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Studies repeatedly found overweight or obesity to be a precursor of eating disorders in males. Bulimic men in Carlat et al. s (1997) sample were signi cantly more likely to report premorbid obesity and showed a higher weight at study onset compared to men with AN or EDNOS. Fifty-three percent of subjects in this study also reported a parental history of overweight, but again only in bulimic males did this nding reach statistical signi cance. More than 60% of males examined by Andersen (1992) had experienced obesity in childhood or adolescence. Along with obesity in childhood and adolescence, eating-disordered males quite frequently report teasing by peers. Sixty-four percent of bulimic males in the study of Herzog et al. (1984) had a history of being overweight compared to 37% of females, a difference that did not reach statistical signi cance. Crisp et al. (1986) reported that their anorexic males were signi cantly more overweight at onset of the disorder. Sharp et al.

That these two projections are sufficient to reconstruct the relation RABC is demonstrated in Figure 3.5. In the top half and on the right the cylindrical extensions of the two projections RAB and RBC to the subspaces {A, B} and {B, C}, respectively, are shown. The cylindrical extension of a projection is obtained by simply adding to the tuples in the projection all possible values of the missing dimension. That is, to the tuples in the relation RAB all possible values of the attribute C are added and to the tuples in the relation RBC all possible values of the attribute A are added. (That this operation is called cylindrical extension is due to the common practice to sketch sets as circles or disks: adding a dimension to a disk yields a cylinder.) In a second step the two cylindrical extensions are intersected, by which the original relation RABC is reconstructed, as shown on the bottom left of Figure 3.5. Since relational networks are closely related to database theory, it is not surprising that the decomposition property just studied is well known: if a relation can be decomposed into projections to subspaces (that is, to subsets of attributes), it is called join-decomposable [Maier 1983, Date 1986, Ullman 1988], because the intersection of the cylindrical extensions is identical to a natural join of the projections. In database theory join-decomposition is studied mainly in order to avoid redundancy (which can lead to update anomalies) and to exploit the resulting storage savings. Note that even in this very simple example some savings result: to store the three-dimensional relation, we need 36 bits one for each combination of attribute values in the reasoning space, indicating whether the combination is possible or not. To store the two projections, however, we need only 9 + 12 = 21 bits.

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The same intellectual rigor requirement is not a suf cient condition for an obvious reason. If the eld itself brings little intellectual rigor to the subject, this factor will provide scant gatekeeping protection against bad science or imsy expertise. In this way it is similar to the general acceptance standard. If the eld is occupied by those who uncritically accept the science or technique, surveying their opinion will provide almost no information about the reliability of the evidence. The Kumho Tire Court itself stressed this danger: Nor . . . does the presence of Daubert s general acceptance factor help show that an expert s testimony is reliable where the discipline itself lacks reliability. In the same way, where the discipline lacks intellectual rigor, nding that an expert has applied the same intellectual rigor will not show that that testimony is reliable. Therefore, failing the same intellectual rigor test should usually lead to exclusion, but passing that test should not lead to automatic admission. The courts must still determine whether the amount of rigor employed by the eld is rigorous enough.