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Restorative Justice: The In uence of Psychology from a Jurisprudent Therapy Perspective
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and where k denotes the bias for the kth hidden neuron. A common method for estimating synaptic weights given a collection p1 , q1 , . . . , pt , qt of training patterns is to de ne an energy function 1 2
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10.06 Sexual Intimacies with Relatives or Significant Others of Current Therapy Clients/Patients
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However, research has shown that humans have dif culty with simple, combined and especially conditional probability (such as Bayes theorem). The simple probability of event A is p(A); the negation of the probability of event A is ~ ( p A) = 1 p(A); the combined probability of two mutually exclusive events = p(A) + p(B); the combined probability of two independent events = p(A) p(B). Confusion between the different types of probability can be crucial in criminal cases as the recent trial and conviction of a mother who was charged with the murder of her two children (at different times) shows. A key piece of evidence was the assertion that the chance of two children dying from cot-death (the alternative explanation) was 1 in 73 million. This probability statement is commonly regarded as having convinced the jury that the mother should be found guilty. This gure, it has since been argued (Watkins, 2000), was based upon the calculation of the combined probability of independent events. What would the probability estimate be, however, if it was demonstrable that they were not independent events, but rather could be linked by, for example, a cotdeath gene, transmittable from the mother (or father) The estimated probability drops precipitously, to about 1 in 4! From all that has been said above about psychological research into human decisionmaking, it would be misguided to assume that jurors, judges or magistrates are fully rational, calculating machines with infallible reasoning and decision-making capabilities. When a human acts as a judicial fact- nder and decision-maker his or her human information processing limitations, cognitive biases and heuristics, and grounded beliefs, values, attitudes and opinions are not somehow miraculously set aside to be replaced with unlimited rationality, cognitive capacity and infallible logical reasoning powers. Once a human, always a human: irrespective of what role ascription one nds oneself in. But if humans are poor at hypothetico-deductive reasoning could it not be that they are good at inferential reasoning: reasoning from speci c facts or observations to a general conclusion that may explain the facts Unfortunately, such seems not to be the case. Psychology has demonstrated that humans have dif culty with causal inferences whether it be with Mill s (1874) method of agreement, or his method of difference; with the law of large numbers, or with base-rate information; and with con guration bias, illusory correlation, and correlation per se. Holyoak and Nisbett (1988) suggest that humans use both bottom-up (evidence based) and top-down (existing knowledge) strategies when drawing inferences. More recently Sloman (1996) has suggested that humans have two complementary systems of reasoning. The rst is an associative system that involves mental operations based upon observed similarities and temporal contiguities. The second is a rule-based system. The associative system can lead to fast responses that are based on well-learned patterns and general tendencies, focusing on salient typical-features of a situation. This system, however, makes use of the error-producing representativeness heuristic discussed above, belief-bias effects in syllogistic reasoning, plausibility effects in causal reasoning and enhancement of conditional reasoning in pragmatic context.
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