On January 20th, 22nd, and 29th, 1970 Saul Kripke delivered three lectures at Princeton University. They produced something of a sensation. In the lectures he argued, amongst other things, that many names in ordinary language referred to objects directly rather than by means of associated descriptions; that causal chains from language user to language user were an important mechanism for preserving reference; that there were necessary a posteriori and contingent a priori truths; that identity relations between rigid designators were necessary; and argued, more tentatively, that materialist identity theories in the philosophy of mind were suspect. Interspersed with this was a consider able amount of material on natural kind terms and essentialism. As a result of these lectures and a related 1971 paper, 'Identity and Necessity' (Kripke [1971]), talk of rigid designators, Hesperus and Phosphorus, meter bars, gold and H 0, and suchlike quickly became commonplace in philosophical circles 2 and when the lectures were published under the title Naming and Necessity in the collection The Semantics of Natural Language (Davidson and Harman l [1972]), that volume became the biggest seller in the Reidel (later Kluwer) list. The cluster of theses surrounding the idea that a relation of direct reference 2 exists between names and their referents is now frequently referred to as 'The 3 New Theory of Reference'.

On January 20th, 22nd, and 29th, 1970 Saul Kripke delivered three lectures at Princeton University. They produced something of a sensation. In the lectures he argued, amongst other things, that many names in ordinary language referred to objects directly rather than by means of associated descriptions; that causal chains from language user to language user were an important mechanism for preserving reference; that there were necessary a posteriori and contingent a priori truths; that identity relations between rigid designators were necessary; and argued, more tentatively, that materialist identity theories in the philosophy of mind were suspect. Interspersed with this was a consider able amount of material on natural kind terms and essentialism. As a result of these lectures and a related 1971 paper, 'Identity and Necessity' (Kripke [1971]), talk of rigid designators, Hesperus and Phosphorus, meter bars, gold and H 0, and suchlike quickly became commonplace in philosophical circles 2 and when the lectures were published under the title Naming and Necessity in the collection The Semantics of Natural Language (Davidson and Harman l [1972]), that volume became the biggest seller in the Reidel (later Kluwer) list. The cluster of theses surrounding the idea that a relation of direct reference 2 exists between names and their referents is now frequently referred to as 'The 3 New Theory of Reference'.

This series will include monographs and collections of studies devoted to the investigation and exploration of knowledge, information, and data-processing systems of all kinds, no matter whether human, (other) animal, or machine. Its scope is intended to span the full range of interest from classical problems in the philosophy of mind and philosophical psychology through issues in cognitive psychology and sociobiology (concerning the mental powers of other species) to ideas related to artificial intelligence and computer science. While primary emphasis will be placed upon theoretical, conceptual, and epistemological aspects of these problems and domains, empirical, experimen tal, and methodological studies will also appear from time to time. The present volume reflects the kind of insights that can be obtained when research workers in philosophy, artificial intelligence, and computer science explore problems of common concern. The issues here tend to fall into two broad but varied sets, namely: those concerned with content and concepts, on the one hand, and those concerned with semantics and epistemology, on the other. The collection begins with a prologue that focuses upon the relations between connectionism and alternative conceptions of nativism and ends with an epilogue that examines the significance of alternative conceptions of the Frame Problem for artificial intelligence. Because these papers are rich and diverse, they ought to appeal to a wide and heterogeneous audience. J.H.F."

Among the most important problems confronting computer science is that of developing a paradigm appropriate to the discipline. Proponents of formal methods - such as John McCarthy, C.A.R. Hoare, and Edgar Dijkstra - have advanced the position that computing is a mathematical activity and that computer science should model itself after mathematics. Opponents of formal methods - by contrast, suggest that programming is the activity which is fundamental to computer science and that there are important differences that distinguish it from mathematics, which therefore cannot provide a suitable paradigm. Disagreement over the place of formal methods in computer science has recently arisen in the form of renewed interest in the nature and capacity of program verification as a method for establishing the reliability of software systems. A paper that appeared in Communications of the ACM entitled, Program Verification: The Very Idea', by James H. Fetzer triggered an extended debate that has been discussed in several journals and that has endured for several years, engaging the interest of computer scientists (both theoretical and applied) and of other thinkers from a wide range of backgrounds who want to understand computer science as a domain of inquiry. The editors of this collection have brought together many of the most interesting and important studies that contribute to answering questions about the nature and the limits of computer science. These include early papers advocating the mathematical paradigm by McCarthy, Naur, R. Floyd, and Hoare (in Part I), others that elaborate the paradigm by Hoare, Meyer, Naur, and Scherlis and Scott (in Part II), challenges, limits and alternatives explored by C. Floyd, Smith, Blum, and Naur (in Part III), and recent work focusing on formal verification by DeMillo, Lipton, and Perlis, Fetzer, Cohn, and Colburn (in Part IV). It provides essential resources for further study. This volume will appeal to scientists, philosophers, and laypersons who want to understand the theoretical foundations of computer science and be appropriately positioned to evaluate the scope and limits of the discipline.

This series will include monographs and collections of studies devoted to the investigation and exploration of knowledge, information and data-processing systems of all kinds, no matter whether human, (other) animal or machine. Its scope is intended to span the full range of interests from classical problems in the philosophy of mind and philosophical psychology through issues in cognitive psychology and sociobiology (concerning the mental capabilities of other species) to ideas related to artificial intelligence and to computer science. While primary emphasis will be placed upon theoretical, conceptual and epistemological aspects of these problems and domains, empirical, experimental and methodological studies will also appear from time to time. The present volume illustrates the approach represented by this series. It addresses fundamental questions lying at the heart of artificial intelligence, including those of the relative virtues of computational and of non-computational conceptions of language and of mind, whether AI should be envisioned as a philosophical or as a scientific discipline, the theoretical character of patterns of inference and modes of argumenta tion (especially, defeasible and inductive reasoning), and the relations that may obtain between AI and epistemology. Alternative positions are developed in detail and subjected to vigorous debate in the justifiable expectation that - here as elsewhere - critical inquiry provides the most promising path to discovering the truth about ourselves and the world around us. lH.F."

With this defense of intensional realism as a philosophical foundation for understanding scientific procedures and grounding scientific knowledge, James Fetzer provides a systematic alternative to much of recent work on scientific theory. To Fetzer, the current state of understanding the 'laws' of nature, or the 'law-like' statements of scientific theories, appears to be one of philosophical defeat; and he is determined to overcome that defeat. Based upon his incisive advocacy of the single-case propensity interpretation of probability, Fetzer develops a coherent structure within which the central problems of the philosophy of science find their solutions. Whether the reader accepts the author's contentions may, in the end, depend upon ancient choices in the interpretation of experience and explanation, but there can be little doubt of Fetzer's spirited competence in arguing for setting ontology before epistemology, and within the analysis of language. To us, Fetzer's ambition is appealing, fusing, as he says, the substantive commitment of the Popperian with the conscientious sensitivity of the Hempelian to the technical precision required for justified explication. To Fetzer, science is the objective pursuit of fallible general knowledge. This innocent character ization, which we suppose most scientists would welcome, receives a most careful elaboration in this book; it will demand equally careful critical con sideration. Center for the Philosophy and ROBERT S. COHEN History of Science, MARX W. WARTOFSKY Boston University October 1981 v TABLE OF CONTENTS EDITORIAL PREFACE v FOREWORD xi ACKNOWLEDGEMENTS xv PART I: CAUSATION 1."

This series will include monographs and collections of studies devoted to the investigation and exploration of knowledge, information, and data-processing systems of all kinds, no matter whether human. (other) animal, or machine. Its scope is intended to span the full range of interests from classical problems in the philosophy of mind and philosophical psychology through issues in cognitive psychology and sociobiology (concerning the mental capabilities of other species) to ideas related to artificial intelligence and computer science. While primary emphasis will be placed upon theoretical, conceptual, and epistemological aspects of these problems and domains, empirical, experimental, and methodological studies will also appear from time to time. No problem within the field of cognitive inquiry is more difficult than that of developing an adequate conception of the nature of mind and of its mode of operation. Our purpose in compiling the present volume has been to contribute to the pursuit of this objective by bringing together a repre sentative cross-section of the principal approaches and the primary players who are engaged in contemporary debate on these crucial issues. The book begins with a comprehensive introduction composed by David Cole, the senior editor of this work, which provides a background for understanding the major problems and alternative solutions, and ends with a selected bibliography intended to promote further research. If our efforts assist others in dealing with these issues, they will have been worthwhile. J. H. F. David J. Cole et at. (eds. ), Philosophy, Mind, and Cognitive Inquiry, ix."

This series will include monographs and collections of studies devoted to the investigation and exploration of knowledge, information, and data processing systems of all kinds, no matter whether human, (other) animal, or machine. Its scope is intended to span the full range of interests from classical problems in the philosophy of mind and philosophical psycholo gy through issues in cognitive psychology and sociobiology (concerning the mental capabilities of other species) to ideas related to artificial in telligence and to computer science. While primary emphasis will be placed upon theoretical, conceptual, and epistemological aspects of these prob lems and domains, empirical, experimental, and methodological studies will also appear from time to time. The perspective that prevails in artificial intelligence today suggests that the theory of computability defines the boundaries of the nature of thought, precisely because all thinking is computational. This paradigm draws its inspiration from the symbol-system hypothesis of Newell and Simon and finds its culmination in the computational conception of lan guage and mentality. The "standard conception" represented by these views is subjected to a thorough and sustained critique in the pages of this book. Employing a distinction between systems for which signs are signif icant for the users of a system and others for which signs are significant for use by a system, I have sought to define the boundaries of what AI, in principle, may be expected to achieve."

The papers presented in this special collection focus upon conceptual, the oretical and epistemological aspects of sociobiology, an emerging discipline that deals with the extent to which genetic factors influence or control patterns of behavior as well as the extent to which patterns of behavior, in turn, influence or control genetic evolution. The Prologue advances a compre hensive acco/unt of the field of gene-culture co-evolution, where Lumsden and Gushurst differentiate between "classical" sociobiology (represented especially by Wilson's early work) and current research on human socio biology (represented by Lumsden and Wilson's later work), which emphasizes interplay between genes, minds, and culture. The specter of genetic deter minism, no doubt, has created considerable controversy, some of which may be laid to rest by Hanna's analysis of the (ambiguous) notion of a "genetic program," which indicates the necessity for distinguishing between descriptive and prescriptive dimensions of this complex concept. Brandon offers a framework for assessing the respective contributions of nature and of nurture by advancing a means for measuring genetic and cultural influences upon "inheritance," which supports the conclusion that evolving patterns of behavior do not always maximize inclusive fitness, contrary to what socio biologists have claimed. The influence of culture upon genetic evolution, of course, can be adequately appraised only when a suitable account of culture itself has been found, a desideratum Smillie attempts to satisfy by utilizing the notion of "cinfo" as culturally transmitted ecological informa tion, a resource other species tend not to exploit."

This series will include monographs and collections of studies devoted to the investigation and exploration of knowledge, information, and data-processing systems of all kinds, no matter whether human, (other) animal, or machine. Its scope is intended to span the full range of interest from classical problems in the philosophy of mind and philosophical psychology through issues in cognitive psychology and sociobiology (concerning the mental powers of other species) to ideas related to artificial intelligence and computer science. While primary emphasis will be placed upon theoretical, conceptual, and epistemological aspects of these problems and domains, empirical, experimen tal, and methodological studies will also appear from time to time. The present volume reflects the kind of insights that can be obtained when research workers in philosophy, artificial intelligence, and computer science explore problems of common concern. The issues here tend to fall into two broad but varied sets, namely: those concerned with content and concepts, on the one hand, and those concerned with semantics and epistemology, on the other. The collection begins with a prologue that focuses upon the relations between connectionism and alternative conceptions of nativism and ends with an epilogue that examines the significance of alternative conceptions of the Frame Problem for artificial intelligence. Because these papers are rich and diverse, they ought to appeal to a wide and heterogeneous audience. J.H.F."

Among the most important problems confronting computer science is that of developing a paradigm appropriate to the discipline. Proponents of formal methods - such as John McCarthy, C.A.R. Hoare, and Edgar Dijkstra - have advanced the position that computing is a mathematical activity and that computer science should model itself after mathematics. Opponents of formal methods - by contrast, suggest that programming is the activity which is fundamental to computer science and that there are important differences that distinguish it from mathematics, which therefore cannot provide a suitable paradigm. Disagreement over the place of formal methods in computer science has recently arisen in the form of renewed interest in the nature and capacity of program verification as a method for establishing the reliability of software systems. A paper that appeared in Communications of the ACM entitled, Program Verification: The Very Idea', by James H. Fetzer triggered an extended debate that has been discussed in several journals and that has endured for several years, engaging the interest of computer scientists (both theoretical and applied) and of other thinkers from a wide range of backgrounds who want to understand computer science as a domain of inquiry. The editors of this collection have brought together many of the most interesting and important studies that contribute to answering questions about the nature and the limits of computer science. These include early papers advocating the mathematical paradigm by McCarthy, Naur, R. Floyd, and Hoare (in Part I), others that elaborate the paradigm by Hoare, Meyer, Naur, and Scherlis and Scott (in Part II), challenges, limits and alternatives explored by C. Floyd, Smith, Blum, and Naur (in Part III), and recent work focusing on formal verification by DeMillo, Lipton, and Perlis, Fetzer, Cohn, and Colburn (in Part IV). It provides essential resources for further study. This volume will appeal to scientists, philosophers, and laypersons who want to understand the theoretical foundations of computer science and be appropriately positioned to evaluate the scope and limits of the discipline.

Science aims at the discovery of general principles of special kinds that are applicable for the explanation and prediction of the phenomena of the world in the form of theories and laws. When the phenomena themselves happen to be general, the principlesinvolved assume the form of theories; and when they are p- ticular, they assume the form of general laws. Theories themselves are sets of laws and de nitions that apply to a common domain, which makes laws indispensable to science. Understanding science thus depends upon understanding the nature of theories and laws, the logical structure of explanations and predictions based upon them, and the principles of inference and decision that apply to theories and laws. Laws and theories can differ in their form as well as in their content. The laws of quantum mechanics are indeterministic (or probabilistic), for example, while those of classical mechanics are deterministic (or universal) instead. The history of science re ects an increasing role for probabilities as properties of the world but also as measures of evidential support and as degrees of subjective belief. Our purpose is to clarify and illuminate the place of probability in science.

Science aims at the discovery of general principles of special kinds that are applicable for the explanation and prediction of the phenomena of the world in the form of theories and laws. When the phenomena themselves happen to be general, the principlesinvolved assume the form of theories; and when they are p- ticular, they assume the form of general laws. Theories themselves are sets of laws and de nitions that apply to a common domain, which makes laws indispensable to science. Understanding science thus depends upon understanding the nature of theories and laws, the logical structure of explanations and predictions based upon them, and the principles of inference and decision that apply to theories and laws. Laws and theories can differ in their form as well as in their content. The laws of quantum mechanics are indeterministic (or probabilistic), for example, while those of classical mechanics are deterministic (or universal) instead. The history of science re ects an increasing role for probabilities as properties of the world but also as measures of evidential support and as degrees of subjective belief. Our purpose is to clarify and illuminate the place of probability in science.

This series will include monographs and collections of studies devoted to the investigation and exploration of knowledge, information and data-processing systems of all kinds, no matter whether human, (other) animal or machine. Its scope is intended to span the full range of interests from classical problems in the philosophy of mind and phi losophical psychology through issues in cognitive psychology and socio biology (concerning the mental capabilities of other species) to ideas related to artificial intelligence and computer science. While primary emphasis will be placed upon theoretical, conceptual and epistemologi cal aspects of these problems and domains, empirical, experimental and methodological studies will also appear from time to time. Among the most challenging and difficult projects within the scope of artificial intelligence is the development and implementation of com puter programs suitable for processing natural language. Our purpose in compiling the present volume has been to contribute to the foundations of this enterprise by bringing together classic papers devoted to crucial problems involved in understanding natural language, which range from issues of formal syntax and logical form to those of possible-worlds and situation semantics. The book begins with a comprehensive introduc tion composed by Jack Kulas, the senior editor of this work, which pro vides a systematic orientation to this complex field, and ends with a selected bibliography intended to promote further research. If our efforts assist others in dealing with these problems, they will have been worthwhile. J. H. F."

This series will include monographs and collections of studies devoted to the investigation and exploration of knowledge, information, and data-processing systems of all kinds, no matter whether human. (other) animal, or machine. Its scope is intended to span the full range of interests from classical problems in the philosophy of mind and philosophical psychology through issues in cognitive psychology and sociobiology (concerning the mental capabilities of other species) to ideas related to artificial intelligence and computer science. While primary emphasis will be placed upon theoretical, conceptual, and epistemological aspects of these problems and domains, empirical, experimental, and methodological studies will also appear from time to time. No problem within the field of cognitive inquiry is more difficult than that of developing an adequate conception of the nature of mind and of its mode of operation. Our purpose in compiling the present volume has been to contribute to the pursuit of this objective by bringing together a repre sentative cross-section of the principal approaches and the primary players who are engaged in contemporary debate on these crucial issues. The book begins with a comprehensive introduction composed by David Cole, the senior editor of this work, which provides a background for understanding the major problems and alternative solutions, and ends with a selected bibliography intended to promote further research. If our efforts assist others in dealing with these issues, they will have been worthwhile. J. H. F. David J. Cole et at. (eds. ), Philosophy, Mind, and Cognitive Inquiry, ix."

An important collection of studies providing a fresh and original perspective on the nature of mind, including thoughtful and detailed arguments that explain why the prevailing paradigm - the computational conception of language and mentality - can no longer be sustained. An alternative approach is advanced, inspired by the work of Charles S. Peirce, according to which minds are sign-using (or semiotic') systems, which in turn generates distinctions between different kinds of minds and overcomes problems that burden more familiar alternatives. Unlike conceptions of minds as machines, this novel approach has obvious evolutionary implications, where differences in semiotic abilities tend to distinguish the species. From this point of view, the scope and limits of computer and AI systems can be more adequately appraised and alternative accounts of consciousness and cognition can be more thoroughly criticised. Readership: Intermediate and advanced students of computer science, AI, cognitive science, and all students of the philosophy of the mind.

This series will include monographs and collections of studies devoted to the investigation and exploration of knowledge, information, and data processing systems of all kinds, no matter whether human, (other) animal, or machine. Its scope is intended to span the full range of interests from classical problems in the philosophy of mind and philosophical psycholo gy through issues in cognitive psychology and sociobiology (concerning the mental capabilities of other species) to ideas related to artificial in telligence and to computer science. While primary emphasis will be placed upon theoretical, conceptual, and epistemological aspects of these prob lems and domains, empirical, experimental, and methodological studies will also appear from time to time. The perspective that prevails in artificial intelligence today suggests that the theory of computability defines the boundaries of the nature of thought, precisely because all thinking is computational. This paradigm draws its inspiration from the symbol-system hypothesis of Newell and Simon and finds its culmination in the computational conception of lan guage and mentality. The "standard conception" represented by these views is subjected to a thorough and sustained critique in the pages of this book. Employing a distinction between systems for which signs are signif icant for the users of a system and others for which signs are significant for use by a system, I have sought to define the boundaries of what AI, in principle, may be expected to achieve."

This series will include monographs and collections of studies devoted to the investigation and exploration of knowledge, information and data-processing systems of all kinds, no matter whether human, (other) animal or machine. Its scope is intended to span the full range of interests from classical problems in the philosophy of mind and phi losophical psychology through issues in cognitive psychology and socio biology (concerning the mental capabilities of other species) to ideas related to artificial intelligence and computer science. While primary emphasis will be placed upon theoretical, conceptual and epistemologi cal aspects of these problems and domains, empirical, experimental and methodological studies will also appear from time to time. Among the most challenging and difficult projects within the scope of artificial intelligence is the development and implementation of com puter programs suitable for processing natural language. Our purpose in compiling the present volume has been to contribute to the foundations of this enterprise by bringing together classic papers devoted to crucial problems involved in understanding natural language, which range from issues of formal syntax and logical form to those of possible-worlds and situation semantics. The book begins with a comprehensive introduc tion composed by Jack Kulas, the senior editor of this work, which pro vides a systematic orientation to this complex field, and ends with a selected bibliography intended to promote further research. If our efforts assist others in dealing with these problems, they will have been worthwhile. J. H. F."

This series will include monographs and collections of studies devoted to the investigation and exploration of knowledge, information and data-processing systems of all kinds, no matter whether human, (other) animal or machine. Its scope is intended to span the full range of interests from classical problems in the philosophy of mind and philosophical psychology through issues in cognitive psychology and sociobiology (concerning the mental capabilities of other species) to ideas related to artificial intelligence and to computer science. While primary emphasis will be placed upon theoretical, conceptual and epistemological aspects of these problems and domains, empirical, experimental and methodological studies will also appear from time to time. The present volume illustrates the approach represented by this series. It addresses fundamental questions lying at the heart of artificial intelligence, including those of the relative virtues of computational and of non-computational conceptions of language and of mind, whether AI should be envisioned as a philosophical or as a scientific discipline, the theoretical character of patterns of inference and modes of argumenta tion (especially, defeasible and inductive reasoning), and the relations that may obtain between AI and epistemology. Alternative positions are developed in detail and subjected to vigorous debate in the justifiable expectation that - here as elsewhere - critical inquiry provides the most promising path to discovering the truth about ourselves and the world around us. lH.F."

The contributions to this special collection concern issues and problems discussed in or related to the work of Wesley C. Salmon. Salmon has long been noted for his important work in the philosophy of science, which has included research on the interpretation of probability, the nature of explanation, the character of reasoning, the justification of induction, the structure of space/time and the paradoxes of Zeno, to mention only some of the most prominent. During a time of increasing preoccupation with historical and sociological approaches to under standing science (which characterize scientific developments as though they could be adequately analysed from the perspective of political movements, even mistaking the phenomena of conversion for the rational appraisal of scientific theories), Salmon has remained stead fastly devoted to isolating and justifying those normative standards distinguishing science from non-science - especially through the vindi cation of general principles of scientific procedure and the validation of specific examples of scientific theories - without which science itself cannot be (even remotely) adequately understood. In this respect, Salmon exemplifies and strengthens a splendid tradi tion whose most remarkable representatives include Hans Reichenbach, Rudolf Carnap and Carl G. Hempel, all of whom exerted a profound influence upon his own development."

The papers presented in this special collection focus upon conceptual, the oretical and epistemological aspects of sociobiology, an emerging discipline that deals with the extent to which genetic factors influence or control patterns of behavior as well as the extent to which patterns of behavior, in turn, influence or control genetic evolution. The Prologue advances a compre hensive acco/unt of the field of gene-culture co-evolution, where Lumsden and Gushurst differentiate between "classical" sociobiology (represented especially by Wilson's early work) and current research on human socio biology (represented by Lumsden and Wilson's later work), which emphasizes interplay between genes, minds, and culture. The specter of genetic deter minism, no doubt, has created considerable controversy, some of which may be laid to rest by Hanna's analysis of the (ambiguous) notion of a "genetic program," which indicates the necessity for distinguishing between descriptive and prescriptive dimensions of this complex concept. Brandon offers a framework for assessing the respective contributions of nature and of nurture by advancing a means for measuring genetic and cultural influences upon "inheritance," which supports the conclusion that evolving patterns of behavior do not always maximize inclusive fitness, contrary to what socio biologists have claimed. The influence of culture upon genetic evolution, of course, can be adequately appraised only when a suitable account of culture itself has been found, a desideratum Smillie attempts to satisfy by utilizing the notion of "cinfo" as culturally transmitted ecological informa tion, a resource other species tend not to exploit."

With this defense of intensional realism as a philosophical foundation for understanding scientific procedures and grounding scientific knowledge, James Fetzer provides a systematic alternative to much of recent work on scientific theory. To Fetzer, the current state of understanding the 'laws' of nature, or the 'law-like' statements of scientific theories, appears to be one of philosophical defeat; and he is determined to overcome that defeat. Based upon his incisive advocacy of the single-case propensity interpretation of probability, Fetzer develops a coherent structure within which the central problems of the philosophy of science find their solutions. Whether the reader accepts the author's contentions may, in the end, depend upon ancient choices in the interpretation of experience and explanation, but there can be little doubt of Fetzer's spirited competence in arguing for setting ontology before epistemology, and within the analysis of language. To us, Fetzer's ambition is appealing, fusing, as he says, the substantive commitment of the Popperian with the conscientious sensitivity of the Hempelian to the technical precision required for justified explication. To Fetzer, science is the objective pursuit of fallible general knowledge. This innocent character ization, which we suppose most scientists would welcome, receives a most careful elaboration in this book; it will demand equally careful critical con sideration. Center for the Philosophy and ROBERT S. COHEN History of Science, MARX W. WARTOFSKY Boston University October 1981 v TABLE OF CONTENTS EDITORIAL PREFACE v FOREWORD xi ACKNOWLEDGEMENTS xv PART I: CAUSATION 1."