This work has been selected by scholars as being culturally important and is part of the knowledge base of civilization as we know it. This work is in the public domain in the United States of America, and possibly other nations. Within the United States, you may freely copy and distribute this work, as no entity (individual or corporate) has a copyright on the body of the work. Scholars believe, and we concur, that this work is important enough to be (...) preserved, reproduced, and made generally available to the public. To ensure a quality reading experience, this work has been proofread and republished using a format that seamlessly blends the original graphical elements with text in an easy-to-read typeface. We appreciate your support of the preservation process, and thank you for being an important part of keeping this knowledge alive and relevant. (shrink)

We argue that current discussions of criteria for actual causation are ill-posed in several respects. (1) The methodology of current discussions is by induction from intuitions about an infinitesimal fraction of the possible examples and counterexamples; (2) cases with larger numbers of causes generate novel puzzles; (3) "neuron" and causal Bayes net diagrams are, as deployed in discussions of actual causation, almost always ambiguous; (4) actual causation is (intuitively) relative to an initial system state since state changes are relevant, but (...) most current accounts ignore state changes through time; (5) more generally, there is no reason to think that philosophical judgements about these sorts of cases are normative; but (6) there is a dearth of relevant psychological research that bears on whether various philosophical accounts are descriptive. Our skepticism is not directed towards the possibility of a correct account of actual causation; rather, we argue that standard methods will not lead to such an account. A different approach is required. (shrink)

We argue that current discussions of criteria for actual causation are ill-posed in several respects. (1) The methodology of current discussions is by induction from intuitions about an infinitesimal fraction of the possible examples and counterexamples; (2) cases with larger numbers of causes generate novel puzzles; (3) “neuron” and causal Bayes net diagrams are, as deployed in discussions of actual causation, almost always ambiguous; (4) actual causation is (intuitively) relative to an initial system state since state changes are relevant, but (...) most current accounts ignore state changes through time; (5) more generally, there is no reason to think that philosophical judgements about these sorts of cases are normative; but (6) there is a dearth of relevant psychological research that bears on whether various philosophical accounts are descriptive. Our skepticism is not directed towards the possibility of a correct account of actual causation; rather, we argue that standard methods will not lead to such an account. A different approach is required. Once upon a time a hungry wanderer came into a village. He filled an iron cauldron with water, built a fire under it, and dropped a stone into the water. “I do like a tasty stone soup” he announced. Soon a villager added a cabbage to the pot, another added some salt and others added potatoes, onions, carrots, mushrooms, and so on, until there was a meal for all. (shrink)

By combining experimental interventions with search procedures for graphical causal models we show that under familiar assumptions, with perfect data, N - 1 experiments suffice to determine the causal relations among N > 2 variables when each experiment randomizes at most one variable. We show the same bound holds for adaptive learners, but does not hold for N > 4 when each experiment can simultaneously randomize more than one variable. This bound provides a type of ideal for the measure of (...) success of heuristic approached in active learning methods of casual discovery, which currently use less informative measures. (shrink)

ObjectiveTo compare techniques for computing clustering and switching scores in terms of agreement, correlation, and empirical value as predictors of incident cognitive impairment.MethodsWe transcribed animal and letter F fluency recordings on 640 cases of ICI and matched controls from a national epidemiological study, amending each transcription with word timings. We then calculated clustering and switching scores, as well as scores indexing speed of responses, using techniques described in the literature. We evaluated agreement among the techniques with Cohen’s κ and calculated (...) correlations among the scores. After fitting a base model with raw scores, repetitions, and intrusions, we fit a series of Bayesian logistic regression models adding either clustering and switching scores or speed scores, comparing the models in terms of several metrics. We partitioned the ICI cases into acute and progressive cases and repeated the regression analysis for each group.ResultsFor animal fluency, we found that models with speed scores derived using the slope difference algorithm achieved the best values of the Watanabe–Akaike Information Criterion, but with good net reclassification improvement only for the progressive group. For letter fluency, different models excelled for prediction of acute and progressive cases. For acute cases, NRI was best for speed scores derived from a network model, while for progressive cases, the best model used clustering and switching scores derived from the same network model. Combining variables from the best animal and letter F models led to marginal improvements in model fit and NRI only for the all-cases and acute-cases analyses.ConclusionSpeed scores improve a base model for predicting progressive cognitive impairment from animal fluency. Letter fluency scores may provide complementary information. (shrink)

Originally published between 1968 and 2009, this collection of 25 pieces includes six interviews translated into English for the first time and a new transcription of a Q&A session with Baudrillard following a lecture he gave in London in 1994. The guiding theme of the collection is Baudrillard's engagement with culture. The implications of the implosion of Western culture are dissected and documented in the rich range of material included here.

Peter Spirtes, Richard Scheines and Clark Glymour. Simulated Studies of the Reliability of Computer-Aided Model Specification Using the TETRAD, EQS and LISREL Programs.

In this unique volume, some of today's most eminent political philosophers examine the thought of John Rawls, focusing in particular on his most recent work. These original essays explore diverse issues, including the problem of pluralism, the relationship between constitutive commitment and liberal institutions, just treatment of dissident minorities, the constitutional implications of liberalism, international relations, and the structure of international law. The first comprehensive study of Rawls's recent work, The Idea of Political Liberalism will be indispensable for political philosophers (...) and theorists interested in contemporary political thought. (shrink)

This paper examines how the riparian vegetation of perennial and ephemeral rivers systems in the semi-arid, winter rainfall region of South Africa has changed over time. Using an environmental history approach we assess the extent of change in plant cover at 32 sites using repeat photographs that cover a time span of 36-113 years. The results indicate that in the majority of sites there has been a significant increase in cover of riparian vegetation in both the channel beds and adjacent (...) floodplain environments. The most important species to have increased in cover across the region is Acacia karroo. We interpret the findings in the context of historical changes in climate and land use practices. Damage to riparian vegetation caused by mega-herbivores probably ceased sometime during the early 19th century as did scouring events related to large floods that occurred at regular intervals from the 15th to early 20th centuries. Extensive cutting of riparian vegetation for charcoal and firewood has also declined over the last 150 years. Changes in the grazing history as well as increased abstraction and dam building along perennial rivers in the region also account for some of the changes observed in riparian vegetation during the second half of the 20th century. Predictions of climate change related to global warming anticipate increased drought events with the subsequent loss of species and habitats in the study area. The evidence presented here suggests that an awareness of the region's historical ecology should be considered more carefully in the modelling and formulation of future climate change predictions as well as in the understanding of climate change impacts over time frames of decades and centuries. (shrink)

DNA microarrays are perfectly suited for comparing gene expression in different populations of cells. An important application of microarray techniques is identifying genes which are activated by a particular drug of interest. This process will allow biologists to identify therapies targeted to particular diseases, and, eventually, to gain more knowledge about the biological processes in organisms. Such an application is described in this paper. It is focused on diabetes and obesity, which is a genetically heterogeneous disease, meaning that multiple defective (...) genes are responsible for the diseases. The paper is divided in three parts, each dealing with a different problem addressed to our study. First we validate the data from our microarray experiment. We identified significant systematic sources of variability which are potentially issues for other microarray datasets. Second, we applied multiple hypothesis testing to identify differentially expressed genes. We found a set of genes which appear to change in expression level over time in response to a drug treatment. Third, we tried to address the problem of identification of co-expressed genes using cluster analysis. This last problem is still under discussion. (shrink)

It has been shown in Spirtes(1995) that X and Y are d-separated given Z in a directed graph associated with a recursive or non-recursive linear model without correlated errors if and only if the model entails that ρXY.Z = 0. This result cannot be directly applied to a linear model with correlated errors, however, because the standard graphical representation of a linear model with correlated errors is not a directed graph. The main result of this paper is to show how (...) to associate a directed graph with a linear model L with correlated errors, and then use d-separation in the associated directed graph to determine whether L entails that a particular partial correlation is zero. (shrink)

In an inspirational act of faith and hope, nearly one hundred contributors--social activists, thinkers, artists and spiritual leaders--reflect with poignant candor on our shared human condition and attempt to define a core set of human values in our rapidly changing socity. Contributors include: * The Dalai Lama * Wilma Mankiller * Oscar Arias * Jimmy Carter * Cornel West * Jack Miles * Mother Teresa * Nancy Willard * Elie Wiesel * James Earl Jones * Joan Chittister * Mary Evelyn (...) Tucker * Vaclav Havel * Archbishop Desmund Tutu What Does It Mean To Be Human? is a vital meditation on the endless possibilities of our humanity. (shrink)

Clark Glymour, Richard Scheines, Peter Spirtes and Kevin Kelly. Discovering Causal Structure: Artifical Intelligence, Philosophy of Science and Statistical Modeling.

Written by five scholars whose expertise extends across the disciplines of biblical, historical, systematic, and philosophical theology, this is a careful and ...

The literature on causal discovery has focused on interventions that involve randomly assigning values to a single variable. But such a randomized intervention is not the only possibility, nor is it always optimal. In some cases it is impossible or it would be unethical to perform such an intervention. We provide an account of ‘hard' and ‘soft' interventions and discuss what they can contribute to causal discovery. We also describe how the choice of the optimal intervention(s) depends heavily on the (...) particular experimental setup and the assumptions that can be made. ‡The first author is funded by the Causal Learning Collaborative Initiative supported by the James S. McDonnell Foundation. Many aspects of this paper were inspired by discussions with members of the collaborative. †To contact the authors, please write to: Department of Philosophy, Carnegie Mellon University, Pittsburgh, PA 15213; e-mail: [email protected] and [email protected]. (shrink)

A plea for a clinical year in the course of theological study -- Ethics and the medical profession -- Ethics and business -- Ethics and education -- Ethics and social work.

How shall we distinguish religious delusion from sane religious belief? Making this determination is not usually found to be difficult in clinical practice – but what shall be our theoretical rationale? Attempts to answer this question often try to provide differentiating principles by which the religious “sheep” may be separated from the delusional “goats.” As we shall see, none of these attempts work. We may, however, ask whether the assumption underlying the search for a differentiating principle – that religious beliefs (...) and religious delusions can usefully be considered species of a common genus – is a good one. In this paper, we outline an alternative, “disjunctive,” understanding of religious belief and religious delusion. By reminding ourselves both of what is central to any delusion and of what distinguishes bona fide religious claims from their pretenders, we show how to resolve our reflective puzzlement about religious delusion without recourse to differentiating principles. (shrink)

We present an algorithm to infer causal relations between a set of measured variables on the basis of experiments on these variables. The algorithm assumes that the causal relations are linear, but is otherwise completely general: It provides consistent estimates when the true causal structure contains feedback loops and latent variables, while the experiments can involve surgical or `soft' interventions on one or multiple variables at a time. The algorithm is `online' in the sense that it combines the results from (...) any set of available experiments, can incorporate background knowledge and resolves conflicts that arise from combining results from different experiments. In addition we provide a necessary and sufficient condition that determines when the algorithm can uniquely return the true graph, and can be used to select the next best experiment until this condition is satisfied. We demonstrate the method by applying it to simulated data and the flow cytometry data of Sachs et al. (shrink)

Researchers routinely face the problem of inferring causal relationships from large amounts of data, sometimes involving hundreds of variables. Often, it is the causal relationships between "latent" (unmeasured) variables that are of primary interest. The problem is how causal relationships between unmeasured variables can be inferred from measured data. For example, naval manpower researchers have been asked to infer the causal relations among psychological traits such as job satisfaction and job challenge from a data base in which neither trait is (...) measured directly, but in which answers to interview questions are plausibly associated with each trait. By combining background knowledge with an algorithm that searches for causal structure among the unobserved variables, we have created a tool that can reliably extract useful causal information about latent variables from large data bases. In what follows we describe the class of causal models to which our.. (shrink)

We show that if any number of variables are allowed to be simultaneously and independently randomized in any one experiment, log2(N ) + 1 experiments are sufficient and in the worst case necessary to determine the causal relations among N ≥ 2 variables when no latent variables, no sample selection bias and no feedback cycles are present. For all K, 0 < K <.

Outpatient services are increasingly recognised as an important component of health care provision and may be improved through the application of modern management techniques. We have performed a time and role audit of consultation and waiting times in two medical clinics using different queuing systems: namely, a serial processing clinic where patients wait in a single queue and a quasi-parallel processing clinic where patients are directed to the shortest queue to maintain clinic flow. Data collected were used to construct a (...) computer simulation of patient flows in clinic. Assessment of patient satisfaction in the clinic process was determined using a self-administered questionnaire. Mean waiting time was shorter in the quasi-parallel processing clinic: 26 (SD 17) minutes compared with 36(24) minutes in the serial processing clinic. In the serial processing clinic 61% of patients waited more than 30 minutes compared with 41% in the quasi-parallel processing clinic. In the serial processing clinic 8% of 142 patients surveyed complained of the time spent waiting. The computer simulation we produced was able to determine waiting times with different clinic structures. The simulation showed that reductions in waiting time up to 30% might be achieved by changing our serial processing clinic to a quasi-parallel processing one. Performance of medical outpatient clinics can be improved by examining and changing clinic management. Computer simulation of outpatient clinics offers a means of assessing the impact of such changes on waiting time in clinic and on waiting lists. (shrink)

Clark Glymour, Richard Scheines, Peter Spirtes, and Christopher Meek. Regression and Causation.

Drawing substantive conclusions from linear causal models that perform acceptably on statistical tests is unreasonable if it is not known how alternatives fare on these same tests. We describe a computer program, TETRAD, that helps to search rapidly for plausible alternatives to a given causal structure. The program is based on principles from statistics, graph theory, philosophy of science, and artificial intelligence. We describe these principles, discuss how TETRAD employs them, and argue that these principles make TETRAD an effective tool. (...) Finally, we illustrate TETRAD's effectiveness by applying it to a multiple indicator model of Political and Industrial development. A pilot version of the TETRAD program is described in this paper. The current version is described in our forthcoming Discovering Causal Structure: Artificial Intelligence for Statistical Modeling. (shrink)

The proliferation of digital data and internet-based research technologies is transforming the research landscape, and researchers and research ethics communities are struggling to respond to the ethical issues being raised. This paper discusses the findings from a collaborative project that explored emerging ethical issues associated with the expanding use of digital data for research. The project involved consulting with researchers from a broad range of disciplinary fields. These discussions identified five key sets of issues and informed the development of guidelines (...) orientated to meet the needs of researchers and ethics committee members. We argue that establishing common approaches to assessing ethical risks of research involving digital data will promote consistency in the ethical standards for research, enable the smooth functioning of ethics committees, and sustain public confidence in research. We conclude with recommendations for the development of educational resources for ethics committees, data management guidelines and further public education. (shrink)

Deductive Logic is designed as an intermediate-level text directed at upper-division students from philosophy and the humanities. Its focus is exclusively on deductive logic, avoiding altogether topics such as informal reasoning and scientific method normally included in introductory logic courses. Its exposition of logical topics is informal, with emphasis on explaining the basic concepts and procedures of modern symbolic logic in the simplest and most intuitive manner possible rather than on developing a rigorous formal system and providing proofs of its (...) properties. The fact that the text presupposes a course offered to philosophy students and serves to introduce them to logic as the "language of philosophy" has strongly influenced the selection of topics. The topics here are controversial, and the problems not easily resolved, but this text strives to relate the formal logical structures introduced to issues of philosophic interest. (shrink)

Do our lives have meaning? Should we create more people? Is death bad? Should we commit suicide? Would it be better if we were immortal? Should we be optimistic or pessimistic? Life, Death, and Meaning brings together key readings, primarily by English-speaking philosophers, on such 'big questions.'.