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This book examines the concepts of cause and effect from two dimensions. The first concerns the macrocosm of the Universe and how each belief system views creation. The second dimension explores the ways in which beliefs about creation influence the microcosmic world in terms of the nature of the self, the proximate goals within each system, the answers each belief system offers to the presence of evil and suffering in existence, and ideas about the ultimate goal of release from them. All these ideas inform and are fundamental to the understanding of the present-day practices of different faiths, presenting challenges for scriptural testimony balanced with existential living. The final two chapters explore current research in physics concerning the beginnings of the cosmos and what implications such research might have for existence within it, with the final chapter examining scientific views of the nature of the self.
Causality: Macrocosmic and Microcosmic Theories of Cause and Effect in Belief Systems by Jeaneane Fowler – eBook Details
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- Date of Publication: —
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JUDEA PEARL - HOME
HOMEPUBLICATIONSBIOCAUSALITYPRIMERWHYDANIEL PEARL FOUNDATION
Welcome to my homepage.
To find out what I am up to, new submissions, working papers, adventures and introspections, click here.
For discussions and disputations concerning controversial topics read the Causality Blog.
To view the slides of my tutorial at the Joint Statistical Meetings (JSM-16), Chicago, IL, August 1, 2016, click [ppt] or [pdf].
To view my commencement speech at the University of Toronto June 21, 2007, click here.For transcript, click here.
For a gentle introduction to my current research on causality, [click 1 or 2].
Transcript and slides of 1996 Faculty Research Lecture: The Art and Science of Cause and Effect
Transcript and slides of 1999 IJCAI Award Lecture: Reasoning with Cause and Effect
Technical material supporting the story in 1-2, can be found [postscript] or [pdf] in:
- (R-350): [pdf]
J. Pearl, 'Causal inference in statistics: An overview,' Statistics Surveys, 3:96--146, 2009. - (R-264): [pdf]
J. Pearl, ``Simpson's paradox: An anatomy' Extracted from Chapter 6 of CAUSALITY. - (R-218-B): [postscript][pdf]
J. Pearl, 'Causal Diagrams for Empirical Research' Biometrika, 82(4), 669--710, December 1995.
Key publications related to causality
Causality Free Download Mac
- (R-320):[postscript][pdf]
J. Pearl, 'Robustness of Causal Claims' In Proceedings of the 20th Conference on Uncertainty in Artificial Intelligence, AUAI Press: Arlington, VA, 446-453, July 2004. - (R-290):[pdf]
J. Tian and J. Pearl, 'A General Identification Condition for Causal Effects' In Proceedings of the Eighteenth Conference on Artificial Intelligence, AAAI/The MIT Press: Menlo Park, 567-573, August 2002. - (R-273-U): [postscript][pdf]
J. Pearl, 'Direct and Indirect Effects' In Proceedings of the Seventeenth Conference on Uncertainty in Artificial Intelligence, San Francisco, CA: Morgan Kaufmann, 411-420, 2001. - (R-266-Part1):[pdf]
J.Y. Halpern and J. Pearl, 'Causes and explanations: A structural-model approach- -- Part I: Causes' In British Journal of Philosophy of Science, 56:843-887, 2005.
- (R-266-Part2): [pdf]
J.Y. Halpern and J. Pearl, 'Causes and explanations: A structural-model approach- -- Part II: Explanations' In British Journal of Philosophy of Science, 56:889-911, 2005.
- (R-269): [postscript][pdf]
J. Pearl, 'The logic of counterfactuals in causal inference (Discussion of `Causal inference without counterfactuals' by A.P. Dawid),' In Journal of American Statistical Association, Vol. 95, No. 450, 428--435, June 2000. - (R-271-A): [postscript][pdf]
J. Tian and J. Pearl, 'Probabilities of causation: Bounds and identification' In Annals of Mathematics and Artificial Intelligence, Vol. 28, 287--313, 2000.