chinese studies, to mention only two empires, but one could also mention the colossal study on international relations by[START_REF] Duroselle | Tout Empire périra[END_REF].