Degrees of belief; Dempster's rule of combination; Simple and separable support functions; The weights of evidence; Compatible frames of discernment; Support functions; The discernment of evidence; Quasi support functions; Consonance; Statistical evidence; The dual nature of probable reasoning.

THE ART OF CAUSAL CONJECTURE Glenn Shafer Table of Contents Chapter 1. Introduction........................................................................................ ...........1 1.1. Probability Trees..........................................................................................3 1.2. Many Observers, Many Stances, Many Natures..........................................8 1.3. Causal Relations as Relations in Nature’s Tree...........................................9 1.4. Evidence............................................................................................ ...........13 1.5. Measuring the Average Effect of a Cause....................................................17 1.6. Causal Diagrams..........................................................................................20 1.7. Humean Events............................................................................................23 1.8. Three Levels of Causal Language................................................................27 1.9. An Outline of the Book................................................................................27 Chapter 2. Event Trees............................................................................................... .....31 2.1. Situations and Events...................................................................................32 2.2. The Ordering of Situations and Moivrean Events.......................................35 2.3. Cuts................................................................................................ ..............39 2.4. Humean (...) Events............................................................................................43 2.5. Moivrean Variables......................................................................................49 2.6. Humean Variables........................................................................................53 2.7. Event Trees for Stochastic Processes...........................................................54 2.8. Timing in Event Trees.................................................................................56 2.9. Intersecting Event Trees...............................................................................60 2.10. Notes on the Literature...............................................................................61 Chapter 3. Probability Trees...........................................................................................63 3.1. Some Types of Probability Trees.................................................................64 ii 3.2. Axioms for the Probabilities of Moivrean Events.......................................68 3.3. Zero Probabilities....................................................................................... ..70 3.4. A Sample-Space Analysis of the Event-Tree Axioms.................................72 3.5. Probabilities and Expected Values for Variables.........................................74 3.6. Martingales......................................................................................... .........79 3.7. The Expectation of a Variable in a Cut........................................................83 3.8. Conditional Expected Value and Conditional Expectation.........................87 Chapter 4. The Meaning of Probability...........................................................................91 4.1. The Interpretation of Expected Value..........................................................92 4.2. The Interpretation of Expectation................................................................95 4.3. The Long Run..............................................................................................98 4.4. Changes in Belief.........................................................................................101 4.5. The Empirical Validation of Probability......................................................106 4.6. The Diversity of Uses of Probability...........................................................108 4.7. Notes on the Literature.................................................................................110 Chapter 5. Independent Events.......................................................................................113 5.1. Independence........................................................................................ .......114 5.2. Weak Independence.....................................................................................118 5.3. The Principle of the Common Cause...........................................................121 5.4. Conditional Independence............................................................................128 5.5. Notes on the Literature.................................................................................133 Chapter 6. Events Tracking Events.................................................................................135 6.1. Tracking............................................................................................ ...........137 6.2. Tracking and Conditional Independence.....................................................142 6.3. Stochastic Subsequence...............................................................................143 6.4. Singular Diagrams for Stochastic Subsequence...........................................147 6.5. Conjunctive and Interactive Forks...............................................................149 Chapter 7. Events as Signs of Events..............................................................................153 iii 7.1. Sign................................................................................................ ..............154 7.2. Weak Sign................................................................................................ ....159 7.3. The Ethics of Causal Talk............................................................................160 7.4. Screening Off...............................................................................................16 2 Chapter 8. Independent Variables...................................................................................167 8.1. Unconditional Independence........................................................................170 8.2. Conditional Independence............................................................................175 8.3. Independence for Partitions.........................................................................177 8.4. Independence for Families of Variables......................................................182 8.5. Individual Properties of the Independence Relations...................................186 Chapter 9. Variables Tracking Variables........................................................................189 9.1. Tracking and Conditional Independence: A Summary...............................190 9.2. Strong Tracking............................................................................................ 192 9.3. Strong Tracking and Conditional Independence..........................................198 9.4. Stochastic Subsequence...............................................................................201 9.5. Functional Dependence................................................................................203 9.6. Tracking in Mean.........................................................................................204 9.7. Linear Tracking............................................................................................ 207 9.8. Tracking by Partitions..................................................................................210 9.9. Tracking by Families of Variables...............................................................212 Chapter 10. Variables as Signs of Variables...................................................................215 10.1. Sign................................................................................................ ............219 10.2. Linear Sign................................................................................................ .222 10.3. Scored Sign................................................................................................ 225 10.4. Families of Variables.................................................................................227 Chapter 11. AnTheory of Event Trees.............................................................229 11.1. Event Trees as Sets of Sets........................................................................230 11.2. Event Trees as Partially Ordered Sets........................................................232 iv 11.3. Regular Event Trees...................................................................................240 11.4. The Resolution of Moivrean Variables......................................................244 11.5. Humean Events and Variables...................................................................246 Chapter 12. Martingale Trees..........................................................................................247 12.1. Examples of Decision Trees......................................................................249 12.2. The Meaning of Probability in a Decision Tree.........................................253 12.3. Martingales......................................................................................... .......257 12.4. The Structure of Martingale Trees.............................................................261 12.5. Probability and Causality...........................................................................265 12.6. Lower and Upper Probability.....................................................................269 12.7. The Law of Large Numbers.......................................................................272 12.8. Notes on the Literature...............................................................................274 Chapter 13. Refining............................................................................................ ...........275 13.1. Examples of Refinement............................................................................277 13.2. A Constructive Definition of Finite Refinement.......................................281 13.3. Axioms for Refinement..............................................................................282 13.4. Lifting Moivrean Events and Variables.....................................................288 13.5. Refining Martingale Trees.........................................................................288 13.6. Grounding........................................................................................... .......294 Chapter 14. Principles of Causal Conjecture..................................................................299 14.1. The Diversity of Causal Explanation.........................................................302 14.2. The Mean Effect of the Happening of a Moivrean Event..........................305 14.3. The Effect of a Humean Variable..............................................................311 14.4. Attribution and Generality.........................................................................316 14.5. The Statistical Measurement of the Effect of a Cause...............................319 14.6. Measurement by Experiment.....................................................................320 14.7. Using Our Knowledge of How Things Work............................................322 v 14.8. Sampling Error...........................................................................................329 14.9. The Sampling Frame..................................................................................329 14.10. Notes on the Literature.............................................................................330 Chapter 15. Causal Models.............................................................................................3 31 15.1. The Causal Interpretation of Statistical Prediction....................................333 15.2. Generalizing to a Family of Exogenous Variables....................................337 15.3 Some Joint Causal Diagrams......................................................................339 15.4. Causal Path Diagrams................................................................................342 15.5. Causal Relevance Diagrams.......................................................................346 15.6. The Meaning of Latent Variables..............................................................352 15.7. Notes on the Literature...............................................................................357 Chapter 16. Representing Probability Trees...................................................................359 16.1. Three Graphical Representations...............................................................361 16.2. Skeletal Simplifications.............................................................................368 16.3. Martingale Trees in Type Theory...............................................................371 Appendix A. Huygens’s Probability Trees.....................................................................379 Huygens’s Manuscript in Translation..................................................................380 Appendix B. Some Elements of Graph Theory..............................................................385 B1. Undirected Graphs........................................................................................385 B2. Directed Graphs............................................................................................38 6 Appendix C. Some Elements of Order Theory...............................................................393 C1. Partial and Quasi Orderings.........................................................................393 C2. Singular and Joint Diagrams for Binary Relations.......................................394 C3. Lattices............................................................................................ .............395 C4. The Lattice of Partitions of a Set..................................................................396 Appendix D. The Sample-Space Framework for Probability.........................................399 D1. Probability Measures....................................................................................399 D2. Variables........................................................................................... ...........400 vi D3. Families of Variables...................................................................................401 D4. Expected Value............................................................................................402 D5. The Law of Large Numbers.........................................................................405 D6. Conditional Probability................................................................................406 D7. Conditional Expected Value........................................................................407 Appendix E. Prediction in Probability Spaces................................................................409 E1. Conditional Distribution...............................................................................411 E2. Regression on a Single Variable...................................................................412 E3. Regression on a Partition or a Family of Variables......................................415 E4. Linear Regression on a Single Variable.......................................................418 E5. Linear Regression on a Family of Variables................................................422 Appendix F. Sample-Space Concepts of Independence.................................................425 F1. Overview............................................................................................ ...........426 F2. Independence Proper.....................................................................................432 F3. Unpredictability in Mean..............................................................................434 F4. Simple Uncorrelatedness..............................................................................437 F5. Mixed Uncorrelatedness...............................................................................438 F6. Partial Uncorrelatedness...............................................................................440 F7. Independence for Partitions..........................................................................442 F8. Independence for Families of Variables.......................................................445 F9. The Basic Role of Uncorrelatedness.............................................................448 F10. Dawid’s Axioms.........................................................................................449 Appendix G. Prediction Diagrams..................................................................................453 G1. Path Diagrams............................................................................................ ..454 G2. Generalized Path Diagrams..........................................................................462 G3. Relevance Diagrams.....................................................................................466 G4. Bubbled Relevance Diagrams......................................................................475 Appendix H. Abstract Stochastic Processes...................................................................479 vii H1. Probability Conditionals and Probability Distributions...............................477 H2. Abstract Stochastic Processes......................................................................479 H3. Embedding Variables and Processes in a Sample Space.............................480 References.......................................................................................... ..............................491. (shrink)

Theories of subjective probability are viewed as formal languages for analyzing evidence and expressing degrees of belief. This article focuses on two probability langauges, the Bayesian language and the language of belief functions (Shafer, 1976). We describe and compare the semantics (i.e., the meaning of the scale) and the syntax (i.e., the formal calculus) of these languages. We also investigate some of the designs for probability judgment afforded by the two languages.

Richard Jeffrey's generalization of Bayes' rule of conditioning follows, within the theory of belief functions, from Dempster's rule of combination and the rule of minimal extension. Both Jeffrey's rule and the theory of belief functions can and should be construed constructively, rather than normatively or descriptively. The theory of belief functions gives a more thorough analysis of how beliefs might be constructed than Jeffrey's rule does. The inadequacy of Bayesian conditioning is much more general than Jeffrey's examples of uncertain perception (...) might suggest. The ``parameter α '' that Hartry Field has introduced into Jeffrey's rule corresponds to the "weight of evidence" of the theory of belief functions. (shrink)

ArgumentThe Germans occupying Paris arrested Emile Borel and three other members of the Académie des Sciences in October 1941 and released them about five weeks later. Drawing on German and French archives and other sources, we argue that these events illustrate the complexity of the motivations and tactics of the occupiers and the occupied. While Borel and his colleagues were genuine members of the Resistance, and those who arrested them were full participants in a brutal occupation, both sides respected a (...) bargain, of no small importance to the Vichy regime, that allowed the university to pursue its work if its members avoided overt acts of opposition. (shrink)

Causality in the abstract is a grand theme. We take it up when we want to penetrate to the bottom of things to understand general laws that govern the working at the world of the deepest and most detailed level.In this essay, I argue for a more situated understanding of causality. To counter our desire for ever greater generality, I suggest that causal relations, even those that hold only on average, require context. To counter our desire for ever greater detail, (...) I suggest that causal relations may exist only at a certain level of granularity. (shrink)

In a recent monograph, I advocated a new theory—the theory of belief functions—as an alternative to the Bayesian theory of epistemic probability. In this paper I compare the two theories in the context of a simple but authentic example of assessing evidence.The Bayesian theory is ostensibly the theory that assessment of evidence should proceed by conditioning additive probability distributions; this theory dates from the work of Bayes and Laplace in the second half of the eighteenth century. It is indisputably the (...) dominant theory of epistemic probability today.The theory of belief functions differs from the Bayesian theory in that it uses certain non-additive set functions in the place of additive probability distributions and in that it generalizes the rule of conditioning to a general rule for combining evidence. As a mathematical theory its apparent origin is rather recent and abrupt; it first appears in work of A. P. Dempster, published in the 1960’s. (shrink)

The appreciation of nature and natural beauty demands our attention as environmental issues become ever more urgent. In this timely introduction, Glenn Parsons provides an overview of philosophical work on the aesthetics of nature, identifying key conceptual questions, clarifying central theories, and analyzing the ethical ramifications of our experience of natural beauty. Outlining five major approaches to understanding the aesthetic value of nature, this second edition explores the aesthetic appreciation of nature as it occurs in wilderness, in gardens, and (...) in the context of appreciating environmental art. Now updated to cover recent developments in the field, it includes: · A new chapter on the sublime, the picturesque, and the beautiful · Expanded discussion of empirical and evolutionary accounts of nature appreciation, as well as the appreciation of the environment in non-Western cultures · A new chapter on the aesthetic appreciation of animals · An in-depth analysis of the appreciation of nature through cinema and photography · Discussion of the relation between environmental appreciation and climate change __ Combining a clear and engaging style with a sophisticated treatment of a fascinating subject, _Aesthetics and Nature_ explores the aesthetic dimension of humanity's relationship with our physical surroundings. This a must-read for anyone who cares about nature and the future of our environment. (shrink)

Should we allow performance-enhancing substances in competitive athletics? The first book of its kind, Well Played answers this question by urging us to a deeper appreciation for the purpose of sport. Giving special reference to performance-enhancing substances, Shafer challenges the incompleteness of the ethical arguments and contributes a Christian voice to the discussion. He initiates a theological conversation that is both scholarly and accessible, arguing that a distinctively Christian understanding of sport will have far-reaching implications for how we treat (...) ethical issues like doping. The values, beliefs, and practices within the Christian tradition show an alternative that prioritizes humility and friendship, grace and gratitude over the "win at all costs" mentality that drives the use of performance-enhancing substances for a competitive advantage. This groundbreaking book ventures into new theological territory as it explores the intersections of theology, philosophy of sport, and the ethics of doping. Theologians, ethicists, and pastors, as well as coaches, athletes, and sports fans will benefit from this book's thoughtful reflection on how Christians can play well in the modern sports culture. (shrink)

Living Ethics: An Introduction with Readings is an ideal all-in-one resource for courses in introduction to ethics and contemporary moral problems. In this hybrid textbook/reader, Russ Shafer-Landau brings moral theory and contemporary moral issues to life with a comprehensive and balanced set of readings, uniquely engaging explanations, and clear analysis of arguments. The book balances coverage of moral reasoning (in Part 1) with highly relevant contemporary moral problems (in Part 2).

Introduction -- Value theory : the nature of the good life -- Epicurus letter to Menoeceus -- John Stuart Mill, Hedonism -- Aldous Huxley, Brave new world -- Robert Nozick, The experience machine -- Richard Taylor, The meaning of life -- Jean Kazez, Necessities -- Normative ethics : theories of right conduct -- J.J.C. Smart, Eextreme and restricted utilitarianism -- Immanuel Kant the good will & the categorical imperative -- Thomas Hobbes, Leviathan -- Philippa Foot, Natural goodness -- Aristotle, Nicomachean (...) ethics -- W.D. Ross, What makes right acts right? -- Hilde Lindemann, What is feminist ethics? -- Metaethics : the status of morality -- David Hume, Moral distinctions not derived from reason -- J.L. Mackie, The subjectivity of values -- Gilbert Harman, Ethics and observation -- Mary Midgley, Trying out one's new sword -- Michael Smith, Rrealism -- Renford Bambrough, Pproof -- Moral problems -- Peter Singe, The Singer solution to world poverty -- Heidi Malm, Paid surrogacy: arguments and responses -- Ronald Dworkin, Playing God : genes, clones, and luck -- James Rachels, The morality of euthanasia -- John Harris, The survival lottery -- Peter Singer, Unsanctifying human life -- William F. Baxter, People or penguins : the case for optimal pollution -- Judith Jarvis, Tthomson a defense of abortion -- Don Marquis, Why abortion is immoral -- Jonathan Bennett, The conscience of Huckleberry Finn -- Michael Walzer, Terrorism : a critique of excuses -- David Luban, Liberalism, torture, and the ticking bomb -- Martin Luther King, Jr., Letter from Birmingham City Jail -- Igor Primoratz, Justifying legal punishment -- Stephen Nathanson, An eye for an eye -- Michael Huemer, America's unjust drug war -- John Corvino, Why shouldn't Tommy and Jimmy have sex? : a defense of homosexuality -- Bonnie Steinbock, Adultery -- Hugh Lafollette, Licensing parents -- Jane English, What do grown children owe their parents? (shrink)

This study investigates the relations among Machiavellianism, the stakeholder orientation, and Italian managers' support for corporate social and environmental reporting (SER). These relationships have not previously been investigated among a sample of experienced managers but have important implications. As anticipated, Machiavellianism had a strong negative association with the support for SER. Machiavellianism was also negatively related to the stakeholder orientation, which in turn was positively correlated with the support for SER. Support for the stakeholder orientation partially mediated the association between (...) Machiavellianism and SER. The findings advance our understanding of the motivations for sustainability reporting by documenting that managers' fundamental personality traits and economic ideologies are closely associated and are important determinants of normative support for social and environmental disclosures. We further suggest that the results support the case for mandated compliance‐with‐standard sustainability reports coupled with a requirement that such reports be independently audited. (shrink)

An account of the conflict between our positive and negative emotional relationships to the Earth and how they will be resolved for the Symbiocene, the next period in the history of the Earth.

Americans today seem to be more divided than at any time since the Civil War. Our differences are not just political and moral, but philosophical and even spiritual. Red and Blue America hardly seem to live in the same reality. Something has gone terribly wrong with the American political community. It has been a long time since the people of the United States fully exercised their sovereign authority to choose the officials in government whose primary job is to protect the (...) people's natural rights according to the Constitution. Our political community has become something different. America, our "regime," has become post-constitutional. Yet it is not entirely clear what this post-constitutional arrangement is, how it operates, who is in charge, or how to fix it. Where did this crisis come from? Can it be overcome? What does the future hold for the survival of the American Constitution? Glenn Ellmers--a senior fellow with the Claremont Institute, prolific analyst of current affairs, and scholar of political philosophy--explores the deepest roots of our political turmoil and shows the connections between government bureaucracy, the misuse of science, and the leftwing ideology that controls so much of our public and private life. (shrink)

The evolutionary theory of artefact proper function holds that an artefact’s proper function is that effect which explains the reproduction of past instances of the artefact type. This theory has many sources but received its clearest presentation in Beth Preston’s essay “Why Is a Wing Like a Spoon?”. More recently, Preston has raised an objection to the theory, based on the phenomenon of ‘phantom functions’: these are functions that an artefact type is unable to perform, but which nonetheless apparently constitute (...) its proper function. Deflecting qi energy, for example, is the proper function of feng shui mirrors, even though no feng shui mirror is able to do this. Preston concludes that the existence of phantom functions refutes the evolutionary theory of artefact proper function. In this paper, the evolutionary theory is defended, by arguing that it can adequately account for phantom function cases. (shrink)

The presence of slavery in the Laws has puzzled and distressed many of Plato's admirers. However, before passing judgment on Plato's attitude toward slavery, we must first have a clear idea of the legal status of the slave under Plato's law, and compare it with the slave's position under Greek law of Plato's day. This work sets out to do just that, as well as to provide a good account of Greek law, much of which has been lost over the (...) course of history. (shrink)

Our project in this essay is to showcase nonnaturalistic moral realism’s resources for responding to metaphysical and epistemological objections by taking the view in some new directions. The central thesis we will argue for is that there is a battery of substantive moral propositions that are also nonnaturalistic conceptual truths. We call these propositions the moral fixed points. We will argue that they must find a place in any system of moral norms that applies to beings like us, in worlds (...) similar to our own. By committing themselves to true propositions of these sorts, nonnaturalists can fashion a view that is highly attractive in its own right, and resistant to the most prominent objections that have been pressed against it. (shrink)

Difficulties in distinguishing veridical reports of experience from confabulations have implications for theories of consciousness. I develop some of these implications through a consideration of out-of-body experiences (OBEs). Do these variations indicate individual variation in experience or are they post-hoc confabulations, stories told by subjects to themselves in an attempt to make sense of the core phenomenology? I argue that no existent or possible evidence would be sufficient to favour one hypothesis over the other. How such evidence is interpreted depends (...) on prior commitments to one or other of these hypotheses or to a theory of consciousness that is not neutral as to these hypotheses. One of these types of theory, namely vehicle theories, has difficulty accommodating the existence of confabulations and so allows for only the elaborate phenomenology hypothesis. Because we cannot know that reports are not confabulations, vehicle theories are insufficient to explain OBEs. (shrink)

Simon Blackburn has developed an interesting challenge to moral realism based on its alleged inability to account for supervenience relations between the moral and nonmoral. If supervenience holds, then any base property once giving rise to a supervening one must always do so. The realist accepts supervenience, but also (according to Blackburn) accepts the claim that nonmoral base properties do not necessitate the moral ones that supervene on them. This combination is thought deadly, because it leaves the realist without an (...) explanation of why ethical supervenience should be true. I offer three responses on behalf of the moral realist. The first rejects the need for explanation, arguing that supervenience should be understood as closely analogous to Leibniz's law, which, I argue, needs no defense. I next argue that ethical naturalism may be right, and if so, would provide an adequate response to Blackburn. Lastly, I show that the success of Blackburn's arguments implies a global antirealism, and so does not, as he claims, amount to a special problem for realism in ethics. (shrink)

This book is an account of the life and work of the Russian novelist and political essayist Konstantin Nikolaevich Leontiev, 1831-1891.

Unlocking the debate behind the headlines, this book combines clear thinking with the very latest in science and medicine, enabling readers to decide for themselves exactly what the scientific future should hold.

This chapter contains sections titled: Mothers on Baby Beauty Good Mom, Bad Critic? Beauty, Love, and Prejudice Notes.

Dating back to the early modern theories of Burke and Kant, philosophical accounts have made cognitive failure central to the experience of the sublime. This essay argues for a re-conception of the sublime in terms of the notion of epistemic expansion. Doing so not only provides a plausible account of traditional examples of the sublime, but also provides us with language that can capture an important but neglected aesthetic dimension of experimental science: the expansion of human perception. Recognizing this dimension, (...) it is argued, also enriches our understanding of the ways in which experimental science can facilitate broader public engagement with science. (shrink)

Glenn Kreider explores the whole Bible to show us the full scope of God's active involvement in his creation from the very beginning. This better understanding of God's humility will affect our own humility and our attitude toward serving those around us."--Publisher description.