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References

Published online by Cambridge University Press:  20 October 2021

David A. Lagnado
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University College London
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Explaining the Evidence
How the Mind Investigates the World
, pp. 282 - 298
Publisher: Cambridge University Press
Print publication year: 2021

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References

Achinstein, P. (2001). The book of evidence. New York: Oxford University Press.Google Scholar
Alicke, M. D., Mandel, D. R., Hilton, D. J., Gerstenberg, T., & Lagnado, D. A. (2015). Causal conceptions in social explanation and moral evaluation: A historical tour. Perspectives on Psychological Science, 10(6), 790812.Google Scholar
Allen, R. J., & Pardo, M. S. (2019). Relative plausibility and its critics. The International Journal of Evidence & Proof, 23(1–2), 559.Google Scholar
Anderson, J. R. (1996). ACT: A simple theory of complex cognition. American Psychologist, 51(4), 355.Google Scholar
Anderson, T., Schum, D., & Twining, W. (2005). Analysis of evidence. New York: Cambridge University Press.CrossRefGoogle Scholar
Austerweil, J. L., & Griffiths, T. L. (2011). A rational model of the effects of distributional information on feature learning. Cognitive Psychology, 63(4), 173209.CrossRefGoogle ScholarPubMed
Bales, R. (2002). The great Chicago fire and the myth of Mrs. O’Leary’s cow. Jefferson, NC: McFarland.Google Scholar
Banks, D. L., Kafadar, K., Kaye, D. H., & Tackett, M. (Eds.). (2020). Handbook of forensic statistics. Boca Raton, FL: CRC Press.Google Scholar
Barbey, A. K., & Sloman, S. B. (2007). Base-rate respect: From ecological rationality to dual processes. Behavioral and Brain Sciences, 30(3), 241254.Google Scholar
Baron, R. A. (2004). The cognitive perspective: A valuable tool for answering entrepreneurship’s basic ‘why’ questions. Journal of Business Venturing, 19(2), 221239.CrossRefGoogle Scholar
Barrett, E. C. (2009). The interpretation and exploitation of information in criminal investigations [Unpublished doctoral dissertation]. University of Birmingham.Google Scholar
Battaglia, P. W., Hamrick, J. B., & Tenenbaum, J. B. (2013). Simulation as an engine of physical scene understanding. Proceedings of the National Academy of Sciences, 110(45), 1832718332.CrossRefGoogle ScholarPubMed
Bayes, T. (1763). An essay towards solving a problem in the doctrine of chances. Philosophical Transactions of the Royal Society of London, 53 (53), 370–418.Google Scholar
Bechlivanidis, C., Lagnado, D. A., Zemla, J. C., & Sloman, S. (2017). Concreteness and abstraction in everyday explanation. Psychonomic Bulletin & Review, 24(5), 14511464.Google Scholar
Beer, I., Ben-David, S., Chockler, H., Orni, A., & Trefler, R. (2012). Explaining counterexamples using causality. Formal Methods in System Design, 40(1), 2040.Google Scholar
Bennett, W. L., & Feldman, M. S. (1981). Reconstructing reality in the courtroom. Alameda, CA: Tavistock.Google Scholar
Bentham, J. (1843). The works of Jeremy Bentham (Vol. 6). Edinburgh: W. Tait.Google Scholar
Bes, B., Sloman, S., Lucas, C. G., & Raufaste, É. (2012). Non‐Bayesian inference: Causal structure trumps correlation. Cognitive Science, 36(7), 11781203.Google Scholar
Bilton, M. (2012). Wicked beyond belief: The hunt for the Yorkshire ripper. New York: Harper.Google Scholar
Bingham, T. (2006). Assessing contentious eyewitness evidence: A judicial review. In Heaton-Armstrong, A., Shepherd, E., Gudjonsson, G., & Wolchover, D. (Eds.), Witness testimony: Psychological, investigative and evidence perspectives (2nd ed., pp. 327345). Oxford: Oxford University Press.CrossRefGoogle Scholar
Botvinick, M., Ritter, S., Wang, J. X., Kurth-Nelson, Z., Blundell, C., & Hassabis, D. (2019). Reinforcement learning, fast and slow. Trends in Cognitive Sciences, 23(5), 408422.CrossRefGoogle ScholarPubMed
Bovens, L., & Hartmann, S. (2002). Bayesian networks and the problem of unreliable instruments. Philosophy of Science, 69(1), 29–72.Google Scholar
Bovens, L., & Hartmann, S. (2003). Bayesian epistemology. Oxford University Press, on demand.Google Scholar
Bramley, N. R., Dayan, P., Griffiths, T. L., & Lagnado, D. A. (2017). Formalizing Neurath’s ship: Approximate algorithms for online causal learning. Psychological Review, 124(3), 301338.CrossRefGoogle ScholarPubMed
Brem, S. K., & Rips, L. J. (2000). Explanation and evidence in informal argument. Cognitive Science, 24(4), 573604.Google Scholar
Buck, U., Naether, S., Räss, B., Jackowski, C., & Thali, M. J. (2013). Accident or homicide – Virtual crime scene reconstruction using 3D methods. Forensic Science International, 225(1–3), 7584.Google Scholar
Buehler, R., Griffin, D., & Ross, M. (1994). Exploring the ‘planning fallacy’: Why people underestimate their task completion times. Journal of Personality and Social Psychology, 67(3), 366381.CrossRefGoogle Scholar
Carey, S. (1995). On the origin of causal understanding. In Sperber, D., Premack, D., & Premack, A. J. (Eds.), Symposia of the Fyssen Foundation. Causal cognition: A multidisciplinary debate (pp. 268308). Oxford: Clarendon Press/Oxford University Press.Google Scholar
Cartwright, N., & Hardie, J. (2012). Evidence-based policy: A practical guide to doing it better. New York: Oxford University Press.Google Scholar
Chi, M. T., De Leeuw, N., Chiu, M. H., & LaVancher, C. (1994). Eliciting self-explanations improves understanding. Cognitive Science, 18(3), 439477.Google Scholar
Chisum, W. J., & Turvey, B. E. (2011). Crime reconstruction. Cambridge, MA: Academic Press.Google Scholar
Coenen, A., Nelson, J. D., & Gureckis, T. M. (2018). Asking the right questions about the psychology of human inquiry: Nine open challenges. Psychonomic Bulletin and Review, 74, 141.Google Scholar
Conan Doyle, A. (1891). A scandal in Bohemia. The adventures of Sherlock Holmes (pp. 5–29).Google Scholar
Conan Doyle, A. (1892). Silver blaze. Strand Magazine.Google Scholar
Cook, R., Evett, I. W., Jackson, G., Jones, P. J., & Lambert, J. A. (1998). A hierarchy of propositions: Deciding which level to address in casework. Science & Justice, 4(38), 231239.CrossRefGoogle Scholar
Cornish, D. B., & Clarke, R. V. (1987). Understanding crime displacement: An application of rational choice theory. Criminology, 25(4), 933948.Google Scholar
Cornish, D. B., & Clarke, R. V. (Eds.). (2014). The reasoning criminal: Rational choice perspectives on offending. New Brunswick: Transaction Publishers.Google Scholar
Craik, K. J. W. (1952). The nature of explanation. Cambridge: Cambridge University Press.Google Scholar
Crisp, A., & Feeney, A. (2009). Causal conjunction fallacies: The roles of causal strength and mental resources. Quarterly Journal of Experimental Psychology, 62(12), 23202337 .Google Scholar
Crown Court Compendium (2020). Part I: Jury and Trial Management and Summing Up. Judicial College (England and Wales). www.judiciary.uk/wp-content/uploads/2020/12/Crown-Court-Compendium-Part-I-December-2020-amended-01.02.21.pdfGoogle Scholar
Crupi, V., Tentori, K., & Gonzalez, M. (2007). On Bayesian measures of evidential support: Theoretical and empirical issues. Philosophy of Science, 74, 229252.Google Scholar
Cruz, N., Connor Desai, S., Dewitt, S., Hahn, U., Lagnado, D., Liefgreen, A., … Tesic, M. (2020). Widening access to Bayesian problem solving. Frontiers in Psychology, 11, 660.CrossRefGoogle ScholarPubMed
Curley, L. J., Munro, J., Lages, M., MacLean, R., & Murray, J. (2020). Assessing cognitive bias in forensic decisions: A review and outlook. Journal of Forensic Sciences, 65(2), 354360.CrossRefGoogle ScholarPubMed
Danks, D. (2014). Unifying the mind: Cognitive representations as graphical models. Cambridge, MA: MIT Press.Google Scholar
Danks, D. (2018). Privileged (default) causal cognition: A mathematical analysis. Frontiers in Psychology, 9, 498.Google Scholar
Dawid, A. P. (2000). Causal inference without counterfactuals. Journal of the American Statistical Association, 95(450), 407424.CrossRefGoogle Scholar
Dawid, A. P. (2002). Bayes’s theorem and weighing evidence by juries. In Proceedings of the British Academy (Vol. 113, pp. 7190). Oxford: Oxford University Press.Google Scholar
Dawid, A. P. (2005). Statistics on trial. Significance, 2(1), 68.Google Scholar
Dawid, A. P. (2021). The tale wags the DAG. In Dechter, R, Geffner, H., and Halpern, J (Eds.), Probabilistic and causal inference: The works of Judea Pearl. New York: Association for Computing Machinery.Google Scholar
Dawid, A. P., & Evett, I. W. (1997). Using a graphical method to assist the evaluation of complicated patterns of evidence. Journal of Forensic Science, 42(2), 226231.Google Scholar
Dawid, A. P., & Mortera, J. (2020). Bayesian networks in forensic science. In Banks, D, Kafadar, K., Kaye, D. H., & Tackett, M (Eds.), Handbook of forensic statistics (pp. 165197). Boca Raton, FL: CRC Press.CrossRefGoogle Scholar
Dennis, I. H. (2007). The law of evidence. London: Sweet & Maxwell.Google Scholar
Dennis, M. J., & Ahn, W. (2001). Primacy in causal strength judgments. Memory & Cognition, 29, 152164.Google Scholar
Denrell, J. (2005). Selection bias and the perils of benchmarking. Harvard Business Review, 83(4), 114–119.Google Scholar
Denrell, J., & March, J. G. (2001). Adaptation as information restriction: The hot stove effect. Organization Science, 12(5), 523538.Google Scholar
Devine, D. J. (2012). Jury decision making: The state of the science (Vol. 8). New York: New York University Press.Google Scholar
Devroye, L. (2006). Nonuniform random variate generation. Handbooks in Operations Research and Management Science, 13, 83121.Google Scholar
Dewitt, S., Fenton, N., Liefgreen, A., & Lagnado, D. A. (2020). Propensities and second order uncertainty: A modified taxi cab problem. Frontiers in Psychology, 11, 503233.CrossRefGoogle ScholarPubMed
Dewitt, S., Lagnado, D. A., & Fenton, N. (2018). Updating prior beliefs based on ambiguous evidence. In Kalish, C., Rau, M., Zhu, J., & Rogers, T. T. (Eds.), Proceedings of the 40th Annual Conference of the Cognitive Science Society (pp. 20472052). Austin, TX: Cognitive Science Society.Google Scholar
Dostoevsky, F. (1866/1957). Crime and punishment (Garnett, C., Trans.). London: Folio Society.Google Scholar
Dougherty, M. R., Gettys, C. F., & Thomas, R. P. (1997). The role of mental simulation in judgments of likelihood. Organizational Behavior and Human Decision Processes, 70(2), 135148.CrossRefGoogle Scholar
Dror, I. E. (2018). Biases in forensic experts. Science, 360(6386), 243.CrossRefGoogle ScholarPubMed
Dror, I. E., & Charlton, D. (2006). Why experts make errors. Journal of Forensic Identification, 56(4), 600.Google Scholar
Dror, I. E., Morgan, R. M., Rando, C., & Nakhaeizadeh, S. (2017). The bias snowball and the bias cascade effects: Two distinct biases that may impact forensic decision making [Letter to the editor]. Journal of Forensic Sciences, 62(3), 832833.CrossRefGoogle ScholarPubMed
Edwards, W. (1991). Influence diagrams, Bayesian imperialism, and the Collins case: An appeal to reason. Cardozo Law Review, 13, 1025.Google Scholar
Eggleston, R. (1978). Wigmore, fact-finding and probability. Monash University Law Review, 15(3), 370–382.Google Scholar
Evans, J. S. B. (1989). Bias in human reasoning: Causes and consequences. Brighton: Erlbaum.Google Scholar
Evans, J. S. B. (2007). Hypothetical thinking: Dual processes in reasoning and judgement. London: Psychology Press.Google Scholar
Fenton, N. (2014). Assessing evidence and testing appropriate hypotheses. Science and Justice, 54(6), 502504.Google Scholar
Fenton, N. (2020). A note on ‘Collider bias undermines our understanding of COVID-19 disease risk and severity’ and how causal Bayesian networks both expose and resolve the problem. arXiv preprint arXiv:2005.08608.Google Scholar
Fenton, N., Lagnado, D., Dahlman, C., & Neil, M. (2019). The opportunity prior: A proof-based prior for criminal cases. Law, Probability and Risk, 18(4), 237253.Google Scholar
Fenton, N., Lagnado, D., Hsu, A., Berger, D., & Neil, M. (2014). Response to ‘On the use of the likelihood ratio for forensic evaluation: Response to Fenton et al.’. Science Justice, 54(4), 319320.Google Scholar
Fenton, N., & Neil, M. (2018). Risk assessment and decision analysis with Bayesian networks. New York: Chapman and Hall/CRC.CrossRefGoogle Scholar
Fenton, N., Neil, M., & Lagnado, D. A. (2013). A general structure for legal arguments about evidence using Bayesian networks. Cognitive Science, 37(1), 61102.CrossRefGoogle ScholarPubMed
Fenton, N., Neil, M., Lagnado, D., Marsh, W., Yet, B., & Constantinou, A. (2016). How to model mutually exclusive events based on independent causal pathways in Bayesian network models. Knowledge-based Systems, 113, 3950.CrossRefGoogle Scholar
Fenton, N., Neil, M., Yet, B., & Lagnado, D. A. (2020). Analyzing the Simonshaven case using Bayesian networks. Topics in Cognitive Science, 12(4), 10921114.Google Scholar
Fenton, N. E., & Lagnado, D. A. (2021). Bayesianism: Objections and rebuttals. In Tuzet, G., Dahlman, C., & Stein, A. (Eds.), Philosophical foundations of evidence law. Oxford University Press.Google Scholar
Fenton, N. E., Neil, M., Osman, M., & McLachlan, S. (2020). COVID-19 infection and death rates: The need to incorporate causal explanations for the data and avoid bias in testing. Journal of Risk Research, 23(7–8), 862865.Google Scholar
Fiedler, K. (2000). Beware of samples! A cognitive-ecological sampling approach to judgment biases. Psychology Review, 107(4), 659676.Google Scholar
Fiedler, K., Brinkmann, B., Betsch, T., & Wild, B. (2020). A sampling approach to biases in conditional probability judgments: Beyond base rate neglect and statistical format. Journal of Experimental Psychology: General, 129(3), 399.CrossRefGoogle Scholar
Fiedler, K., & Juslin, P. (2006). Taking the interface between mind and environment seriously. In Fiedler, K. & Juslin, P. (Eds.), Information sampling and adaptive cognition (pp. 329). Cambridge: Cambridge University Press.Google Scholar
Fiedler, K., Walther, E., Freytag, P., & Plessner, H. (2002). Judgment biases in a simulated classroom – A cognitive-environmental approach. Organizational Behavior and Human Decision Processes, 88(1), 527561.Google Scholar
Fischhoff, B., Slovic, P., & Lichtenstein, S. (2013). Fault trees. Judgment and Decision Making, 124, 330–344.Google Scholar
Flavell, J. H. (1979). Metacognition and cognitive monitoring: A new area of cognitive–developmental inquiry. American Psychologist, 34(10), 906.Google Scholar
Forster, E. M. (1927/1955). Aspects of the novel. New York: Harcourt.Google Scholar
Friedman, R. D. (1987). Route analysis of credibility and hearsay. Yale Law Journal, 96(4), 1.Google Scholar
Garrett, B. (2011). Convicting the innocent. Cambridge, MA: Harvard University Press.Google Scholar
Gentner, D., & Stevens, A. L. (Eds.). (1983). Mental models. Hillsdale, NJ: Lawrence Erlbaum.Google Scholar
Gerstenberg, T., Goodman, N. D., Lagnado, D. A., & Tenenbaum, J. B. (2021). A counterfactual simulation model of causal judgments for physical events. Psychological Review. https://doi.org/10.1037/rev0000281Google Scholar
Gerstenberg, T., & Tenenbaum, J. B. (2017). Intuitive theories. In Waldmann, M. R. (Ed.), Oxford library of psychology. The Oxford handbook of causal reasoning (pp. 515547). New York: Oxford University Press.Google Scholar
Gettys, C. F., III Kelly, C., & Peterson, C. R. (1973). The best guess hypothesis in multistage inference. Organizational Behavior and Human Performance, 10(3), 364373.Google Scholar
Gigerenzer, G., & Todd, P. (1999). Simple heuristics that make us smart. New York: Oxford University Press.Google Scholar
Gill, R. D., Fenton, N., Neil, M., & Lagnado, D. A. (2020). Statistical issues in Serial Killer Nurse cases [Unpublished manuscript].Google Scholar
Gillies, D., & Gillies, D. A. (2000). Philosophical theories of probability. London: Psychology Press.Google Scholar
Glymour, C. (2001). The mind’s arrows: Bayes nets and graphical causal models in psychology. Cambridge, MA: MIT Press.Google Scholar
Glymour, C. (2003). Learning, prediction and causal Bayes nets. Trends in Cognitive Sciences, 7(1), 4348.Google Scholar
Goodman, N. D., Ullman, T. D., & Tenenbaum, J. B. (2011). Learning a theory of causality. Psychological Review, 118(1), 110.Google Scholar
Gopnik, A., Glymour, C., Sobel, D. M., Schulz, L. E., Kushnir, T., & Danks, D. (2004). A theory of causal learning in children: Causal maps and Bayes nets. Psychological Review, 111(1), 332.Google Scholar
Gopnik, A., & Schulz, L. (Eds.). (2007). Causal learning: Psychology, philosophy, and computation. New York: Oxford University Press.CrossRefGoogle Scholar
Gopnik, A., & Wellman, H. M. (2012). Reconstructing constructivism: Causal models, Bayesian learning mechanisms, and the theory theory. Psychological Bulletin, 138(6), 1085.CrossRefGoogle ScholarPubMed
Gorman, R., Charney, E., Holtzman, N., & Roberts, K. (1985). A successful city-wide smoke detector giveaway program. Pediatrics, 75(1), 1418.Google Scholar
Griffith, G. J., Morris, T. T., Tudball, M. J., Herbert, A., Mancano, G., Pike, L., … Hermani, G. (2020). Collider bias undermines our understanding of COVID-19 disease risk and severity. Nature Communications, 11(1), 112.CrossRefGoogle ScholarPubMed
Griffiths, T. L. (2020). Understanding human intelligence through human limitations. Trends in Cognitive Sciences, 24(11), 873883.Google Scholar
Griffiths, T. L., Lieder, F., & Goodman, N. D. (2015). Rational use of cognitive resources: Levels of analysis between the computational and the algorithmic. Topics in Cognitive Science, 7(2), 217229.Google Scholar
Griffiths, T. L., & Tenenbaum, J. B. (2009). Theory-based causal induction. Psychological Review, 116(4), 661716.Google Scholar
Hacking, I. (1975). The emergence of probability. New York: Cambridge University Press.Google Scholar
Hahn, U. (2020). Argument quality in real world argumentation. Trends in Cognitive Sciences, 24(5), 363374.Google Scholar
Hahn, U., & Harris, A. J. (2014). What does it mean to be biased: Motivated reasoning and rationality. In Psychology of learning and motivation (Vol. 61, pp. 41102). New York: Academic Press.Google Scholar
Halpern, J. (2016). Actual Causality. Cambridge, MA: MIT Press.Google Scholar
Halpern, J. Y., & Pearl, J. (2005). Causes and explanations: A structural-model approach. Part I: Causes. The British Journal for the Philosophy of Science, 56(4), 843887.Google Scholar
Hanson, N. R. (1958). Patterns of discovery: An inquiry into the conceptual foundations of science. Cambridge, UK: Cambridge University Press.Google Scholar
Harvey, N. (2020). Behavioral fatigue: Real phenomenon, naïve construct, or policy contrivance? Frontiers in Psychology, 11, 589892.Google Scholar
Hayes, B. K., Hawkins, G. E., & Newell, B. R. (2016). Consider the alternative: The effects of causal knowledge on representing and using alternative hypotheses in judgments under uncertainty. Journal of Experimental Psychology: Learning, Memory, and Cognition, 42(5), 723.Google Scholar
Hayes, B. K., Hawkins, G. E., Newell, B. R., Pasqualino, M., & Rehder, B. (2014). The role of causal models in multiple judgments under uncertainty. Cognition, 133(3), 611620.Google Scholar
Hayes, B. K., Ngo, J., Hawkins, G. E., & Newell, B. R. (2018). Causal explanation improves judgment under uncertainty, but rarely in a Bayesian way. Memory & Cognition, 46(1), 112131.Google Scholar
Hegarty, M. (2004). Mechanical reasoning by mental simulation. Trends in Cognitive Sciences, 8(6), 280285.Google Scholar
Heider, F. (1958). The psychology of interpersonal relations. Hoboken, NJ: Wiley.Google Scholar
Heller, K. J. (2006). The cognitive psychology of circumstantial evidence. Michigan Law Review, 105, 241.Google Scholar
Hempel, C. G. (1965). Aspects of scientific explanation. New York: Free Press.Google Scholar
Hepler, A. B., Dawid, A. P., & Leucari, V. (2007). Object-oriented graphical representations of complex patterns of evidence. Law, Probability and Risk, 6(1–4), 275293.Google Scholar
Herring, J. (2014). Criminal law: Text, cases, and materials. New York: Oxford University Press.Google Scholar
Hogarth, R. M., & Einhorn, H. J. (1992). Order effects in belief updating: The belief-adjustment model. Cognitive Psychology, 24(1), 155.CrossRefGoogle Scholar
Hogarth, R. M., Lejarraga, T., & Soyer, E. (2015). The two settings of kind and wicked learning environments. Current Directions in Psychological Science, 24(5), 379385.CrossRefGoogle Scholar
Hogarth, R. M., & Soyer, E. (2011). Sequentially simulated outcomes: Kind experience versus nontransparent description. Journal of Experimental Psychology: General, 140(3), 434.CrossRefGoogle ScholarPubMed
Holyoak, K. J., & Simon, D. (1999). Bidirectional reasoning in decision making by constraint satisfaction. Journal of Experimental Psychology: General, 128(1), 3.Google Scholar
Horst, S. (2016). Cognitive pluralism. Cambridge, MA: MIT Press.Google Scholar
Howson, C., & Urbach, P. (2006). Scientific reasoning: The Bayesian approach. Chicago, IL: Open Court Publishing.Google Scholar
Icard, T. (2016). Subjective probability as sampling propensity. Review of Philosophy and Psychology, 7, 863903.Google Scholar
Innes, M. (2003). Investigating murder: Detective work and the police response to criminal homicide. Clarendon Studies in Criminology. Oxford: Oxford University Press.Google Scholar
Innes, M. (2007). Investigation order and major crime inquiries. In T. Newburn, T. Williamson, & A. Wright (Eds.), Handbook of Criminal Investigation (pp. 255–276). London: Taylor & Francis.Google Scholar
Johnson, S. G., Merchant, T., & Keil, F. C. (2020). Belief digitization: Do we treat uncertainty as probabilities or as bits? Journal of Experimental Psychology: General, 149(8), 14171434.Google Scholar
Johnson-Laird, P. N. (1983). Mental models: Towards a cognitive science of language, inference, and consciousness. Cambridge, MA: Harvard University Press.Google Scholar
Johnson-Laird, P. N. (2006). How we reason. New York: Oxford University Press.Google Scholar
Johnson-Laird, P. N. (2010). Mental models and human reasoning. Proceedings of the National Academy of Sciences, 107(43), 1824318250.Google Scholar
Kadane, J. B., & Schum, D. A. (2011). A probabilistic analysis of the Sacco and Vanzetti evidence (Vol. 773). Hoboken, NJ: Wiley.Google Scholar
Kahneman, D. (2011). Thinking, fast and slow. New York: Farrar, Straus and Giroux.Google Scholar
Kahneman, D., & Lovallo, D. (1993). Timid choices and bold forecasts: A cognitive perspective on risk taking. Management Science, 39(1), 1731.Google Scholar
Kahneman, D., & Tversky, A. (1982a). The simulation heuristic. In Kahneman, D., Slovic, P., & Tversky, A. (Eds.), Judgment under uncertainty: Heuristics and biases (pp. 201208). New York: Cambridge University Press.Google Scholar
Kahneman, D., & Tversky, A. (1982b). Variants of uncertainty. Cognition, 11(2), 143157.Google Scholar
Kassin, S., Dror, I., & Kukucka, J. (2013). The forensic confirmation bias: Problems, perspectives, and proposed solutions. Journal of Applied Research in Memory and Cognition, 2(1), 4252.Google Scholar
Keil, F. C. (2003). Folk science: Coarse interpretations of a complex reality. Trends in Cognitive Sciences, 7, 368373.Google Scholar
Keil, F. C. (2006). Explanation and understanding. Annual Review of Psychology, 57, 227254.CrossRefGoogle ScholarPubMed
Klayman, J. (1995). Varieties of confirmation bias. In Busemeyer, J., Hastie, R., & Medin, D. L. (Eds.), Decision making from a cognitive perspective (pp. 365418). New York: Academic Press.Google Scholar
Klayman, J., & Ha, Y. W. (1987). Confirmation, disconfirmation, and information in hypothesis testing. Psychological Review, 94(2), 211228.Google Scholar
Klein, G. A. (1999). Applied decision making. In Hancock, P. A. (Ed.), Handbook of perception and cognition series. Human performance and ergonomics (2nd ed., pp. 87107). New York: Academic Press.Google Scholar
Klein, G. (2008). Naturalistic decision making. Human Factors, 50(3), 456460.Google Scholar
Klein, G. A. (2017). Sources of power: How people make decisions (Anniversary ed.). Cambridge, MA: MIT Press.Google Scholar
Klein, G., Moon, B., & Hoffman, R. R. (2006). Making sense of sensemaking 2: A macrocognitive model. IEEE Intelligent Systems, 21(5), 8892.Google Scholar
Klein, G., Phillips, J. K., Rall, E. L., & Peluso, D. A. (2007). A data-frame theory of sensemaking. In Hoffman, R. R. (Ed.), Expertise out of context: Proceedings of the Sixth International Conference on Naturalistic Decision Making (pp. 113155). Hillsdale, NJ: Lawrence Erlbaum.Google Scholar
Koehler, J. J. (2011). If the shoe fits they might acquit: The value of forensic science testimony. Journal of Empirical Legal Studies, 8, 2148.Google Scholar
Koehler, J. J. (2016). Communicating probabilistic forensic evidence in court. In Jamieson, A. & Bader, S. (Eds.), A guide to forensic DNA profiling. Hoboken, NJ: Wiley.Google Scholar
Koehler, J. J., Chia, A., & Lindsey, S. (1995). The random match probability (RMP) in DNA evidence: Irrelevant and prejudicial? Jurimetrics, 35, 201219.Google Scholar
Koslowski, B. (1996). Theory and evidence: The development of scientific reasoning. Cambridge, MA: MIT Press.Google Scholar
Krynski, T. R., & Tenenbaum, J. B. (2007). The role of causality in judgment under uncertainty. Journal of Experimental Psychology: General, 136(3), 430450.Google Scholar
Kuhn, D. (1989). Children and adults as intuitive scientists. Psychological Review, 96(4), 674.Google Scholar
Kuhn, D. (1991). The skills of argument. Cambridge: Cambridge University Press.Google Scholar
Kuhn, D. (2000). Metacognitive development. Current Directions in Psychological Science, 9, 178181.Google Scholar
Kuhn, D. (2001). How do people know?. Psychological Science, 12, 18.Google Scholar
Kuhn, D. (2008). Education for thinking. Cambridge, MA: Harvard University Press.Google Scholar
Kuhn, D. (2012). The development of causal reasoning. Wiley Interdisciplinary Reviews: Cognitive Science, 3. doi:10.1002/wcs.1160Google Scholar
Kuhn, D. (2017). Building our best future: Thinking critically about ourselves and our world. Blacksburg, VA: Wessex.Google Scholar
Kuhn, D., Weinstock, M., & Flaton, R. (1994). How well do jurors reason? Competence dimensions of individual variation in a juror reasoning task. Psychological Science, 5, 289296.Google Scholar
Lagnado, D. A., Fenton, N., & Neil, M. (2013). Legal idioms: A framework for evidential reasoning. Argument & Computation, 4(1), 4663.Google Scholar
Lagnado, D. A., & Gerstenberg, T. (2017). Causation in legal and moral reasoning. In Waldmann, M. R. (Ed.), Oxford library of psychology. The Oxford handbook of causal reasoning (pp. 565601). New York: Oxford University Press.Google Scholar
Lagnado, D. A., Gerstenberg, T., & Zultan, R. (2013). Causal responsibility and counterfactuals. Cognitive Science, 37(6), 10361073.Google Scholar
Lagnado, D. A., Waldmann, M. R., Hagmayer, Y., & Sloman, S. A. (2007). Beyond covariation: Cues to causal structure. In Gopnik, A. & Schulz, L. (Eds.), Causal learning: Psychology, philosophy, and computation (pp. 154172). New York: Oxford University Press.CrossRefGoogle Scholar
Laird, J. E. (2012). The Soar cognitive architecture. Cambridge, MA: MIT Press.Google Scholar
Lakatos, I., Worrall, J., & Zahar, E. (Eds.). (1976). Proofs and refutations: The logic of mathematical discovery. Cambridge: Cambridge University Press.Google Scholar
Lake, B., Ullman, T., Tenenbaum, J., & Gershman, S. (2017). Building machines that learn and think like people. Behavioral and Brain Sciences, 40, E253.Google Scholar
Laplace, P. S. (1812/1951). Philosophical essay on probability. New York: Dover.Google Scholar
Leone, C., Kleinberg, S., & Lagnado, D. (2021). Mitigating collider bias in the evaluation of causal claims. [unpublished manuscript].Google Scholar
Lichtenstein, S., Slovic, P., Fischhoff, B., Layman, M., & Combs, B. (1978). Judged frequency of lethal events. Journal of Experimental Psychology: Human Learning and Memory, 4(6), 551.Google Scholar
Lieder, F., & Griffiths, T. L. (2020) Resource-rational analysis: Understanding human cognition as the optimal use of limited computational resources. Behavioral and Brain Sciences, 43(e1), 160.Google Scholar
Lieder, F., Griffiths, T. L., & Hsu, M. (2018). Overrepresentation of extreme events in decision making reflects rational use of cognitive resources. Psychological Review, 125(1), 1.Google Scholar
Liefgreen, A., Pilditch, T., & Lagnado, D. (2020). Strategies for selecting and evaluating information. Cognitive Psychology, 123, 101332.Google Scholar
Liefgreen, A., Yousif, S. R., Keil, F. C., & Lagnado, D. A. (2020). I don’t know if you did it, but I know why: A ‘motive’ preference at multiple stages of the legal–investigative process. In Denison, S., Mack, M., Yu, Y., & Armstrong, B. C. (Eds.), Proceedings of the 42nd Annual Conference of the Cognitive Science Society (pp. 11231129). Austin, TX: Cognitive Science Society.Google Scholar
Liefgreen, A. and Lagnado, D. (2021). The role of causal models in evaluating simple and complex legal explanations. In Proceedings of the 43rd Annual Meeting of the Cognitive Science Society. Austin, TX: Cognitive Science Society.Google Scholar
Lipton, P. (2004). Inference to the best explanation. London: Taylor & Francis.Google Scholar
Lombrozo, T. (2012). Explanation and abductive inference. In Holyoak, K. J. & Morrison, R. G. (Eds.), Oxford library of psychology. The Oxford handbook of thinking and reasoning (pp. 260276). New York: Oxford University Press.Google Scholar
Lynch, M., & McNally, R. (2003). ‘Science’, ‘common sense’, and DNA evidence: A legal controversy about the public understanding of science. Public Understanding of Science, 12(1), 83103.Google Scholar
Mandel, D. R., & Navarrete, G. (2015). Improving Bayesian reasoning: What works and why? Frontiers in Psychology, 6, 1872.CrossRefGoogle ScholarPubMed
Marcus, G., & Davis, E. (2019). Rebooting AI: Building artificial intelligence we can trust. New York: Vintage.Google Scholar
Martin, G. A. (1967). Closing argument to the jury for the defense in criminal cases. Journal of Criminal Law, Criminology and Political Science, 58, 217.Google Scholar
Martire, K. A., Kemp, R. I., Watkins, I., Sayle, M. A., & Newell, B. R. (2013). The expression and interpretation of uncertain forensic science evidence: Verbal equivalence, evidence strength, and the weak evidence effect. Law and Human Behavior, 37(3), 197207.Google Scholar
McCoy, M. L., Nunez, N., & Dammeyer, M. M. (1999). The effect of jury deliberations on jurors’ reasoning skills. Law and Human Behavior, 23(5), 557575.Google Scholar
McGrayne, S. B. (2011). The theory that would not die: How Bayes’ rule cracked the enigma code, hunted down Russian submarines, and emerged triumphant from two centuries of controversy. New Haven, CT: Yale University Press.Google Scholar
McKenzie, C. R. (2004). Hypothesis testing and evaluation. In Koehler, D. J. & Harvey, N. (Eds.), Blackwell handbook of judgment and decision making (pp. 200219). Hoboken, NJ: Wiley-Blackwell.Google Scholar
McKenzie, C. R. (2006). Increased sensitivity to differentially diagnostic answers using familiar materials: Implications for confirmation bias. Memory & Cognition, 34(3), 577588.Google Scholar
McNair, S., & Feeney, A. (2015). Whose statistical reasoning is facilitated by a causal structure intervention? Psychonomic Bulletin & Review, 22(1), 258264.Google Scholar
Mercier, H., & Sperber, D. (2011). Why do humans reason? Arguments for an argumentative theory. The Behavioral and Brain Sciences, 34, 5774.Google Scholar
Mercier, H., & Sperber, D. (2017). The enigma of reason. Cambridge, MA: Harvard University Press.Google Scholar
Mierley, M. C., & Baker, S. P. (1983). Fatal house fires in an urban population. Journal of the American Medical Association, 249(11), 14661468.Google Scholar
Mill, J. S., (1869). On liberty. London: Longman, Roberts & Green.Google Scholar
Miyara, M., Tubach, F., Pourcher, V., Morelot-Panzini, C., Pernet, J., & Harochei, J. (2020). Low rate of daily active tobacco smoking in patients with symptomatic COVID-19. Oeios. doi:10.32388/WPP19W.3Google Scholar
Mocke, P., Pilditch, T., & Lagnado, D. (2020). How to catch a liar: A Bayesian approach to laypeople’s reasoning about deception [Unpublished manuscript].Google Scholar
Morgan, R. M. (2017). Conceptualising forensic science and forensic reconstruction. Part I: A conceptual model. Science and Justice, 57(6), 455459.Google Scholar
Morris, M. W., & Larrick, R. P. (1995). When one cause casts doubt on another: A normative analysis of discounting in causal attribution. Psychological Review, 102(2), 331.Google Scholar
Mosteller, R. P. (2015). Pernicious inferences: Double counting and perception and evaluation biases in criminal cases. Howard Law Journal, 58, 365396.Google Scholar
Murrie, D. C., Gardner, B. O., Kelley, S., & Dror, I. E. (2019). Perceptions and estimates of error rates in forensic science: A survey of forensic analysts. Forensic Science International, 302, 109887.Google Scholar
Neil, M., Fenton, N., Lagnado, D., & Gill, R. (2019). Modelling competing legal arguments using Bayesian model comparison and averaging. Artificial Intelligence and Law, 27. doi:10.1007/s10506–019-09250-3Google Scholar
Neisser, U. (1976). Cognition and reality: Principles and implications of cognitive psychology. New York: W. H. Freeman/Times Books/Henry Holt.Google Scholar
Nelson, J. D. (2005). Finding useful questions: On Bayesian diagnosticity, probability, impact, and information gain. Psychological Review, 112(4), 979999.Google Scholar
Nickerson, R. S. (1998). Confirmation bias: A ubiquitous phenomenon in many guises. Review of General Psychology, 2(2), 175220.Google Scholar
Nisbett, R. E., & Ross, L. (1980). Human inference: Strategies and shortcomings of social judgment. Upper Saddle River, NJ: Prentice-Hall.Google Scholar
Oaksford, M., & Chater, N. (2007). Bayesian rationality: The probabilistic approach to human reasoning. New York: Oxford University Press.Google Scholar
OIG. (2006). A review of the FBI’s handling of the Brandon Mayfield case. Office of the Inspector General, Oversight & Review Division, US Department of Justice.Google Scholar
Oldroyd, D. R. (1986). The arch of knowledge: An introductory study of the history of the philosophy and methodology of science. London: Methuen.Google Scholar
Operskalski, J. T., & Barbey, A. K. (2016). Risk literacy in medical decision-making. Science, 352(6284), 413414.Google Scholar
Ormerod, T. C., Barrett, E., & Taylor, P. J. (2008). Investigative sense-making in criminal contexts. In Schraagen, J. M. C. (Ed.), Proceedings of the Seventh International NDM Conference, Amsterdam, the Netherlands, June 2005 (pp. 81–102).Google Scholar
Osman, M. (2011). Controlling uncertainty: Decision making and learning in complex worlds. Hoboken, NJ: Wiley.Google Scholar
Palmer, A. (2011). Why and how to teach proof. Sydney Law Review, 33, 563.Google Scholar
Pearl, J. (1988). Probabilistic reasoning in intelligent systems: Networks of plausible inference. San Francisco, CA: Morgan-Kaufmann.Google Scholar
Pearl, J. (2009). Causality: Models, reasoning, and inference (2nd ed.). New York: Cambridge University Press.Google Scholar
Pearl, J. (2011). The algorithmization of counterfactuals. Annals of Mathematics and Artificial Intelligence, 61(1), 2939.CrossRefGoogle Scholar
Pearl, J. (2018). Theoretical impediments to machine learning with seven sparks from the causal revolution [Keynote speech]. WSDM, Feb. 5–9, 2018, Marina Del Ray, CA. arXiv:1801.04016.Google Scholar
Pearl, J., Glymour, M., & Jewell, N. P. (2016). Causal inference in statistics: A primer. Chichester: Wiley.Google Scholar
Peirce, C. S. (1931). Collected papers. Cambridge, MA: Harvard University Press.Google Scholar
Pennington, N., & Hastie, R. (1986). Evidence evaluation in complex decision making. Journal of Personality and Social Psychology, 51(2), 242258.Google Scholar
Pennington, N., & Hastie, R. (1988). Explanation-based decision making: Effects of memory structure on judgment. Journal of Experimental Psychology: Learning, Memory, and Cognition, 14(3), 521533.Google Scholar
Pennington, N., & Hastie, R. (1992). Explaining the evidence: Tests of the Story Model for juror decision making. Journal of Personality and Social Psychology, 62(2), 189206.Google Scholar
Perfect, T. J., & Schwartz, B. L. (Eds.). (2002). Applied metacognition. Cambridge, UK: Cambridge University Press.Google Scholar
Pilditch, T. D., Fenton, N., & Lagnado, D. (2019). The zero-sum fallacy in evidence evaluation. Psychological Science, 30, 250260.Google Scholar
Pilditch, T. D., Fries, A., & Lagnado, D. (2019). Deception in evidential reasoning: Wilful deceit or honest mistake? In Goel, A., Seifert, C., & Freska, C., (Eds.), Proceedings of the 41st Annual Conference of the Cognitive Science Society (pp. 931937). Austin, TX: Cognitive Science Society.Google Scholar
Pilditch, T. D., Hahn, U., Fenton, N., & Lagnado, D. (2020). Dependencies in evidential reports: The case for informational advantages. Cognition, 204, 104343.Google Scholar
Pilditch, T. D., Lagator, S., & Lagnado, D. (2021). Strange but true: Corroboration and base rate neglect. Journal of Experimental Psychology: Learning, Memory, and Cognition, 47(1), 1128.Google Scholar
Pilditch, T. D., Liefgreen, A., & Lagnado, D. A. (2019). Zero-sum reasoning in information selection. In Goel, A., Seifert, C., & Freska, C., (Eds.), Proceedings of the 41st Annual Conference of the Cognitive Science Society (pp. 938943). Austin, TX: Cognitive Science Society.Google Scholar
Poe, E. A. (1841/2012). ‘The Murders in the Rue Morgue’ and other tales. London: Penguin Classics.Google Scholar
Poletiek, F. H. (2001). Essays in cognitive psychology. Hypothesis-testing behaviour. London: Psychology Press.Google Scholar
Popper, K. R. (1959). The logic of scientific discovery. New York: Basic Books.Google Scholar
Radvansky, G. A., & Zacks, J. M. (2014). Event cognition. New York: Oxford University Press.Google Scholar
Redmayne, M. (2015) Character in the criminal trial. Oxford: Oxford University Press.Google Scholar
Rehder, B. (2017). Concepts as causal models: Induction. In Waldmann, M. R. (Ed.), Oxford library of psychology. The Oxford handbook of causal reasoning (pp. 377413). New York: Oxford University Press.Google Scholar
Rehder, B., & Waldmann, M. R. (2017). Failures of explaining away and screening off in described versus experienced causal learning scenarios. Memory & Cognition, 45(2), 245260.Google Scholar
Richens, J. G., Lee, C. M., & Johri, S. (2020). Improving the accuracy of medical diagnosis with causal machine learning. Nature Communications, 11(1), 19.Google ScholarPubMed
Roberts, P., & Zuckerman, A. (2010). Criminal evidence. New York: Oxford University Press.Google Scholar
Robertson, P., & Aitken, C. (2014). The logic of forensic proof: Inferential reasoning in criminal evidence and forensic science. (Communicating and Interpreting Statistical Evidence in the Administration of Criminal Justice.) Guidance for Judges, Lawyers, Forensic Scientists and Expert Witnesses, Practitioner Guide. Royal Statistical Society. https://rss.org.uk/news-publications/our-research/Google Scholar
Roese, N. J., & Vohs, K. D. (2012). Hindsight bias. Perspectives on Psychological Science, 7(5), 411426.Google Scholar
Rogers, T. T., & McClelland, J. L. (2004). Semantic cognition: A parallel distributed processing approach. Cambridge, MA: MIT Press.Google Scholar
Rossmo, D. K. (2008). Criminal investigative failures. Boca Raton, FL: CRC Press.Google Scholar
Rossmo, K., & Pollock, J. (2019). Confirmation bias and other systemic causes of wrongful convictions: A sentinel events perspective. Northeastern University Law Review, 11(2), 790835.Google Scholar
Rottman, B. M., & Hastie, R. (2014). Reasoning about causal relationships: Inferences on causal networks. Psychological Bulletin, 140(1), 109139.Google Scholar
Rottman, B. M., & Hastie, R. (2016). Do people reason rationally about causally related events? Markov violations, weak inferences, and failures of explaining away. Cognitive Psychology, 87, 88134.Google Scholar
Royce, C. S., Hayes, M. M., & Schwartzstein, R. M. (2019). Teaching critical thinking: A case for instruction in cognitive biases to reduce diagnostic errors and improve patient safety. Academic Medicine, 94(2), 187194.Google Scholar
Rozenblit, L., & Keil, F. (2002). The misunderstood limits of folk science: An illusion of explanatory depth. Cognitive Science, 26(5), 521562.Google Scholar
Rule, J. S., Tenenbaum, J. B., & Piantadosi, S. T. (2020). The child as hacker. Trends in Cognitive Sciences, 24(11), 900915.Google Scholar
Rumelhart, D. E. (1975). Notes on a schema for stories. In Bobrow, D. G. & Collins, A. (Eds.), Representation and understanding (pp. 211236). New York: Academic Press.Google Scholar
Rusconi, P., & Mckenzie, C. (2013). Insensitivity and oversensitivity to answer diagnosticity in hypothesis testing. Quarterly Journal of Experimental Psychology, 66(12), 24432464.Google Scholar
Saks, M. J., & Koehler, J. J. (2005). The coming paradigm shift in forensic identification science. Sciences, 309(5736), 892895.Google Scholar
Sanborn, A. N., & Chater, N. (2016). Bayesian brains without probabilities. Trends in Cognitive Sciences, 20(12), 883893.Google Scholar
Schank, R. C., & Abelson, R. P. (1977). Scripts, plans, goals, and understanding: An inquiry into human knowledge structures. Mahwah, NJ: Lawrence Erlbaum.Google Scholar
Scherr, K. C., Redlich, A. D., & Kassin, S. M. (2020). Cumulative disadvantage: A psychological framework for understanding how innocence can lead to confession, wrongful conviction, and beyond. Perspectives on Psychological Science, 15(2), 353383.Google Scholar
Schofield, D. (2016). The use of computer generated imagery in legal proceedings. Digital Evidence & Electronic Signature Law Review, 13, 3.Google Scholar
Schum, D. A. (2001). The evidential foundations of probabilistic reasoning. Evanston, IL: Northwestern University Press.Google Scholar
Schum, D. A. (2009). A science of evidence: Contributions from law and probability. Law, Probability and Risk, 8(3), 197231.Google Scholar
Searle, J. R., & Willis, S. (1983). Intentionality: An essay in the philosophy of mind. Cambridge University Press.Google Scholar
Semmler, C., Dunn, J., Mickes, L., & Wixted, J. T. (2018). The role of estimator variables in eyewitness identification. Journal of Experimental Psychology: Applied, 24(3), 400.Google Scholar
Shaler, R. C. (2011). Crime scene forensics: A scientific method approach. London: Taylor & Francis.Google Scholar
Shengelia, T., & Lagnado, D. (2020). Are jurors intuitive statisticians? Bayesian causal reasoning in legal contexts. Frontiers in Psychology, 11, 5519262.Google Scholar
Shepard, R. N. (1978). The mental image. American Psychologist, 33(2), 125.Google Scholar
Simon, D. (2012). In doubt: The psychology of the criminal justice process. Cambridge, MA: Harvard University Press.Google Scholar
Simon, D., Snow, C. J., & Read, S. J. (2004). The redux of cognitive consistency theories: Evidence judgments by constraint satisfaction. Journal of Personality and Social Psychology, 86(6), 814837.Google Scholar
Simon, H. A. (1956). Rational choice and the structure of the environment. Psychological Review, 63(2), 129138.Google Scholar
Skov, R. B., & Sherman, S. J. (1986). Information-gathering processes: Diagnosticity, hypothesis-confirmatory strategies, and perceived hypothesis confirmation. Journal of Experimental Social Psychology, 22(2), 93121.Google Scholar
Sloman, S. (2005). Causal models: How people think about the world and its alternatives. New York: Oxford University Press.Google Scholar
Sloman, S., & Lagnado, D. (2015). Causality in thought. Annual Review of Psychology, 66, 223247.Google Scholar
Sloman, S. A., & Fernbach, P. M. (2018). The knowledge illusion: Why we never think alone. New York: Riverhead.Google Scholar
Smit, N. M., Lagnado, D. A., Morgan, R. M., & Fenton, N. E. (2016). Using Bayesian networks to guide the assessment of new evidence in an appeal case. Crime Science, 5(1), 112.Google Scholar
Smit, N. M., Morgan, R. M., & Lagnado, D. (2018). A systematic analysis of misleading evidence in unsafe rulings in England and Wales. Science & Justice, 58(2), 128137.Google Scholar
Sodhi, M., & Etminan, M. (2020). Safety of ibuprofen in patients with COVID-19: Causal or confounded?. Chest, 158(1), 5556.Google Scholar
Stapleton, J. (2008). Choosing what we mean by causation in the law. Missouri Law Review, 73, 433.Google Scholar
Stephen, J. F. (1876). A digest of the law of evidence (12th ed.). London: Macmillan.Google Scholar
Stephen, J. F. (1948). A digest of the law of evidence (1st ed.). London: Macmillan.Google Scholar
Sterman, J. D. (1989). Modeling managerial behavior: Misperceptions of feedback in a dynamic decision making experiment. Management Science, 35(3), 321339.Google Scholar
Sterman, J. D. (2010). Business dynamics. New York: Irwin/McGraw-Hill.Google Scholar
Stone, J. V. (2013). Bayes’ rule: A tutorial introduction to Bayesian analysis. Sebtel Press.Google Scholar
Strevens, M. (2008). Depth: An account of scientific explanation. Cambridge, MA: Harvard University Press.Google Scholar
Stuhlmüller, A., & Goodman, N. D. (2014). Reasoning about reasoning by nested conditioning: Modeling theory of mind with probabilistic programs. Cognitive Systems Research, 28, 8099.Google Scholar
Taroni, F., Biedermann, A., Bozza, S., Garbolino, P., & Aitken, C. (2014). Bayesian networks for probabilistic inference and decision analysis in forensic science. Hoboken, NJ: Wiley.Google Scholar
Tenenbaum, J. B., Griffiths, T. L., & Niyogi, S. (2007). Intuitive theories as grammars for causal inference. In Gopnik, A. & Schulz, L. (Eds.), Causal learning: Psychology, philosophy, and computation (pp. 301322). New York: Oxford University Press.CrossRefGoogle Scholar
Tenenbaum, J. B., Kemp, C., Griffiths, T. L., & Goodman, N. D. (2011). How to grow a mind: Statistics, structure, and abstraction. Science, 331(6022), 12791285.Google Scholar
Tentori, K., Crupi, V., & Russo, S. (2013). On the determinants of the conjunction fallacy: Probability versus inductive confirmation. Journal of Experimental Psychology: General, 42(1), 235.Google Scholar
Tetlock, P. E. (2002). Social functionalist frameworks for judgment and choice: Intuitive politicians, theologians, and prosecutors. Psychological Review, 109(3), 451.Google Scholar
Tetlock, P. E., & Gardner, D. (2016). Superforecasting: The art and science of prediction. New York: Random House.Google Scholar
Thomas, N. J. T., (2020). Mental imagery. In Zalta, E. N. (Ed.), The Stanford encyclopedia of philosophy (Fall 2020 edition). https://plato.stanford.edu/archives/fall2020/entries/mental-imagery/Google Scholar
Thompson, W. C. (2011). What role should investigative facts play in the evaluation of scientific evidence?. Australian Journal of Forensic Sciences, 43(2–3), 123134.Google Scholar
Trabasso, T., & Sperry, L. L. (1985). Causal relatedness and importance of story events. Journal of Memory and Language, 24(5), 595611.Google Scholar
Tversky, A., & Kahneman, D. (1973). Availability: A heuristic for judging frequency and probability. Cognitive Psychology, 5(2), 207232.Google Scholar
Tversky, A., & Kahneman, D. (1981). The framing of decisions and the psychology of choice. Science, 21(1), 453–58.Google Scholar
Tversky, A., & Kahneman, D. (1982). Causal schemas in judgments under uncertainty. In Kahneman, D., Slovic, P., & Tversky, A. (Eds.), Judgment under uncertainty: Heuristics and biases (pp. 117128). New York: Oxford University Press.Google Scholar
Tversky, A., & Kahneman, D. (1983). Extensional versus intuitive reasoning: The conjunction fallacy in probability judgment. Psychological Review, 90(4), 293315.Google Scholar
Twining, W. (1985). Theories of evidence: Bentham and Wigmore. London: Weidenfeld & Nicolson.Google Scholar
Ullman, T. D., Spelke, E., Battaglia, P., Tenenbaum, J. B. (2017). Mind games: Game engines as an architecture for intuitive physics. Trends in Cognitive Sciences, 21(9), 649–665.Google Scholar
van Koppen, P. J., & Mackor, A. R. (2020). A scenario approach to the Simonshaven case. Topics in Cognitive Science, 12(4), 11321151.Google Scholar
Vul, E., Goodman, N., Griffiths, T. L., Tenenbaum, J. B. (2014). One and done? Optimal decisions from very few samples. Cognitive Science , 38(2014), 599637.Google Scholar
Waldmann, M. R. (1996). Knowledge-based causal induction. Psychology of Learning and Motivation, 34, 4788.Google Scholar
Waldmann, M. R. (Ed.). (2017). Oxford library of psychology. The Oxford handbook of causal reasoning. New York: Oxford University Press.Google Scholar
Waskin, M. (1985). Mrs O’Leary’s comet: Cosmic causes of the great Chicago fire. Chicago, IL: Academy Chicago Publishers.Google Scholar
Wason, P. C. (1960). On the failure to eliminate hypotheses in a conceptual task. Quarterly Journal of Experimental Psychology, 12: 129140.Google Scholar
Weick, K. (1995). Sensemaking in organisations. London: SAGE.Google Scholar
Weinstock, M. (1999). Epistemological understanding and argumentive competence as foundations of juror reasoning skill [Unpublished doctoral dissertation]. Teachers College, Columbia University.Google Scholar
Weinstock, M., & Cronin, M. A. (2003). The everyday production of knowledge: Individual differences in epistemological understanding and juror-reasoning skill. Applied Cognitive Psychology, 17(2), 161181.Google Scholar
Wells, G. L. (1992). Naked statistical evidence of liability: Is subjective probability enough? Journal of Personality and Social Psychology, 62(5), 739752.Google Scholar
Wells, G. L., & Gavanski, I. (1989). Mental simulation of causality. Journal of Personality and Social Psychology, 56(2), 161169.Google Scholar
Wells, G. L., & Olson, E. A. (2003). Eyewitness testimony. Annual Review of Psychology, 54(1), 277295.Google Scholar
Wigmore, J. H. (1913). The problem of proof. Illinois Law Review, 8(2), 77103.Google Scholar
Wigmore, J. H. (1937). The science of proof: As given by logic, psychology and general experience and illustrated judicial trials (3rd ed.). Boston, MA: Little, Brown.Google Scholar
Williamson, E. J., Walker, A. J., Bhaskaran, K., Bacon, S., Bates, C., Morton, C. E., … Goldacre, B. (2020). Factors associated with COVID-19-related death using OpenSAFELY. Nature, 584(7821), 430436.Google Scholar
Woodward, J. (2003). Making things happen: A theory of causal explanation. New York: Oxford University Press.Google Scholar
Wortley, R., & Sidebottom, A. (2017). Deterrence and rational choice theory. In The Encyclopedia of Juvenile Delinquency and Justice (pp. 1–6). Wiley Online Library. https://doi.org/10.1002/9781118524275.ejdj0131Google Scholar
Wykes, A. (1964). The complete illustrated guide to gambling. London: Aldus Books.Google Scholar
Yaniv, I., & Foster, D. P. (1995). Graininess of judgment under uncertainty: An accuracy-informativeness trade-off. Journal of Experimental Psychology: General, 124(4), 424432.Google Scholar
Yardley, E., & Wilson, D. (2016). In search of the ‘angels of death’: conceptualising the contemporary nurse healthcare serial killer. Journal of Investigative Psychology and Offender Profiling, 13(1), 3955.Google Scholar
Zsambok, C. E., & Klein, G. (Eds.). (2014). Naturalistic decision making. London: Psychology Press.Google Scholar
Zwaan, R. A. (1999). Situation models: The mental leap into imagined worlds. Current Directions in Psychological Science, 8(1), 1518.Google Scholar
Zwaan, R. A., & Radvansky, G. A. (1998). Situation models in language comprehension and memory. Psychological Bulletin, 123(2), 162185.Google Scholar

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  • References
  • David A. Lagnado, University College London
  • Book: Explaining the Evidence
  • Online publication: 20 October 2021
  • Chapter DOI: https://doi.org/10.1017/9780511794520.013
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  • References
  • David A. Lagnado, University College London
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  • Book: Explaining the Evidence
  • Online publication: 20 October 2021
  • Chapter DOI: https://doi.org/10.1017/9780511794520.013
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