This paper is about the differences between probabilities and beliefs and why reasoning should not always conform to probability laws. Probability is defined in terms of urn models from which probability laws can be derived. This means that probabilities are expressed in rational numbers, they suppose the existence of veridical representations and, when viewed as parts of a probability model, they are determined by a restricted set of variables. Moreover, probabilities are subjective, in that they apply to classes of events (...) that have been deemed (by someone) to be equivalent, rather than to unique events. Beliefs on the other hand are multifaceted, interconnected with all other beliefs, and inexpressible in their entirety. It will be argued that there are not sufficient rational numbers to characterise beliefs by probabilities and that the idea of a veridical set of beliefs is questionable. The concept of a complete probability model based on Fisher's notion of identifiable subsets is outlined. It is argued that to be complete a model must be known to be true. This can never be the case because whatever a person supposes to be true must be potentially modifiable in the light of new information. Thus to infer that an individual's probability estimate is biased it is necessary not only to show that the estimate differs from that given by a probability model, but also to assume that this model is complete, and completeness is not empirically verifiable. It follows that probability models and Bayes theorem are not necessarily appropriate standards for people's probability judgements. The quality of a probability model depends on how reasonable it is to treat some existing uncertainty as if it were equivalent to that in a particular urn model and this cannot be determined empirically. Bias can be demonstrated in estimates of proportions of finite populations such as in the false consensus effect. However the modification of beliefs by ad hoc methods like Tversky and Kahneman's heuristics can be justified, even though this results in biased judgements. This is because of pragmatic factors such as the cost of obtaining and taking account of additional information which are not included even in a complete probability model. Finally, an analogy is drawn between probability models and geometric figures. Both idealisations are useful but qualitatively inadequate characterisations of nature. A difference between the two is that the size of any error can be limited in the case of the geometric figure in a way that is not possible in a probability model. (shrink)

Evidence-based medicine has beendefined as the conscientious and judicious useof current best evidence in making clinicaldecisions. This paper will attempt to explicatethe terms ``conscientious'''' and ``judicious''''within the evidence-based medicine definition.It will be argued that ``conscientious'''' and``judicious'''' represent virtue terms derived fromvirtue ethics and virtue epistemology. Theidentification of explicit virtue components inthe definition and therefore conception ofevidence-based medicine presents an importantstarting point in the connection between virtuetheories and medicine itself. In addition, aunification of virtue theories andevidence-based medicine will illustrate theneed for (...) future research in order to combinethe fields of virtue-based approaches andclinical practice. (shrink)

Issue two contained three pieces arguing against relativism: the view that what is true from one individual's or community's perspective might be false from another, that there is no ‘absolute’ truth on any issue. Here David Mills, an anthropologist, argues that, even if we are right to reject philosophical relativism, there is still value in embracing a methodological form of relativism.

One of the most interesting phenomena in the history of the English language is the remarkable rise of the word right, in its many interrelated senses and uses. This article tries to trace the changes in the meaning and use of this word, as well as the rise of new conversational routines based on right, and raises questions about the cultural underpinnings of these semantic and pragmatic developments. It explores the hypothesis that the `discourse of truth' declined in English over (...) the centuries; that the use of `right' and `wrong' as parallel concepts increased; and it notes that the use of right as an adjective increased enormously in relation to the use of true. Originally, right meant `straight', as in a right line. Figuratively, perhaps, this right in the sense `straight' was also used in an evaluative sense: `good', with an additional component building on the geometrical image: `clearly good'. Spoken of somebody else's words, “right” was linked with `true'. But in the course of the 17th and 18th centuries right appears to have begun to be used more and more with reference to thinking rather than speaking. The association of right with thinking seems to have spread in parallel with a contrastive use of right and wrong — a trend apparently encouraged by the influence of the Reformation, especially within its Calvinist wing. Another interesting development is that over the last two centuries or so the discourse of `right' and `wrong' appears to have found a competitor in a discourse of `cooperation' and mutual concessions. Judging by both the frequency and range of its use, the word right flourished in this atmosphere, whereas wrong was increasingly left behind. This article traces the transition from the Shakespearean response “Right.”, described by the OED as `you are right; you speak well', to the present-day “Right.” of non-committal acknowledgement and it links the developments in semantics and discourse patterns with historical phenomena such as Puritanism, British empiricism, the Enlightenment and the growth of democracy. (shrink)