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  1. Perception and experience of altruism in graduate nursing students.Xinyu Gu, Yanxia Yang, Hao Gong & Luojing Zhou - 2023 - Nursing Ethics 30 (7-8):1125-1137.
    Background Altruism is the core of nursing professionalism. Graduate nursing education in China started late and is still developing, exploring the current state of altruistic behavior and the perceived experience of altruism among graduate nursing students may have important implications for nursing education. Objective Explore the current state of altruistic behavior and the perceived experience of altruism among graduate nursing students in China. Research design This is a descriptive phenomenological qualitative research study, semi-structured in-depth interviews were conducted. Seventeen graduate nursing (...)
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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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  • 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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  • 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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  • 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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  • Why optimality is not worth arguing about.Stephen E. G. Lea - 1991 - Behavioral and Brain Sciences 14 (2):225-225.
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  • Optimization of energy gain: Theory and practice.Klaas Westerterp - 1988 - Behavioral and Brain Sciences 11 (1):152-153.
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  • Evolution of a controller of state!Lloyd D. Partridge - 1988 - Behavioral and Brain Sciences 11 (1):142-143.
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  • Game theoretic models and respect for ownership.John Archer - 1986 - Behavioral and Brain Sciences 9 (4):740-741.
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  • Restoring emotion's bad rep: the moral randomness of norms.Ronald De Sousa - 2006 - European Journal of Analytic Philosophy 2 (1):29-47.
    Despite the fact that common sense taxes emotions with irrationality, philosophers have, by and large, celebrated their functionality. They are credited with motivating, steadying, shaping or harmonizing our dispositions to act, and with policing norms of social behaviour. It's time to restore emotion's bad rep. To this end, I shall argue that we should expect that some of the “norms” enforced by emotions will be unevenly distributed among the members of our species, and may be dysfunctional at the individual, social, (...)
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  • (1 other version)Does Meaning Evolve?Mark D. Roberts - 2004 - Behavior and Philosophy 32 (2):401 - 426.
    A common method of making a theory more understandable is to compare it to another theory that has been better developed. Radical interpretation is a theory that attempts to explain how communication has meaning. Radical interpretation is treated as another time-dependent theory and compared to the time-dependent theory of biological evolution. The main reason for doing this is to find the nature of the time dependence; producing analogs between the two theories is a necessary prerequisite to this and brings up (...)
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  • (1 other version)Does meaning evolove?Mark D. Roberts - forthcoming - Philosophical Explorations.
    A common method of improving how well understood a theory is, is by comparing it to another theory which has been better developed. Radical interpretation is a theory which attempts to explain how communication has meaning. Radical interpretation is treated as another time dependent theory and compared to the time dependent theory of biological evolution. Several similarities and differences are uncovered. Biological evolution can be gradual or punctuated. Whether radical interpretation is gradual or punctuated depends on how the question 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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  • Types of optimality: Who is the steersman?Michael E. Hyland - 1991 - Behavioral and Brain Sciences 14 (2):223-224.
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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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  • There's no such thing as a free lunch.Alasdair I. Houston & John M. McNamara - 1988 - Behavioral and Brain Sciences 11 (1):154-163.
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  • Biological relevance.Howard Rachlin - 1988 - Behavioral and Brain Sciences 11 (1):144-144.
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  • Adapting canonical costs and robust rules for imperfect decisions.Ronald A. Heiner - 1988 - Behavioral and Brain Sciences 11 (1):135-136.
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  • Policy-making for survival: Reading the rules and small print.C. J. Barnard - 1988 - Behavioral and Brain Sciences 11 (1):130-131.
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  • Reliability in signalling motivation.Amotz Zahavi - 1986 - Behavioral and Brain Sciences 9 (4):741-742.
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  • Swarm intelligence: when uncertainty meets conflict.Larissa Conradt, Christian List & Timothy J. Roper - 2013 - American Naturalist 182 (5):592-610.
    When animals share decisions with others, they pool personal information, offset individual errors and, thereby, increase decision accuracy. This is termed ‘swarm intelligence.’ But what if those decisions involve conflicts of interest between individual decision-makers? Should animals share decisions with individuals whose goals are different from, and partially in conflict with, their own? A group decision model developed by Larissa Conradt and colleagues finds that, contrary to intuition, conflicting goals often increase both decision accuracy and the individual gains derived from (...)
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  • Booknotes.R. M. - 1994 - Biology and Philosophy 9 (4):507-514.
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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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  • Organisms, scientists and optimality.Michael Davison - 1991 - Behavioral and Brain Sciences 14 (2):220-221.
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  • Houston & McNamara are right, but are they helpful to empiricists?Nils Chr Stenseth - 1988 - Behavioral and Brain Sciences 11 (1):150-151.
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  • Optimization theory: A too narrow path.Gene M. Heyman - 1988 - Behavioral and Brain Sciences 11 (1):136-137.
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  • Motivation, decision-making, and choice.Marian Stamp Dawkins - 1988 - Behavioral and Brain Sciences 11 (1):134-135.
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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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  • A framework for the functional analysis of behaviour.Alasdair I. Houston & John M. McNamara - 1988 - Behavioral and Brain Sciences 11 (1):117-130.
    We present a general framework for analyzing the contribution to reproductive success of a behavioural action. An action may make a direct contribution to reproductive success, but even in the absence of a direct contribution it may make an indirect contribution by changing the animal's state. We consider actions over a period of time, and define a reward function that characterizes the relationship between the animal's state at the end of the period and its future reproductive success. Working back from (...)
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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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  • Fitness, currencies, and models.Thomas Caraco - 1988 - Behavioral and Brain Sciences 11 (1):133-133.
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  • Skepticism about dynamic modeling: General problems and the special problems of learning.Sonja I. Yoerg - 1988 - Behavioral and Brain Sciences 11 (1):153-154.
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  • The God Allusion.Rafael Wlodarski & Eiluned Pearce - 2016 - Huamn Nature 27 (2):160-172.
    It has previously been suggested that the historically and geographically widespread persistence of religious beliefs occurs because it is a by-product of normal cognitive processes, ones which first evolved to confer survival advantages in the social domain. If this theory holds, then it is likely that inter-individual variation in the same biases may predict corresponding variation in religious thoughts and behaviors. Using an online questionnaire, 298 participants answered questions regarding their tendency to detect agency, the degree to which they displayed (...)
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  • Constructing optimal sequences of behavior: Backwards is beautiful, but….William Timberlake - 1988 - Behavioral and Brain Sciences 11 (1):151-152.
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  • Optimal confusion.Stephanie Stolarz-Fantino & Edmund Fantino - 1991 - Behavioral and Brain Sciences 14 (2):234-234.
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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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  • Realism, generality, or testability: The ecological modeler's dilemma.Eric Alden Smith - 1988 - Behavioral and Brain Sciences 11 (1):149-150.
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  • Ownership and honesty in competitive interaction.John Maynard Smith - 1986 - Behavioral and Brain Sciences 9 (4):742-744.
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  • On analyzing complex relationships between behaviour, state and fitness.Andrew Sih - 1988 - Behavioral and Brain Sciences 11 (1):148-149.
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  • Dynamic programming: From eternity to here.David F. Sherry - 1988 - Behavioral and Brain Sciences 11 (1):147-148.
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  • Adjoint optimal control.Robert E. Shaw & Thomas F. Carolan - 1988 - Behavioral and Brain Sciences 11 (1):146-147.
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  • Behavior, adaptedness, and Darwinian theories.Francesco M. Scudo - 1988 - Behavioral and Brain Sciences 11 (1):145-146.
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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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  • John Maynard Smith and the natural philosophy of␣adaptation.Alirio Rosales - 2005 - Biology and Philosophy 20 (5):1027-1040.
    One of the most remarkable aspects of John Maynard Smith’s work was the fact that he devoted time both to doing science and to reflecting philosophically upon its methods and concepts. In this paper I offer a philosophical analysis of Maynard Smith’s approach to modelling phenotypic evolution in relation to three main themes. The first concerns the type of scientific understanding that ESS and optimality models give us. The second concerns the causal–historical aspect of stability analyses of adaptation. The third (...)
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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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  • (1 other version)The Evolution of Cooperative Strategies for Asymmetric Social Interactions.Jörg Rieskamp & Peter M. Todd - 2006 - Theory and Decision 60 (1):69-111.
    How can cooperation be achieved between self-interested individuals in commonly-occurring asymmetric interactions where agents have different positions? Should agents use the same strategies that are appropriate for symmetric social situations? We explore these questions through the asymmetric interaction captured in the indefinitely repeated investment game (IG). In every period of this game, the first player decides how much of an endowment he wants to invest, then this amount is tripled and passed to the second player, who finally decides how much (...)
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  • Realistic versus minimal models.Alliston K. Reid - 1988 - Behavioral and Brain Sciences 11 (1):144-145.
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  • A nonfunctional analysis of behavior.William T. Powers - 1988 - Behavioral and Brain Sciences 11 (1):143-144.
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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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