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  1. The Development of Spatial–Temporal, Probability, and Covariation Information to Infer Continuous Causal Processes.Selma Dündar-Coecke, Andrew Tolmie & Anne Schlottmann - 2021 - Frontiers in Psychology 12.
    This paper considers how 5- to 11-year-olds’ verbal reasoning about the causality underlying extended, dynamic natural processes links to various facets of their statistical thinking. Such continuous processes typically do not provide perceptually distinct causes and effect, and previous work suggests that spatial–temporal analysis, the ability to analyze spatial configurations that change over time, is a crucial predictor of reasoning about causal mechanism in such situations. Work in the Humean tradition to causality has long emphasized on the importance of statistical (...)
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  • Developing a Learning Progression for Probability Based on the GDINA Model in China.Shengnan Bai - 2020 - Frontiers in Psychology 11.
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  • The quest for plausibility: A negative heuristic for science?R. W. Byrne - 1991 - Behavioral and Brain Sciences 14 (2):217-218.
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  • Intuitive statistical inferences in chimpanzees and humans follow Weber’s law.Johanna Eckert, Josep Call, Jonas Hermes, Esther Herrmann & Hannes Rakoczy - 2018 - Cognition 180 (C):99-107.
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  • Executive function in learning mathematics by comparison: incorporating everyday classrooms into the science of learning.Kreshnik Nasi Begolli, Lindsey Engle Richland, Susanne M. Jaeggi, Emily McLaughlin Lyons, Ellen C. Klostermann & Bryan J. Matlen - 2018 - Thinking and Reasoning 24 (2):280-313.
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  • Children’s Neglect of Probabilities in Decision Making with and without Feedback.Anna Lang & Tilmann Betsch - 2018 - Frontiers in Psychology 9.
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  • Children’s quantitative Bayesian inferences from natural frequencies and number of chances.Stefania Pighin, Vittorio Girotto & Katya Tentori - 2017 - Cognition 168 (C):164-175.
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  • The Folk Psychology of Free Will: Fits and Starts.Shaun Nichols - 2004 - Mind and Language 19 (5):473-502.
    According to agent‐causal accounts of free will, agents have the capacity to cause actions, and for a given action, an agent could have done otherwise. This paper uses existing results and presents experimental evidence to argue that young children deploy a notion of agent‐causation. If young children do have such a notion, however, it remains quite unclear how they acquire it. Several possible acquisition stories are canvassed, including the possibility that the notion of agent‐causation develops from a prior notion of (...)
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  • The Physicalization of Mathematics.Peter Milne - 1994 - British Journal for the Philosophy of Science 45 (1):305-340.
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  • Making sense of randomness: Implicit encoding as a basis for judgment.Ruma Falk & Clifford Konold - 1997 - Psychological Review 104 (2):301-318.
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  • How to improve Bayesian reasoning without instruction: Frequency formats.Gerd Gigerenzer & Ulrich Hoffrage - 1995 - Psychological Review 102 (4):684-704.
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  • The Invisible Hand: Toddlers Connect Probabilistic Events With Agentive Causes.Yang Wu, Paul Muentener & Laura E. Schulz - 2016 - Cognitive Science 40 (8):1854-1876.
    Children posit unobserved causes when events appear to occur spontaneously. What about when events appear to occur probabilistically? Here toddlers saw arbitrary causal relationships in a fixed, alternating order. The relationships were then changed in one of two ways. In the Deterministic condition, the event order changed ; in the Probabilistic condition, the causal relationships changed. As intended, toddlers looked equally long at both changes. We then introduced a previously unseen candidate cause. Toddlers looked longer at the appearance of a (...)
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  • Objectivity, Simulation and the Unity of Consciousness: Current Issues in the Philosophy of Mind.Christopher Peacocke - 1995 - Philosophy 70 (273):469-472.
    Notes on Contributors • Preface • Christopher Peacocke, Introduction: The Issues and their Further Development I OBJECTIVE THOUGHT • John Campbell, Objects and Objectivity Commentaries • Bill Brewer, Thoughts about Objects, Places and Times • John O'Keefe, Cognitive Maps, Time and Causality II OBJECTIVITY AND THE UNITY OF CONSCIOUSNESS • Susan Hurley, Unity and Objectivity Commentaries • Anthony Marcel, What is Relevant to the Unity of Consciousness? • Michael Lockwood, Issues of Unity and Objectivity III UNDERSTANDING THE MENTAL:THEORY OR SIMULATION (...)
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  • Toma de decisiones en la adolescencia: Entre la razón y la emoción.Ciencia Cognitiva - forthcoming - Ciencia Cognitiva.
    Yunier Broche-Pérez y Denisse Cruz-López Universidad Central “Marta Abreu” de Las Villas, Villa Clara, Cuba Hospital … Read More →.
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  • Decision making: Nonrational theories.Gerd Gigerenzer - 2001 - In Neil J. Smelser & Paul B. Baltes (eds.), International Encyclopedia of the Social and Behavioral Sciences. Elsevier. pp. 5--3304.
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  • Comparative metaphysics: the development of representing natural and normative regularities in human and non-human primates.Hannes Rakoczy - 2015 - Phenomenology and the Cognitive Sciences 14 (4):683-697.
    How do human children come up to carve up and think of the world around them in its most general and abstract structure? And to which degree are these general forms of viewing the world shared by other animals, notably by non-human primates? In response to these questions of what could be called comparative metaphysics, this paper discusses new evidence from developmental and comparative research to argue for the following picture: human children and non-human primates share a basic framework of (...)
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  • Teaching Bayesian reasoning in less than two hours.Peter Sedlmeier & Gerd Gigerenzer - 2001 - Journal of Experimental Psychology: General 130 (3):380.
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  • The origins of probabilistic inference in human infants.Stephanie Denison & Fei Xu - 2014 - Cognition 130 (3):335-347.
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  • Apes are intuitive statisticians.Hannes Rakoczy, Annette Clüver, Liane Saucke, Nicole Stoffregen, Alice Gräbener, Judith Migura & Josep Call - 2014 - Cognition 131 (1):60-68.
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  • Children can solve Bayesian problems: the role of representation in mental computation.Liqi Zhu & Gerd Gigerenzer - 2006 - Cognition 98 (3):287-308.
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  • The strategy of optimality revisited.Paul J. H. Schoemaker - 1991 - Behavioral and Brain Sciences 14 (2):237-245.
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  • Is economics still immersed in the old concepts of the Enlightenment era?Andrzej P. Wierzbicki - 1991 - Behavioral and Brain Sciences 14 (2):236-237.
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  • Optimal confusion.Stephanie Stolarz-Fantino & Edmund Fantino - 1991 - Behavioral and Brain Sciences 14 (2):234-234.
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  • The human being as a bumbling optimalist: A psychologist's viewpoint.Masanao Toda - 1991 - Behavioral and Brain Sciences 14 (2):235-235.
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  • Avoid the push-pull dilemma in explanation.Kenneth M. Steele - 1991 - Behavioral and Brain Sciences 14 (2):233-234.
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  • Rational agents, real people and the quest for optimality.Eldar Shafir - 1991 - Behavioral and Brain Sciences 14 (2):232-232.
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  • Extremum descriptions, process laws and minimality heuristics.Elliott Sober - 1991 - Behavioral and Brain Sciences 14 (2):232-233.
    The examples and concepts that Shoemaker cites are rather heterogeneous. Some distinctions need to be drawn. An optimality thesis involves not just an ordering of options, but a value judgment about them. So let us begin by distinguishing minimality from optimality. And the concept of minimality can play a variety of roles, among which I distinguish between extremum descriptions, statements hypothesizing an optimizing process, and methodological recommendations. Finally, I consider how the three categories relate to Shoemaker’s question that “Who is (...)
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  • Should the quest for optimality worry us?Nils-Eric Sahlin - 1991 - Behavioral and Brain Sciences 14 (2):231-231.
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  • Don't just sit there, optimise something.J. H. P. Paelinck - 1991 - Behavioral and Brain Sciences 14 (2):230-230.
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  • Optimality as a prescriptive tool.Alexander H. G. Rinnooy Kan - 1991 - Behavioral and Brain Sciences 14 (2):230-231.
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  • Complexity and optimality.Dauglas A. Miller & Steven W. Zucker - 1991 - Behavioral and Brain Sciences 14 (2):227-228.
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  • Two dynamic criteria for validating claims of optimality.Geoffrey F. Miller - 1991 - Behavioral and Brain Sciences 14 (2):228-229.
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  • The infinite regress of optimization.Philippe Mongin - 1991 - Behavioral and Brain Sciences 14 (2):229-230.
    A comment on Paul Schoemaker's target article in Behavioral and Brain Sciences, 14 (1991), p. 205-215, "The Quest for Optimality: A Positive Heuristic of Science?" (https://doi.org/10.1017/S0140525X00066140). This comment argues that the optimizing model of decision leads to an infinite regress, once internal costs of decision (i.e., information and computation costs) are duly taken into account.
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  • The example of psychology: Optimism, not optimality.Daniel S. Levine - 1991 - Behavioral and Brain Sciences 14 (2):225-226.
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  • Straining the word “optimal”.James E. Mazur - 1991 - Behavioral and Brain Sciences 14 (2):227-227.
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  • Natural science, social science and optimality.Oleg Larichev - 1991 - Behavioral and Brain Sciences 14 (2):224-225.
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  • Why optimality is not worth arguing about.Stephen E. G. Lea - 1991 - Behavioral and Brain Sciences 14 (2):225-225.
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  • Optimality and constraint.David A. Helweg & Herbert L. Roitblat - 1991 - Behavioral and Brain Sciences 14 (2):222-223.
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  • Types of optimality: Who is the steersman?Michael E. Hyland - 1991 - Behavioral and Brain Sciences 14 (2):223-224.
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  • Natural selection doesn't have goals, but it's the reason organisms do.Martin Daly - 1991 - Behavioral and Brain Sciences 14 (2):219-220.
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  • Organisms, scientists and optimality.Michael Davison - 1991 - Behavioral and Brain Sciences 14 (2):220-221.
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  • Vaulting optimality.Peter Dayan & Jon Oberlander - 1991 - Behavioral and Brain Sciences 14 (2):221-222.
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  • Criteria for optimality.Michel Cabanac - 1991 - Behavioral and Brain Sciences 14 (2):218-218.
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  • Some optimality principles in evolution.James F. Crow - 1991 - Behavioral and Brain Sciences 14 (2):218-219.
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  • Optimality as a mathematical rhetoric for zeroes.Fred L. Bookstein - 1991 - Behavioral and Brain Sciences 14 (2):216-217.
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  • Optimality as an evaluative standard in the study of decision-making.Jonathan Baron - 1991 - Behavioral and Brain Sciences 14 (2):216-216.
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  • Optimality and human memory.John R. Anderson - 1991 - Behavioral and Brain Sciences 14 (2):215-216.
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  • The quest for optimality: A positive heuristic of science?Paul J. H. Schoemaker - 1991 - Behavioral and Brain Sciences 14 (2):205-215.
    This paper examines the strengths and weaknesses of one of science's most pervasive and flexible metaprinciples;optimalityis used to explain utility maximization in economics, least effort principles in physics, entropy in chemistry, and survival of the fittest in biology. Fermat's principle of least time involves both teleological and causal considerations, two distinct modes of explanation resting on poorly understood psychological primitives. The rationality heuristic in economics provides an example from social science of the potential biases arising from the extreme flexibility of (...)
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  • Children's causal inferences from indirect evidence: Backwards blocking and Bayesian reasoning in preschoolers.D. Sobel - 2004 - Cognitive Science 28 (3):303-333.
    Previous research suggests that children can infer causal relations from patterns of events. However, what appear to be cases of causal inference may simply reduce to children recognizing relevant associations among events, and responding based on those associations. To examine this claim, in Experiments 1 and 2, children were introduced to a “blicket detector,” a machine that lit up and played music when certain objects were placed upon it. Children observed patterns of contingency between objects and the machine's activation that (...)
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  • The Case for Rules in Reasoning.Edward E. Smith, Christopher Langston & Richard E. Nisbett - 1992 - Cognitive Science 16 (1):1-40.
    A number of theoretical positions in psychology—including variants of case‐based reasoning, instance‐based analogy, and connectionist models—maintain that abstract rules are not involved in human reasoning, or at best play a minor role. Other views hold that the use of abstract rules is a core aspect of human reasoning. We propose eight criteria for determining whether or not people use abstract rules in reasoning, and examine evidence relevant to each criterion for several rule systems. We argue that there is substantial evidence (...)
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