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In Britain why should 2 hours 10 minutes be critical in moving from a unanimous decision requirement to one of a 10-2 majority The research cited above suggests that a much more radical approach to understanding juries and juror behaviour is required From a scienti c view, Section 8 of the Contempt of Court Act 1981 which, in Britain, prevents asking jurors about their deliberation, must be looked at again This would be a very important rst step towards the law adapting to the method and ndings of psychology But as Lloyd-Bostock (1995) pointed out, juries are present in Britain in only about 2% of all criminal cases, and in few if any civil cases Thus the clear message of non-rationality, mental heuristics and subjective handling of probabilities applies to many more fact- nders than jury members.

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The structural models are also referred to as asset volatility models. The structural aspect of the models comes from the fact that there is a story behind default (i.e., something happens to trigger default). The structural (asset volatility) models are rooted in the Merton insight we introduced in 3: Debt behaves like a put option on the value of the rm s assets. In a Merton model, default occurs when the value of the rm s assets falls below some trigger level; so default is determined by the structure of the individual rm and its asset volatility. It follows that default correlation must be a function of asset correlation. Implementation of a structural (asset volatility) model requires estimating the market value of the rm s assets and the volatility of that value. Because asset values and their volatilities are not observable for most rms, structural models rely heavily on the existence of publicly traded equity to estimate the needed parameters.

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It applies to judges, magistrates, and to psychologists who present their ndings in court or by way of pre-trial reports All are dealing with uncertainty: never certainty The purpose of this chapter has been to show that, on the surface, psychology and law both deal in uncertainty and thus probabilities; and while psychology can take refuge in statistical testing which does handle probability mathematically, systematically and logically, no such luxury is afforded the trier of fact But when the psychologist steps outside his or her laboratory and attempts to particularise from the general then he or she is in exactly the same sea of uncertainty.

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QALYs may be used for different purposes. They might be employed to decide which of a range of treatments open to a patient will bring about the most favourable quality of life an ethically inoffensive use, to most people. Alternatively they might be used to discriminate between patients in competition for a scarce resource an ethically troublesome use. There are other modes lying between these extremes. QALYs can be deployed in the following ways: 1 To clarify costs of treatment, without generating practical change. 2 To make priorities explicit, so encouraging more self-conscious and rigorous thinking.

In this real sense, then, it is not so much law adapting to the methods of psychology, rather it is the need for both parties to accept, at the law psychology interface, that uncertainty is the reality and that both disciplines have to come to terms.

A natural approach that combines randomization and approximation would be to use random sampling to get an estimator of the solution Unfortunately, this may not always work: as an example, Charikar et al [15] have shown that estimators based on random sampling do not yield good results for F0 Theorem 11 [15] Let E be a (possibly adaptive and randomized) estimator of F0 that examines at most r items in a set of n items and let err = max{E/F0 , F0 /E} be the error of the estimator Then, for any p > 1/er , there is a choice of the set of items such that err ((n r)/2r) ln(1/p) with probability at least p The result of Theorem 11 states that no good estimator can be obtained if we only examine a fraction of the input On the contrary, as we have seen in Section 83.

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technology to which they appertain. For categorization purposes, the Patent Office classification scheme may be utilized (the Patent Office has kindly done this work for us) or any other convenient system may be employed.When plotting a number of patents in a portfolio, related categories are grouped together. It is thus theoretically possible to both

Appendix: Glossary ................................................... 369 Index ....................................................................... 377

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