In this paper we investigate the logical consequences of the common understanding of amateurism in the context of big-time US college athletics, and in so doing, illustrate a method based on linguistic analysis and logic. The initial thrust of the paper centres on the term ?amateur? as presupposed by the late Professor Brand in his attempt to justify the ?business? of NCAA-sponsored Division I sports by decoupling the ?participants from the enterprise?. Next, we examine a more rigorous definition of the (...) term ?amateur? in order to show more clearly the difficulties posed by the current situation in college athletics. Additionally, our use of linguistic analysis exposes a flaw in the NCAA's recent move to amend by-law 12.02 in an attempt to avoid the charge of exploitation. Lastly, we put forth a new proposal for better dealing with the central issues swirling around the NCAA as it strives to formulate sound policy at this ?tectonic? juncture of players, fans, college programmes and academic integrity. (shrink)

Rips, in The Psychology of Proof, argues that, through the processes of evolution, logic (e.g., modus ponens) has become established in the human mind as the basis for thinking, and that production systems rest on this foundation. In this paper we defend the converse argument that, through evolution, a production system architecture has become the basis for human thinking, and that formal logics rest on this production system and the accompanying mechanisms for recognition and search. It is through the “automaticity” (...) of the execution of productions that we experience the compellingness of deductive arguments. (shrink)

Moses Maimonides, scholar, physician, and philosopher, was the most influential Jewish thinker of the Middle Ages. In this magisterial new biography, the work of many years, Herbert Davidson provides an exhaustive guide to Maimonides' life and works. After considering Maimonides' upbringing and education, Davidson expounds all of his voluminous writings in exhaustive detail, with separate chapters on rabbinic, philosophical, and medical texts. This long-awaited volume is destined to become the standard work on this towering figure of Western intellectual history.

What can reason do for us and what can't it do? This is the question examined by Herbert A. Simon, who received the 1978 Nobel Prize in Economic Sciences "for his pioneering work on decision-making processes in economic organizations." The ability to apply reason to the choice of actions is supposed to be one of the defining characteristics of our species. In the first two chapters, the author explores the nature and limits of human reason, comparing and evaluating the (...) major theoretical frameworks that have been erected to explain reasoning processes. He also discusses the interaction of thinking and emotion in the choice of our actions. In the third and final chapter, the author applies the theory of bounded rationality to social institutions and human behavior, and points out the problems created by limited attention span human inability to deal with more than one difficult problem at a time. He concludes that we must recognize the limitations on our capabilities for rational choice and pursue goals that, in their tentativeness and flexibility, are compatible with those limits. (shrink)

Là où on peut dater les commentaires d'Averroès sur Aristote, le Commentaire Moyen d'une œuvre donnée peut être considéré comme antérieur au Commentaire Long. En accompagnement de sa belle édition du Commentaire Moyen d'Averroès sur leDe anima, A. Ivry a soutenu que dans ce cas-ci les choses sont inversées et que le Commentaire Moyen duDe animaest “une version abrégée et révisée” du Commentaire Long de la même œuvre. Ivry développe sa thèse avec le plus de détails dansArabic Sciences and Philosophy, (...) 5. Là, il soutient que deux passages dans le Commentaire Moyen duDe animase rapportent nominalement au Commentaire Long, qu'un troisième passage fait allusion au Commentaire Long, et que dans d'autres passages le Commentaire Moyen et le Commentaire Long utilisent une phraséologie semblable et qu'on peut considérer que le premier a été la version abrégée du second. Le présent article répond à cette thèse de la manière suivante: les deux passages dans le Commentaire Moyen qui semblent selon d'lvry se rapporter explicitement au Commentaire Long peuvent vraisemblablement être compris comme des references a l'intérieur du Commentaire Moyen lui-même. Le passage qu'il comprend comme faisant allusion au Commentaire Long ne fait pas réellement allusion à cette œuvre, mais constitue une référence non-equivoque à une section ultérieure du Commentaire Moyen. II n'y a rien qui justifie le fait de regarder les passages dans le Commentaire Moyen cités par Ivry et utilisent une phraséologie semblable à celle du Commentaire Long comme des emprunts faits à ce dernier. Au cours de son argumentation, Ivry mentionne la position d'Averroes sur la nature de l'intellect materiel de l'homme, question qui a donne a Averroes le plus de peine dans ses commentaires sur le De anima d'Aristote et qui, depuis lors, a le plus intrigue ceux qui etudient Averroes. Le présent article souligne que sur le sujet de l'intellect materiel de l'homme, ni le Commentaire Moyen, ni le Commentaire Long sur leDe animan'empruntent I'un a l'autre, car les conceptions de l'intellect matériel qu'ils embrassent sont différentes et incompatibles. (shrink)

It is often claimed that there can be no such thing as a logic of scientific discovery, but only a logic of verification. By 'logic of discovery' is usually meant a normative theory of discovery processes. The claim that such a normative theory is impossible is shown to be incorrect; and two examples are provided of domains where formal processes of varying efficacy for discovering lawfulness can be constructed and compared. The analysis shows how one can treat operationally and formally (...) phenomena that have usually been dismissed with fuzzy labels like 'intuition' and 'creativity'. (shrink)

Cognitive science is, of course, not really a new discipline, but a recognition of a fundamental set of common concerns shared by the disciplines of psychology, computer science, linguistics, economics, epistemology, and the social sciences generally. All of these disciplines are concerned with information processing systems, and all of them are concerned with systems that are adaptive—that are what they are from being ground between the nether millstone of their physiology or hardware, as the case may be, and the upper (...) millstone of a complex environment in which they exist. Systems that are adaptive may equally well be described as “artificial,” for as environments change, they can be expected to change too, as though they were deliberately designed to fit those environments (as indeed they sometimes are).The task of empirical science is to discover and verify invariants in the phenomena under study. The artificiality of information processing systems creates a subtle problem in defining empirical invariants in such systems. For observed regularities are very likely invariant only within a limited range of variation in their environments, and any accurate statement of the laws of such systems must contain reference to their relativity to environmental features. It is a common experience in experimental psychology, for example, to discover that we are studying sociology—the effects of the past histories of our subjects—when we think we are studying physiology—the effects of properties of the human nervous system. Similarly, business cycle economists are only now becoming aware of the extent to which the parameters of the system they are studying are dependent on the experiences of a population with economic events over the previous generation.In artificial sciences, the descriptive and the normative are never far apart. Thus, in economics, the “principle of rationality” is sometimes asserted as a descriptive invariant, sometimes as advice to decision makers. Similarly, in psychology, the processes of adaptation (learning) have always been a central topic, at one time a topic that dominated the whole field of research. Linguistics, too, has suffered its confusions between descriptive and normative attitudes towards its subject. But we must avoid the error, in studying information processing systems, of thinking that the adaptive processes themselves must be invariant; and we must be prepared to face the complexities of regression in the possibility that they themselves may be subject to improvement and adaptation.It might have been necessary a decade ago to argue for the commonality of the information processes that are employed by such disparate systems as computers and human nervous systems. The evidence for that commonality is now overwhelming, and the remaining questions about the boundaries of cognitive science have more to do with whether there also exist nontrivial commonalities with information processing in genetic systems than with whether men and machines both think. (shrink)

Cognitive science is, of course, not really a new discipline, but a recognition of a fundamental set of common concerns shared by the disciplines of psychology, computer science, linguistics, economics, epistemology, and the social sciences generally. All of these disciplines are concerned with information processing systems, and all of them are concerned with systems that are adaptive—that are what they are from being ground between the nether millstone of their physiology or hardware, as the case may be, and the upper (...) millstone of a complex environment in which they exist. Systems that are adaptive may equally well be described as “artificial,” for as environments change, they can be expected to change too, as though they were deliberately designed to fit those environments (as indeed they sometimes are).The task of empirical science is to discover and verify invariants in the phenomena under study. The artificiality of information processing systems creates a subtle problem in defining empirical invariants in such systems. For observed regularities are very likely invariant only within a limited range of variation in their environments, and any accurate statement of the laws of such systems must contain reference to their relativity to environmental features. It is a common experience in experimental psychology, for example, to discover that we are studying sociology—the effects of the past histories of our subjects—when we think we are studying physiology—the effects of properties of the human nervous system. Similarly, business cycle economists are only now becoming aware of the extent to which the parameters of the system they are studying are dependent on the experiences of a population with economic events over the previous generation.In artificial sciences, the descriptive and the normative are never far apart. Thus, in economics, the “principle of rationality” is sometimes asserted as a descriptive invariant, sometimes as advice to decision makers. Similarly, in psychology, the processes of adaptation (learning) have always been a central topic, at one time a topic that dominated the whole field of research. Linguistics, too, has suffered its confusions between descriptive and normative attitudes towards its subject. But we must avoid the error, in studying information processing systems, of thinking that the adaptive processes themselves must be invariant; and we must be prepared to face the complexities of regression in the possibility that they themselves may be subject to improvement and adaptation.It might have been necessary a decade ago to argue for the commonality of the information processes that are employed by such disparate systems as computers and human nervous systems. The evidence for that commonality is now overwhelming, and the remaining questions about the boundaries of cognitive science have more to do with whether there also exist nontrivial commonalities with information processing in genetic systems than with whether men and machines both think. (shrink)

It is shown how a causal ordering can be defined in a complete structure, and how it is equivalent to identifying the mechanisms of a system. Several techniques are shown that may be useful in actually accomplishing such identification. Finally, it is shown how this explication of causal ordering can be used to analyse causal counterfactual conditionals. First the counterfactual proposition at issue is articulated through the device of a belief-contravening supposition. Then the causal ordering is used to provide modal (...) categories for the factual propositions, and the logical contradiction in the system is resolved by ordering the factual propositions according to these causal categories. (shrink)

The task of axiomatizing physical theories has attracted, in recent years, some interest among both empirical scientists and logicians. However, the axiomatizations produced by either one of these two groups seldom appear satisfactory to the members of the other. It is the purpose of this paper to develop an approach that will satisfy the criteria of both, hence permit us to construct axiomatizations that will meet simultaneously the standards and needs of logicians and of empirical scientists.