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  1. The hierarchical abuse of power in work organizations.Donald Vredenburgh & Yael Brender - 1998 - Journal of Business Ethics 17 (12):1337-1347.
    Although much theoretical and empirical research has examined organizational power, virtually none has addressed the hierarchical abuse of power in organizations. Managers' incentives and discretion and subordinates' dependencies define the abuse of power as an important organizational issue. This paper offers a conceptualization and process model to help further theoretical and applied understanding, and it considers the ethical nature of power abuse. Two dimensions, disrespect for individual dignity and interference with job performance or deserved rewards, conceptualize the interpersonal abuse of (...)
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  • The link between brain learning, attention, and consciousness.Stephen Grossberg - 1999 - Consciousness and Cognition 8 (1):1-44.
    The processes whereby our brains continue to learn about a changing world in a stable fashion throughout life are proposed to lead to conscious experiences. These processes include the learning of top-down expectations, the matching of these expectations against bottom-up data, the focusing of attention upon the expected clusters of information, and the development of resonant states between bottom-up and top-down processes as they reach an attentive consensus between what is expected and what is there in the outside world. It (...)
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  • The dynamical hypothesis in cognitive science.Tim van Gelder - 1998 - Behavioral and Brain Sciences 21 (5):615-28.
    According to the dominant computational approach in cognitive science, cognitive agents are digital computers; according to the alternative approach, they are dynamical systems. This target article attempts to articulate and support the dynamical hypothesis. The dynamical hypothesis has two major components: the nature hypothesis (cognitive agents are dynamical systems) and the knowledge hypothesis (cognitive agents can be understood dynamically). A wide range of objections to this hypothesis can be rebutted. The conclusion is that cognitive systems may well be dynamical systems, (...)
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  • The Dynamics of Neural Populations Capture the Laws of the Mind.Gregor Schöner - 2020 - Topics in Cognitive Science 12 (4):1257-1271.
    The dynamics of neural populations capture the laws of the mindThis paper focuses on the level of neural networks. Examining the case of recurrent neural networks, the paper argues that the dynamics of neural populations form a privileged level of explanation in cognitive science. According to Schöner, this level is privileged, because it enables cognitive scientists to discover the laws governing organisms’ cognition and behaviour.
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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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  • Neural dynamics of autistic behaviors: Cognitive, emotional, and timing substrates.Stephen Grossberg & Don Seidman - 2006 - Psychological Review 113 (3):483-525.
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  • Multialternative decision field theory: A dynamic connectionst model of decision making.Robert M. Roe, Jermone R. Busemeyer & James T. Townsend - 2001 - Psychological Review 108 (2):370-392.
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  • Contrast Effects or Loss Aversion? Comment on Usher and McClelland (2004).Jerome R. Busemeyer, James T. Townsend, Adele Diederich & Rachel Barkan - 2005 - Psychological Review 112 (1):253-255.
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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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  • Contiguity, contingency, adaptiveness, and controls.Glenda MacQueen, James MacRae & Shepard Siegel - 1989 - Behavioral and Brain Sciences 12 (1):154-155.
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  • Extending the “new hegemony” of classical conditioning.Dan Lloyd - 1989 - Behavioral and Brain Sciences 12 (1):152-153.
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  • The dark side of hegemony.Charles Locurto - 1989 - Behavioral and Brain Sciences 12 (1):153-154.
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  • Pavlovian conditioning: Providing a bridge between cognition and biology.Marvin D. Krank - 1989 - Behavioral and Brain Sciences 12 (1):151-151.
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  • Classical conditioning beyond the laboratory.Hugh Lacey - 1989 - Behavioral and Brain Sciences 12 (1):152-152.
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  • A promising new strategy for studying conditioned Immunomodulation.Wolfgang Klosterhalfen - 1989 - Behavioral and Brain Sciences 12 (1):150-150.
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  • Beyond respondent conditioning.Sibylle Klosterhalfen & Wolfgang Klosterhalfen - 1989 - Behavioral and Brain Sciences 12 (1):149-150.
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  • Complexity at the organismic and neuronal levels.R. W. Kentridge - 1989 - Behavioral and Brain Sciences 12 (1):147-148.
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  • The importance of classical conditioning.H. D. Kimmel - 1989 - Behavioral and Brain Sciences 12 (1):148-149.
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  • What is classical conditioning?W. J. Jacobs - 1989 - Behavioral and Brain Sciences 12 (1):146-146.
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  • Associative theory versus classical conditioning: Their proper relationship.E. James Kehoe - 1989 - Behavioral and Brain Sciences 12 (1):147-147.
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  • Classical conditioning: The role of interdisciplinary theory.Stephen Grossberg - 1989 - Behavioral and Brain Sciences 12 (1):144-145.
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  • Preparatory response hypotheses: A muddle of causal and functional analyses.Karen L. Hollis - 1989 - Behavioral and Brain Sciences 12 (1):145-146.
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  • Beyond Pavlovian classical conditioning.Beatrix T. Gardner & R. Allen Gardner - 1989 - Behavioral and Brain Sciences 12 (1):143-144.
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