Results for 'Rcihard Scheines'

290 found
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  1.  53
    Causality From Probability.Peter Spirtes, Clark Glymour & Rcihard Scheines - unknown
  2.  45
    Plurals and Events.Barry Schein - 1993 - MIT Press.
    Barry Schein proposes combining a second-order treatment of plurals with DonaldDavidson's suggestion that there are positions for reference to events in ordinary predicates inorder to account for several of the more puzzling features of ...
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  3.  35
    Piecewise linear instrumental variable estimation of causal influence.Richard Scheines - unknown
    Dept. of Philosophy Center for Biomedical Center for Biomedical Dept. of Philosophy Carnegie Mellon Univ.
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  4.  14
    Simulating Genetic Regulartory Networks.Richard Scheines & Joe Ramsey - unknown
    Richard Scheines and Joe Ramsey. Simulating Genetic Regulartory Networks.
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  5.  21
    Combining Experiments to Discover Linear Cyclic Models with Latent Variables.Richard Scheines, Frederick Eberhardt & Patrik O. Hoyer - unknown
    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 (...)
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  6.  49
    Building Latent Variable Models'.Richard Scheines, Peter Spirtes & Clark Glymour - unknown
    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 (...)
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  7.  43
    Expert statistical testimony and epidemiological evidence: The toxic effects of lead exposure on children.Richard Scheines - unknown
    The past two decades have seen a dramatic growth in the use of statisticians and economists for the presentation of expert testimony in legal proceedings. In this paper, we describe a hypothetical case modeled on real ones and involving statistical testimony regarding the causal effect of lead on lowering the IQs of children who ingest lead paint chips. The data we use come from a well-known pioneering study on the topic and the analyses we describe as the expert testimony are (...)
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  8. Text and transnational subjectification : Media's challenge to anthropology.Louisa Schein - 2008 - In E. Neni K. Panourgia & George E. Marcus (eds.), Ethnographica moralia: experiments in interpretive anthropology. New York, NY: Fordham University Press.
     
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  9.  45
    Noughty bits: the subatomic scope of negation.Barry Schein - 2016 - Linguistics and Philosophy 39 (6):459-540.
    Since Fodor 1970, negation has worn a Homogeneity Condition to the effect that homogeneous predicates, ) denote homogeneously—all or nothing —to characterize the meaning of – when uttered out-of-the blue, in contrast to –:The mirrors are smooth. The mirrors are not smooth. The mirrors circle the telescope’s reflector. The mirrors do not circle the telescope’s reflector. It has been a problem for philosophical logic and for the semantics of natural language that – appear to defy the Principle of Excluded Middle (...)
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  10.  58
    Plurals.Barry Schein - 2005 - In Ernie Lepore & Barry C. Smith (eds.), The Oxford Handbook of Philosophy of Language. Oxford, England: Oxford University Press. pp. 716--767.
    Extension of the logical language to deliver plural reference and the logical relations that constitute knowledge of the singular and plural acquires empirical bite just in case it conforms with increasing precision to the syntax of the natural language and affords explanation of what speakers know about the distribution and meaning of plural expressions in their language. As for the syntax of natural language, this discussion, being none too precise, is guided throughout by just two considerations and their immediate consequences, (...)
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  11.  11
    Euripides and the Politics of Form by Victoria Wohl.Seth L. Schein - 2016 - Classical World: A Quarterly Journal on Antiquity 110 (1):143-144.
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  12. Interventions and causal inference.Frederick Eberhardt & Richard Scheines - 2007 - Philosophy of Science 74 (5):981-995.
    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 (...)
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  13.  89
    The Similarity of Causal Inference in Experimental and Non‐experimental Studies.Richard Scheines - 2005 - Philosophy of Science 72 (5):927-940.
    For nearly as long as the word “correlation” has been part of statistical parlance, students have been warned that correlation does not prove causation, and that only experimental studies, e.g., randomized clinical trials, can establish the existence of a causal relationship. Over the last few decades, somewhat of a consensus has emerged between statisticians, computer scientists, and philosophers on how to represent causal claims and connect them to probabilistic relations. One strand of this work studies the conditions under which evidence (...)
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  14.  18
    An experimental comparison of alternative proof construction environments.Richard Scheines & Wilfried Sieg - unknown
    : "In this paper we compare computerized environments in which students complete proof construction exercises in formal logic. Afterbeing given a pretest for logical aptitude, three matched groups were presented identical course material on logic for approximately five weeks by a computer. During the treatment, all students were required to complete several hundred proof construction exercises. The three groups did the exercises and the midterm in different environments. The group with a more sophisticated interface performed better on the midterm. Nearly (...)
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  15.  77
    Adverbial, descriptive reciprocals.Barry Schein - 2003 - Philosophical Perspectives 17 (1):333–367.
  16.  65
    Events and the semantic content of thematic relations.Barry Schein - 2002 - In Gerhard Preyer & Georg Peter (eds.), Logical Form and Language. Oxford, England: Oxford University Press. pp. 263--344.
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  17. An introduction to causal inference.Richard Scheines - unknown
    In Causation, Prediction, and Search (CPS hereafter), Peter Spirtes, Clark Glymour and I developed a theory of statistical causal inference. In his presentation at the Notre Dame conference (and in his paper, this volume), Glymour discussed the assumptions on which this theory is built, traced some of the mathematical consequences of the assumptions, and pointed to situations in which the assumptions might fail. Nevertheless, many at Notre Dame found the theory difficult to understand and/or assess. As a result I was (...)
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  18. Discovering Causal Structure: Artificial Intelligence, Philosophy of Science, and Statistical Modeling.Clark Glymour, Richard Scheines, Peter Spirtes & Kevin Kelly - 1987 - Academic Press.
    Clark Glymour, Richard Scheines, Peter Spirtes and Kevin Kelly. Discovering Causal Structure: Artifical Intelligence, Philosophy of Science and Statistical Modeling.
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  19.  39
    Single Mother's Efficacy, Parenting in the Home Environment, and Children's Development in a Two-Wave Study.Aurora P. Jackson & Richard Scheines - unknown
    Aurora P. Jackson and Richard Scheines. Single Mother's Efficacy, Parenting in the Home Environment, and Children's Development in a Two-Wave Study.
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  20.  49
    Computer Environments for Proof Construction.Richard Scheines & Wilfried Sieg - unknown
    Richard Scheines and Wilfred Sieg. Computer Environments for Proof Construction.
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  21.  33
    Nip and tuck for definite description.Barry Schein - 2019 - Linguistics and Philosophy 42 (2):177-206.
    Speaking of dental floss contaminated with bacteria, I may separate the dental floss that is sterile from the dental floss that isn’t sterile. The definite description “the dental floss that isn’t sterile” contracts its reference to just the dental floss near bacteria, although it, the dental floss whole, isn’t sterile. To accommodate the definite descriptions that contract their reference, received definitions for ⌜the Φ⌝ are amended from to read as in : ⌜the Φ⌝ refers to that which any Φ is (...)
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  22.  55
    Bayesian estimation and testing of structural equation models.Richard Scheines - unknown
    The Gibbs sampler can be used to obtain samples of arbitrary size from the posterior distribution over the parameters of a structural equation model (SEM) given covariance data and a prior distribution over the parameters. Point estimates, standard deviations and interval estimates for the parameters can be computed from these samples. If the prior distribution over the parameters is uninformative, the posterior is proportional to the likelihood, and asymptotically the inferences based on the Gibbs sample are the same as those (...)
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  23.  19
    (2 other versions)The eyes are the window to the uncanny valley.Chelsea Schein & Kurt Gray - 2015 - Interaction Studies. Social Behaviour and Communication in Biological and Artificial Systemsinteraction Studies / Social Behaviour and Communication in Biological and Artificial Systemsinteraction Studies 16 (2):173-179.
    Horror movies have discovered an easy recipe for making people creepy: alter their eyes. Instead of normal eyes, zombies’ eyes are vacantly white, vampires’ eyes glow with the color of blood, and those possessed by demons are cavernously black. In the Academy Award winning Pan’s Labyrinth, director Guillermo del Toro created the creepiest of all creatures by entirely removing its eyes from its face, placing them instead in the palms of its hands. The unease induced by altering eyes may help (...)
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  24.  69
    Uniform consistency in causal inference.Richard Scheines & Peter Spirtes - unknown
    S There is a long tradition of representing causal relationships by directed acyclic graphs (Wright, 1934 ). Spirtes ( 1994), Spirtes et al. ( 1993) and Pearl & Verma ( 1991) describe procedures for inferring the presence or absence of causal arrows in the graph even if there might be unobserved confounding variables, and/or an unknown time order, and that under weak conditions, for certain combinations of directed acyclic graphs and probability distributions, are asymptotically, in sample size, consistent. These results (...)
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  25.  26
    Genetic Algorithm Search Over Causal Models.Shane Harwood & Richard Scheines - unknown
    Shane Harwood and Richard Scheines. Genetic Algorithm Search Over Causal Models.
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  26.  34
    Learning Linear Causal Structure Equation Models with Genetic Algorithms.Shane Harwood & Richard Scheines - unknown
    Shane Harwood and Richard Scheines. Learning Linear Causal Structure Equation Models with Genetic Algorithms.
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  27.  33
    The Limits of Causal Knowledge.James M. Robins, Richard Scheines, Peter Spirtes & Larry Wasserman - unknown
    James M. Robins, Richard Scheines, Peter Spirtes, and Larry Wasserman. The Limits of Causal Knowledge.
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  28.  34
    A Response Time Model for Bottom-Out Hints as Worked Examples.Richard Scheines - unknown
    Students can use an educational system’s help in unexpected ways. For example, they may bypass abstract hints in search of a concrete solution. This behavior has traditionally been labeled as a form of gaming or help abuse. We propose that some examples of this behavior are not abusive and that bottom-out hints can act as worked examples. We create a model for distinguishing good student use of bottom-out hints from bad student use of bottom-out hints by means of logged response (...)
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  29. Combining Experiments to Discover Linear Cyclic Models.Richard Scheines - unknown
    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 (...)
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  30.  39
    Teaching and Learning with Online Courses.Richard Scheines, Gaea Leinhardt, Joel Smith & Kwangsu Cho - unknown
    Richard Scheines, Gaea Leinhardt, Joel Smith, and Kwangsu Cho. Teaching and Learning with Online Courses.
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  31.  12
    Reading Homer in Dark Times: Rachel Bespaloff's On the Iliad.Seth L. Schein - 2018 - Arion 26 (1):17.
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  32.  62
    On the Number of Experiments Sufficient and in the Worst Case Necessary to Identify All Causal Relations Among N Variables.Clark Glymour & Richard Scheines - unknown
    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 <.
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  33.  35
    Attractiveness bias: A cognitive explanation.Stevie S. Schein, Logan T. Trujillo & Judith H. Langlois - 2017 - Behavioral and Brain Sciences 40.
    According to cognitive averaging theory, preferences for attractive faces result from their similarity to facial prototypes, the categorical central tendencies of a population of faces. Prototypical faces are processed more fluently, resulting in increased positive affect in the viewer.
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  34.  66
    Causation.Richard Scheines - unknown
    Practically, causation matters. Juries must decide, for example, whether a pregnant mother’s refusal to give birth by caesarean section was the cause of one of her twins death. Policy makers must decide whether violence on TV causes violence in life. Neither question can be coherently debated without some theory of causation. Fortunately (or not, depending on where one sits), a virtual plethora of theories of causation have been championed in the third of a century between 1970 and 2004.
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  35.  52
    Causation, statistics, and the law.Richard Scheines - unknown
    More and more, judges and juries are being asked to handle torts and other cases in which establishing liability involves understanding large bodies of complex scientific evidence. When establishing causation is involved, the evidence can be diverse, can involve complicated statistical models, and can seem impenetrable to non-experts. Since the decision in Daubert v. Merril Dow Pharms., Inc.1 in 1993, judges cannot simply admit expert testimony and other technical evidence and let jurors decide the verdict. Judges now must rule on (...)
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  36.  82
    The tetrad project: Constraint based aids to causal model specification.Richard Scheines - 1998 - Multivariate Behavioral Research 33 (1):65-117.
    The statistical community has brought logical rigor and mathematical precision to the problem of using data to make inferences about a model’s parameter values. The TETRAD project, and related work in computer science and statistics, aims to apply those standards to the problem of using data and background knowledge to make inferences about a model’s specification. We begin by drawing the analogy between parameter estimation and model specification search. We then describe how the specification of a structural equation model entails (...)
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  37. Cruelty: A Book About Us.Maggie Schein - 2023 - Springer Verlag.
    Cruelty is such a ubiquitous and at the same time disturbing phenomenon that we take for granted that we understand what it is, and how it impacts the ways in which we think about our humanity as a moral condition—how we understand our moral significance. Cruelty: A Book About Us offers an accessible interrogation of cruelty and humanity, and, most critically, it provides a groundwork for us to raise questions collectively; it is an invitation for us all to join in (...)
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  38.  26
    (2 other versions)Computation and Causation.Richard Scheines - 2002 - Metaphilosophy 33 (1‐2):158-180.
    The computer’s effect on our understanding of causation has been enormous. By the mid‐1980s, philosophical and social‐scientific work on the topic had left us with (1) no reasonable reductive account of causation and (2) a class of statistical causal models tied to linear regression. At this time, computer scientists were attacking the problem of equipping robots with models of the external that included probabilistic portrayals of uncertainty. To solve the problem of efficiently storing such knowledge, they introduced Bayes Networks and (...)
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  39.  63
    Causation, truth, and the law.Richard Scheines - unknown
    Deciding matters of legal liability, in torts and other civil actions, requires deciding causation. The injury suffered by a plaintiff must be caused by an event or condition due to the defendant. The courts distinguish between cause-in-fact and proximate causation, where cause-in-fact is determined by the “but-for” test: the effect would not have happened, “but for” the cause.1 Proximate causation is a set of legal limitations on cause-in-fact.
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  40.  41
    Estimating latent causal influences: Tetrad III variable selection and bayesian parameter estimation.Richard Scheines - unknown
    The statistical evidence for the detrimental effect of exposure to low levels of lead on the cognitive capacities of children has been debated for several decades. In this paper I describe how two techniques from artificial intelligence and statistics help make the statistical evidence for the accepted epidemiological conclusion seem decisive. The first is a variable-selection routine in TETRAD III for finding causes, and the second a Bayesian estimation of the parameter reflecting the causal influence of Actual Lead Exposure, a (...)
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  41. 'Multiple Alterities: The Contouring of Gender in Miao and Chinese Nationalisms'.Louisa Schein - 1996 - In Brackette F. Williams (ed.), Women out of place: the gender of agency and the race of nationality. New York: Routledge. pp. 79--102.
  42.  34
    Replacing Lecture with Web-Based Course Materials.Richard Scheines, Gaea Leinhardt, Joel Smith & Kwangsu Cho - unknown
    In a series of 5 experiments in 2000 and 2001, several hundred students at two different universities with three different professors and six different teaching assistants took a semester long course on causal and statistical reasoning in either traditional lecture/recitation or online/recitation format. In this paper we compare the pre-post test gains of these students, we identify features of the online experience that were helpful and features that were not, and we identify student learning strategies that were effective and those (...)
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  43.  64
    Independence Relations Produced by Parameter Values in Causal Models.Richard Scheines - 1990 - Philosophical Topics 18 (2):55-70.
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  44. Reply to Freedman.Richard Scheines - unknown
    In Causation, Prediction, and Search, we undertook a three part project. First, we characterized when causal models are indistinguishable by population conditional independence relations under several different assumptions relating causality to probability. Second, we proposed a number of algorithms that take sample data and optional background knowledge as input, and output a class of causal models compatible with the data and the background knowledge; the algorithms were accompanied by proofs of their correctness given assumptions that were clearly stated in CPS, (...)
     
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  45.  61
    An Induction Game.Spencer Schein - 1975 - Teaching Philosophy 1 (1):47-49.
  46.  68
    Teaching the normative theory of causal reasoning.Richard Scheines, Matt Easterday & David Danks - 2007 - In Alison Gopnik & Laura Schulz (eds.), Causal learning: psychology, philosophy, and computation. New York: Oxford University Press. pp. 119--38.
    There is now substantial agreement about the representational component of a normative theory of causal reasoning: Causal Bayes Nets. There is less agreement about a normative theory of causal discovery from data, either computationally or cognitively, and almost no work investigating how teaching the Causal Bayes Nets representational apparatus might help individuals faced with a causal learning task. Psychologists working to describe how naïve participants represent and learn causal structure from data have focused primarily on learning from single trials under (...)
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  47.  25
    Unidimensional Linear Latent Variable Models.Richard Scheines - unknown
    Linear structural equation models with latent (unmeasured) variables are used widely in sociology, psychometrics, and political science. When such models have a unidimensional..
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  48.  31
    N − 1 Experiments Suffice to Determine the Causal Relations Among N Variables.Frederick Eberhardt, Clark Glymour & Richard Scheines - unknown
    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 (...)
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  49. Coherence and Confirmation through Causation.Gregory Wheeler & Richard Scheines - 2013 - Mind 122 (485):135-170.
    Coherentism maintains that coherent beliefs are more likely to be true than incoherent beliefs, and that coherent evidence provides more confirmation of a hypothesis when the evidence is made coherent by the explanation provided by that hypothesis. Although probabilistic models of credence ought to be well-suited to justifying such claims, negative results from Bayesian epistemology have suggested otherwise. In this essay we argue that the connection between coherence and confirmation should be understood as a relation mediated by the causal relationships (...)
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  50.  30
    Time and Attention: Students, Sessions, and Tasks.Andrew Arnold, Richard Scheines, Joseph E. Back & Bill Jerome - unknown
    Students in two classes in the fall of 2004 making extensive use of online courseware were logged as they visited over 500 different “learning pages” which varied in length and in difficulty. We computed the time spent on each page by each student during each session they were logged in. We then modeled the time spent for a particular visit as a function of the page itself, the session, and the student. Surprisingly, the average time a student spent on learning (...)
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