Normativity, interpretation, and Bayesian models

It has been suggested that evaluative normativity should be expunged from the psychology of reasoning. A broadly Davidsonian response to these arguments is presented. It is suggested that two distinctions, between different types of rationality, are more permeable than this argument requires and that the fundamental objection is to selecting theories that make the most rational sense of the data. It is argued that this is inevitable consequence of radical interpretation where understanding others requires assuming they share our own norms of reasoning. This requires evaluative normativity and it is shown that when asked to evaluate others’ arguments participants conform to rational Bayesian norms. It is suggested that logic and probability are not in competition and that the variety of norms is more limited than the arguments against evaluative normativity suppose. Moreover, the universality of belief ascription suggests that many of our norms are universal and hence evaluative. It is concluded that the union of evaluative normativity and descriptive psychology implicit in Davidson and apparent in the psychology of reasoning is a good thing.

[1]  Nick Chater,et al.  Cognition and Conditionals: Probability and Logic in Human Thinking , 2010 .

[2]  Susan Vineberg Dutch Book Arguments , 2016 .

[3]  Nick Chater,et al.  Normative Systems: Logic, Probability, and Rational Choice , 2012 .

[4]  L. J. Savage,et al.  The Foundations of Statistics , 1955 .

[5]  Ch. Perelman,et al.  The New Rhetoric: A Treatise on Argumentation , 1971 .

[6]  Branden Fitelson,et al.  Probability, confirmation, and the conjunction fallacy , 2008 .

[7]  Angelo Gilio,et al.  The psychology of inferring conditionals from disjunctions: A probabilistic study , 2012 .

[8]  M. Oaksford,et al.  A Bayesian approach to the argument from ignorance. , 2004, Canadian journal of experimental psychology = Revue canadienne de psychologie experimentale.

[9]  N. Chater,et al.  Précis of Bayesian Rationality: The Probabilistic Approach to Human Reasoning , 2009, Behavioral and Brain Sciences.

[10]  Ulrike Hahn,et al.  Why Are We Convinced by the Ad Hominem Argument?: Bayesian Source Reliability and Pragma-Dialectical Discussion Rules , 2013 .

[11]  D. Davidson Problems Of Rationality , 2004 .

[12]  Nick Chater,et al.  A rational analysis of the selection task as optimal data selection. , 1994 .

[13]  Scott Atran,et al.  Reframing Sacred Values , 2008 .

[14]  G. Kleiter,et al.  Mental probability logic , 2009, Behavioral and Brain Sciences.

[15]  Michael Rescorla,et al.  Rationality as a Constitutive Ideal , 2013 .

[16]  Itamar Pitowsky,et al.  Betting on the Outcomes of Measurements:A Bayesian Theory of Quantum Probability , 2003 .

[17]  K. Stanovich Normative models in psychology are here to stay , 2011, Behavioral and Brain Sciences.

[18]  John R. Anderson The Adaptive Character of Thought , 1990 .

[19]  J. Dessalles,et al.  Arguing, reasoning, and the interpersonal (cultural) functions of human consciousness , 2011, Behavioral and Brain Sciences.

[20]  W. J. Studden,et al.  Theory Of Optimal Experiments , 1972 .

[21]  John Woods,et al.  Argument: Critical Thinking, Logic and the Fallacies , 2002 .

[22]  Nick Chater,et al.  A Rational Analysis of the Selection Task II: Abstract Materials , 1998 .

[23]  Donald Davidson,et al.  On the Very Idea of a Conceptual Scheme , 1973 .

[24]  N. Chater,et al.  RATIONAL EXPLANATION OF THE SELECTION TASK , 1996 .

[25]  Jonathan Evans,et al.  Norms for reasoning about decisions , 2011, Behavioral and Brain Sciences.

[26]  I. Pitowsky,et al.  Betting on the Outcomes of Measurements: A Bayesian Theory of Quantum Probability , 2002, quant-ph/0208121.

[27]  Nick Chater,et al.  Dynamic inference and everyday conditional reasoning in the new paradigm , 2013 .

[28]  Jerome R Busemeyer,et al.  Can quantum probability provide a new direction for cognitive modeling? , 2013, The Behavioral and brain sciences.

[29]  M. Oaksford,et al.  The rationality of informal argumentation: a Bayesian approach to reasoning fallacies. , 2007, Psychological review.

[30]  Niki Pfeifer,et al.  The conditional in mental probability logic , 2010 .

[31]  N. Chater,et al.  An introduction to rational models of cognition , 1998 .

[32]  D. Davidson Truth, language and history , 2005 .

[33]  Philip M. Fernbach,et al.  A quantitative causal model theory of conditional reasoning. , 2013, Journal of experimental psychology. Learning, memory, and cognition.

[34]  Jaines M. Joyce A Nonpragmatic Vindication of Probabilism , 1998, Philosophy of Science.

[35]  K. Holyoak,et al.  The Oxford handbook of thinking and reasoning , 2012 .

[36]  N. Chater,et al.  Rational models of cognition , 1998 .

[37]  M. Oaksford Quantum probability, intuition, and human rationality. , 2013, The Behavioral and brain sciences.

[38]  William Eckhardt,et al.  The Two-Envelopes Problem , 2013 .

[39]  Ulrike Hahn,et al.  A Bayesian Approach to Informal Argument Fallacies , 2006, Synthese.

[40]  U. Hahn The Bayesian boom: good thing or bad? , 2014, Front. Psychol..

[41]  B. Burns,et al.  The collider principle in causal reasoning: why the Monty Hall dilemma is so hard. , 2004, Journal of experimental psychology. General.

[42]  Adam J. L. Harris,et al.  Because Hitler did it! Quantitative tests of Bayesian argumentation using ad hominem , 2012 .