642 research outputs found

    Epistemic Dependence and Collective Scientific Knowledge

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    I argue that scientific knowledge is collective knowledge, in a sense to be specified and defended. I first consider some existing proposals for construing collective knowledge and argue that they are unsatisfactory, at least for scientific knowledge as we encounter it in actual scientific practice. Then I introduce an alternative conception of collective knowledge, on which knowledge is collective if there is a strong form of mutual epistemic dependence among scientists, which makes it so that satisfaction of the justification condition on knowledge ineliminably requires a collective. Next, I show how features of contemporary science support the conclusion that scientific knowledge is collective knowledge in this sense. Finally, I consider implications of my proposal and defend it against objections. © 2013 Springer Science+Business Media Dordrecht

    The role of falsification in the development of cognitive architectures: insights from a Lakatosian analysis

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    It has been suggested that the enterprise of developing mechanistic theories of the human cognitive architecture is flawed because the theories produced are not directly falsifiable. Newell attempted to sidestep this criticism by arguing for a Lakatosian model of scientific progress in which cognitive architectures should be understood as theories that develop over time. However, Newell’s own candidate cognitive architecture adhered only loosely to Lakatosian principles. This paper reconsiders the role of falsification and the potential utility of Lakatosian principles in the development of cognitive architectures. It is argued that a lack of direct falsifiability need not undermine the scientific development of a cognitive architecture if broadly Lakatosian principles are adopted. Moreover, it is demonstrated that the Lakatosian concepts of positive and negative heuristics for theory development and of general heuristic power offer methods for guiding the development of an architecture and for evaluating the contribution and potential of an architecture’s research program

    What is the role of emotions in educational leaders’ decision making? Proposing an organizing framework

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    Purpose: Emotions have a pervasive, predictable, sometimes deleterious but other times instrumental effect on decision making. Yet the influence of emotions on educational leaders’ decision making has been largely underexplored. To optimize educational leaders’ decision making, this article builds on the prevailing data-driven decision-making approach, and proposes an organizing framework of educational leaders’ emotions in decision making by drawing on converging empirical evidence from multiple disciplines (e.g., administrative science, psychology, behavioral economics, cognitive neuroscience, and neuroeconomics) intersecting emotions, decision making, and organizational behavior. Proposed Framework: The proposed organizing framework of educational leaders’ emotions in decision making includes four core propositions: (1) decisions are the outcomes of the interactions between emotions and cognition; (2) at the moment of decision making, emotions have a pervasive, predictable impact on decision making; (3) before making decisions, leaders’ individual differences (e.g., trait affect and power) and organizational contexts (e.g., organizational justice and emotional contagion) have a bearing on leaders’ emotions and decision making; and (4) postdecision behavioral responses trigger more emotions (e.g., regret, guilt, and shame) which, in turn, influence the next cycle of decision-making process. Implications: The proposed framework calls for not only an intensified scholarly inquiry into educational leaders’ emotions and decision making but also an adequate training on emotions in school leadership preparation programs and professional development

    Herding QATs: Quality Assessment Tools for Evidence in Medicine

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    Medical scientists employ ‘quality assessment tools’ (QATs) to measure the quality of evidence from clinical studies, especially randomized controlled trials (RCTs). These tools are designed to take into account various methodological details of clinical studies, including randomization, blinding, and other features of studies deemed relevant to minimizing bias and error. There are now dozens available. The various QATs on offer differ widely from each other, and second-order empirical studies show that QATs have low inter-rater reliability and low inter-tool reliability. This is an instance of a more general problem I call the underdetermination of evidential significance. Disagreements about the strength of a particular piece of evidence can be due to different—but in principle equally good—weightings of the fine-grained methodological features which constitute QATs
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