Search results for 'robustness' (try it on Scholar)

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  1. Jacob Stegenga (2009). Robustness, Discordance, and Relevance. Philosophy of Science 76 (5):650-661.score: 24.0
    Robustness is a common platitude: hypotheses are better supported with evidence generated by multiple techniques that rely on different background assumptions. Robustness has been put to numerous epistemic tasks, including the demarcation of artifacts from real entities, countering the “experimenter’s regress,” and resolving evidential discordance. Despite the frequency of appeals to robustness, the notion itself has received scant critique. Arguments based on robustness can give incorrect conclusions. More worrying is that although robustness may be valuable (...)
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  2. Philippe Huneman (2010). Topological Explanations and Robustness in Biological Sciences. Synthese 177 (2):213-245.score: 24.0
    This paper argues that besides mechanistic explanations, there is a kind of explanation that relies upon “topological” properties of systems in order to derive the explanandum as a consequence, and which does not consider mechanisms or causal processes. I first investigate topological explanations in the case of ecological research on the stability of ecosystems. Then I contrast them with mechanistic explanations, thereby distinguishing the kind of realization they involve from the realization relations entailed by mechanistic explanations, and explain how both (...)
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  3. Robert Hudson (2009). The Methodological Strategy of Robustness in the Context of Experimental WIMP Research. Foundations of Physics 39 (2):174-193.score: 24.0
    According to the methodological principle called ‘robustness’, empirical evidence is more reliable when it is generated using multiple, independent (experimental) routes that converge on the same result. As it happens, robustness as a methodological strategy is quite popular amongst philosophers. However, despite its popularity, my goal here is to criticize the value of this principle on historical grounds. My historical reasons take into consideration some recent history of astroparticle physics concerning the search for WIMPs (weakly interacting massive particles), (...)
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  4. Patrick Grim, Randy Au, Nancy Louie, Robert Rosenberger, William Braynen, Evan Selinger & Robb E. Eason (2008). A Graphic Measure for Game-Theoretic Robustness. Synthese 163 (2):273 - 297.score: 24.0
    Robustness has long been recognized as an important parameter for evaluating game-theoretic results, but talk of ‘robustness’ generally remains vague. What we offer here is a graphic measure for a particular kind of robustness (‘matrix robustness’), using a three-dimensional display of the universe of 2 × 2 game theory. In such a measure specific games appear as specific volumes (Prisoner’s Dilemma, Stag Hunt, etc.), allowing a graphic image of the extent of particular game-theoretic effects in terms (...)
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  5. Jani Raerinne (2013). Robustness and Sensitivity of Biological Models. Philosophical Studies 166 (2):285-303.score: 24.0
    The aim of this paper is to develop ideas about robustness analyses. I introduce a form of robustness analysis that I call sufficient parameter robustness, which has been neglected in the literature. I claim that sufficient parameter robustness is different from derivational robustness, the focus of previous research. My purpose is not only to suggest a new taxonomy of robustness, but also to argue that previous authors have concentrated on a narrow sense of (...) analysis, which they have inadequately distinguished from other investigations of models such as sensitivity analysis. (shrink)
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  6. L. Star, E. D. Ellen, K. Uitdehaag & F. W. A. Brom (2008). A Plea to Implement Robustness Into a Breeding Goal: Poultry as an Example. [REVIEW] Journal of Agricultural and Environmental Ethics 21 (2):109-125.score: 24.0
    The combination of breeding for increased production and the intensification of housing conditions have resulted in increased occurrence of behavioral, physiological, and immunological disorders. These disorders affect health and welfare of production animals negatively. For future livestock systems, it is important to consider how to manage and breed production animals. In this paper, we will focus on selective breeding of laying hens. Selective breeding should not only be defined in terms of production, but should also include traits related to animal (...)
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  7. Elizabeth Irvine (forthcoming). Models, Robustness, and Non-Causal Explanation: A Foray Into Cognitive Science and Biology. Synthese:1-17.score: 22.0
    This paper is aimed at identifying how a model’s explanatory power is constructed and identified, particularly in the practice of template-based modeling (Humphreys, Philos Sci 69:1–11, 2002; Extending ourselves: computational science, empiricism, and scientific method, 2004), and what kinds of explanations models constructed in this way can provide. In particular, this paper offers an account of non-causal structural explanation that forms an alternative to causal–mechanical accounts of model explanation that are currently popular in philosophy of biology and cognitive science. Clearly, (...)
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  8. Ryan Muldoon & Michael Weisberg (2011). Robustness and Idealization in Models of Cognitive Labor. Synthese 183 (2):161-174.score: 21.0
  9. Christophe Abraham & Jean-Pierre Daures (2000). Global Robustness with Respect to the Loss Function and the Prior. Theory and Decision 48 (4):359-381.score: 21.0
    We propose a class [I,S] of loss functions for modeling the imprecise preferences of the decision maker in Bayesian Decision Theory. This class is built upon two extreme loss functions I and S which reflect the limited information about the loss function. We give an approximation of the set of Bayes actions for every loss function in [I,S] and every prior in a mixture class; if the decision space is a subset of R, we obtain the exact set.
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  10. Jian‐Wei Wang (2012). Universal Robustness of Scale‐Free Networks Against Cascading Edge Failures. Complexity 17 (6):17-23.score: 21.0
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  11. Kunihiko Kaneko (2011). Characterization of Stem Cells and Cancer Cells on the Basis of Gene Expression Profile Stability, Plasticity, and Robustness. Bioessays 33 (6):403-413.score: 21.0
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  12. Kurt A. Richardson (2010). Robustness in Complex Information Systems: The Role of Information “Barriers” in Boolean Networks. Complexity 15 (3):26-42.score: 21.0
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  13. Eyal Winter (1996). Mechanism Robustness in Multilateral Bargaining. Theory and Decision 40 (2):131-147.score: 21.0
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  14. Elisabeth A. Lloyd (2010). Confirmation and Robustness of Climate Models. Philosophy of Science 77 (5):971–984.score: 18.0
    Recent philosophical attention to climate models has highlighted their weaknesses and uncertainties. Here I address the ways that models gain support through observational data. I review examples of model fit, variety of evidence, and independent support for aspects of the models, contrasting my analysis with that of other philosophers. I also investigate model robustness, which often emerges when comparing climate models simulating the same time period or set of conditions. Starting from Michael Weisberg’s analysis of robustness, I conclude (...)
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  15. D. Corfield (2010). Understanding the Infinite I: Niceness, Robustness, and Realism. Philosophia Mathematica 18 (3):253-275.score: 18.0
    This paper treats the situation where a single mathematical construction satisfies a multitude of interesting mathematical properties. The examples treated are all infinitely large entities. The clustering of properties is termed ‘niceness’ by the mathematician Michiel Hazewinkel, a concept we compare to the ‘robustness’ described by the philosopher of science William Wimsatt. In the final part of the paper, we bring our findings to bear on the question of realism which concerns not whether mathematical entities exist as abstract objects, (...)
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  16. Brett Calcott (2011). Wimsatt and the Robustness Family: Review of Wimsatt's Re-Engineering Philosophy for Limited Beings. [REVIEW] Biology and Philosophy 26 (2):281-293.score: 18.0
    This review of Wimsatt’s book Re-engineering Philosophy for Limited Beings focuses on analysing his use of robustness, a central theme in the book. I outline a family of three distinct conceptions of robustness that appear in the book, and look at the different roles they play. I briefly examine what underwrites robustness, and suggest that further work is needed to clarify both the structure of robustness and the relation between it various conceptions.
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  17. Michael Weisberg (2006). Robustness Analysis. Philosophy of Science 73 (5):730-742.score: 18.0
    Modelers often rely on robustness analysis, the search for predictions common to several independent models. Robustness analysis has been characterized and championed by Richard Levins and William Wimsatt, who see it as central to modern theoretical practice. The practice has also been severely criticized by Steven Orzack and Elliott Sober, who claim that it a non-empirical form of confirmation, only effective under unusual circumstances. This paper addresses Orzack and Sober’s criticisms by giving a new account of robustness (...)
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  18. Jay Odenbaugh & Anna Alexandrova (2011). Buyer Beware: Robustness Analyses in Economics and Biology. Biology and Philosophy 26 (5):757-771.score: 18.0
    Theoretical biology and economics are remarkably similar in their reliance on mathematical models, which attempt to represent real world systems using many idealized assumptions. They are also similar in placing a great emphasis on derivational robustness of modeling results. Recently philosophers of biology and economics have argued that robustness analysis can be a method for confirmation of claims about causal mechanisms, despite the significant reliance of these models on patently false assumptions. We argue that the power of (...) analysis has been greatly exaggerated. It is best regarded as a method of discovery rather than confirmation. (shrink)
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  19. J. Kuorikoski, A. Lehtinen & C. Marchionni (2010). Economic Modelling as Robustness Analysis. British Journal for the Philosophy of Science 61 (3):541-567.score: 18.0
    We claim that the process of theoretical model refinement in economics is best characterised as robustness analysis: the systematic examination of the robustness of modelling results with respect to particular modelling assumptions. We argue that this practise has epistemic value by extending William Wimsatt's account of robustness analysis as triangulation via independent means of determination. For economists robustness analysis is a crucial methodological strategy because their models are often based on idealisations and abstractions, and it is (...)
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  20. Adina L. Roskies (2008). Robustness and the New Riddle Revived. Ratio 21 (2):218–230.score: 18.0
    The problem of induction is perennially important in epistemology and the philosophy of science. In response to Goodman's 'New Riddle of Induction', Frank Jackson made a compelling case for there being no new riddle, by arguing that there are no nonprojectible properties. Although Jackson's denial of nonprojectible properties is correct, I argue here that he is mistaken in thinking that he thereby shows that there is no new riddle of induction, and demonstrate that his solution to the grue paradox fails (...)
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  21. Jaakko Kuorikoski, Aki Lehtinen & Caterina Marchionni, Economics as Robustness Analysis.score: 18.0
    All economic models involve abstractions and idealisations. Economic theory itself does not tell which idealizations are truly fatal or harmful for the result and which are not. This is why much of what is seen as theoretical contribution in economics is constituted by deriving familiar results from different modelling assumptions. If a modelling result is robust with respect to particular modelling assumptions, the empirical falsity of these particular assumptions does not provide grounds for criticizing the result. In this paper we (...)
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  22. Kent W. Staley, Using Inferential Robustness to Establish the Security of an Evidence Claim.score: 18.0
    : Evidence claims depend on fallible assumptions. This paper discusses inferential robustness as a strategy for justifying evidence claims in spite of this fallibility. I argue that robustness can be understood as a means of establishing the partial security of evidence claims. An evidence claim is secure relative to an epistemic situation if it remains true in all scenarios that are epistemically possible relative to that epistemic situation.
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  23. Jim Woodward (2006). Some Varieties of Robustness. Journal of Economic Methodology 13 (2):219-240.score: 18.0
    It is widely believed that robustness (of inferences, measurements, models, phenomena and relationships discovered in empirical investigation etc.) is a Good Thing. However, there are many different notions of robustness. These often differ both in their normative credentials and in the conditions that warrant their deployment. Failure to distinguish among these notions can result in the uncritical transfer of considerations which support one notion to contexts in which another notion is being deployed. This paper surveys several different notions (...)
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  24. Tarja Knuuttila & Andrea Loettgers (2011). Causal Isolation Robustness Analysis: The Combinatorial Strategy of Circadian Clock Research. Biology and Philosophy 26 (5):773-791.score: 18.0
    This paper distinguishes between causal isolation robustness analysis and independent determination robustness analysis and suggests that the triangulation of the results of different epistemic means or activities serves different functions in them. Circadian clock research is presented as a case of causal isolation robustness analysis: in this field researchers made use of the notion of robustness to isolate the assumed mechanism behind the circadian rhythm. However, in contrast to the earlier philosophical case studies on causal isolation (...)
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  25. Klaus Nehring (2009). Coping Rationally with Ambiguity: Robustness Versus Ambiguity-Aversion. Economics and Philosophy 25 (3):303-334.score: 18.0
    Al-Najjar and Weinstein (2009) argue that the extant literature on ambiguity aversion is not successful in accounting for Ellsberg choices as rational responses to ambiguity. We concur, and propose that rational choice under ambiguity aims at robustness rather than avoidance of ambiguity. A central argument explains why robust choice is intrinsically context-dependent and legitimately violates standard choice consistency conditions. If choice consistency is forced, however, ambiguity-aversion emerges as a semi-rational response to ambiguity.
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  26. Francesco Guala & Luigi Mittone (2005). Experiments in Economics: External Validity and the Robustness of Phenomena. Journal of Economic Methodology 12 (4):495-515.score: 18.0
    External validity is the problem of generalizing results from laboratory to non?laboratory conditions. In this paper we review various ways in which the problem can be tackled, depending on the kind of experiment one is doing. Using a concrete example, we highlight in particular the distinction between external validity and robustness, and point out that many experiments are not aimed at a well?specified real?world target but rather contribute to a ?library of robust phenomena?, a body of experimental knowledge to (...)
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  27. James Logue (1997). Resiliency, Robustness and Rationality of Probability Judgements. International Studies in the Philosophy of Science 11 (1):21 – 34.score: 18.0
    This paper addresses and rejects claims that one can demonstrate experimentally that most untutored subjects are systematically and incurably irrational in their probability judgements and in some deductive reasoning tasks. From within a strongly subjectivist theory of probability, it develops the notions of resiliency —a measure of stability of judgements—and robustness —a measure of expected stability. It then becomes possible to understand subjects' behaviour in the Wason selection task, in examples which have been claimed to involve a 'base-rate fallacy', (...)
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  28. Sylvia Culp (1994). Defending Robustness: The Bacterial Mesosome as a Test Case. PSA: Proceedings of the Biennial Meeting of the Philosophy of Science Association 1994:46 - 57.score: 18.0
    Rasmussen (1993) argues that, because electron microscopists did not use robustness and would not have been warranted in using it as a criterion for the reality or the artifactuality of mesosomes, the bacterial mesosome serves as a test case for robustness that it fails. I respond by arguing that a more complete reading of the research literature on the mesosome shows that ultimately the more robust body of data did not support the mesosome and that electron microscopists used (...)
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  29. Jacques Demongeot, Adrien Elena & Sylvain Sené (forthcoming). Robustness in Regulatory Networks: A Multi-Disciplinary Approach. Acta Biotheoretica.score: 18.0
    We give in this paper indications about the dynamical impact (as phenotypic changes) coming from the main sources of perturbation in biological regulatory networks. First, we define the boundary of the interaction graph expressing the regulations between the main elements of the network (genes, proteins, metabolites, ...). Then, we search what changes in the state values on the boundary could cause some changes of states in the core of the system (robustness to boundary conditions). After, we analyse the role (...)
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  30. Richard A. Healey (1992). Causation, Robustness, and EPR. Philosophy of Science 59 (2):282-292.score: 18.0
    In his recent work, Michael Redhead (1986, 1987, 1989, 1990) has introduced a condition he calls robustness which, he argues, a relation must satisfy in order to be causal. He has used this condition to argue further that EPR-type correlations are neither the result of a direct causal connection between the correlated events, nor the result of a common cause associated with the source of the particle pairs which feature in these events. Andrew Elby (1992) has used this same (...)
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  31. Laura Martignon & Michael Schmitt (1999). Simplicity and Robustness of Fast and Frugal Heuristics. Minds and Machines 9 (4):565-593.score: 18.0
    Intractability and optimality are two sides of one coin: Optimal models are often intractable, that is, they tend to be excessively complex, or NP-hard. We explain the meaning of NP-hardness in detail and discuss how modem computer science circumvents intractability by introducing heuristics and shortcuts to optimality, often replacing optimality by means of sufficient sub-optimality. Since the principles of decision theory dictate balancing the cost of computation against gain in accuracy, statistical inference is currently being reshaped by a vigorous new (...)
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  32. Robert Hudson, Model-Independence Vs. Robustness.score: 18.0
    My goal in this paper is to consider two separate but connected topics, one historical, the other philosophical. The first topic concerns the forms of reasoning contemporary experimental astrophysicists use to investigate the existence of WIMPs (weakly interacting massive particles). These forms of reasoning take two forms, one model-dependent and the other model-independent, and we examine the arguments one WIMP research group (DAMA) uses to support the latter. The second topic concerns recent support Kent Staley has offered for a form (...)
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  33. J. D. Trout (1993). Robustness and Integrative Survival in Significance Testing: The World's Contribution to Rationality. British Journal for the Philosophy of Science 44 (1):1-15.score: 18.0
    Significance testing is the primary method for establishing causal relationships in psychology. Meehl [1978, 1990a, 1990b] and Faust [1984] argue that significance tests and their interpretation are subject to actuarial and psychological biases, making continued adherence to these practices irrational, and even partially responsible for the slow progress of the ‘soft’ areas of psychology. I contend that familiar standards of testing and literature review, along with recently developed meta-analytic techniques, are able to correct the proposed actuarial and psychological biases. In (...)
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  34. Zachary Ernst (2005). Robustness and Conceptual Analysis in Evolutionary Game Theory. Philosophy of Science 72 (5):1187-1196.score: 18.0
    A variety of robustness objections have been made against evolutionary game theory. One of these objections alleges that the games used in the underlying model are too arbitrary and oversimplified to generate a robust model of interesting prosocial behaviors. In this paper, I argue that the robustness objection can be met. However, in order to do so, we must attend to important conceptual issues regarding the nature of fairness, justice, and other moral concepts. Specifically, we must better understand (...)
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  35. Randy Au Patrick Grim, Robert Rosenberger Nancy Louie, Evan Selinger William Braynen & E. Eason Robb (2008). A Graphic Measure for Game-Theoretic Robustness. Synthese 163 (2).score: 18.0
    Robustness has long been recognized as an important parameter for evaluating game-theoretic results, but talk of ‘robustness’ generally remains vague. What we offer here is a graphic measure for a particular kind of robustness (‘matrix robustness’), using a three-dimensional display of the universe of 2 × 2 game theory. In such a measure specific games appear as specific volumes (Prisoner’s Dilemma, Stag Hunt, etc.), allowing a graphic image of the extent of particular game-theoretic effects in terms (...)
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  36. Brit Grosskopf, Yoella Bereby-Meyer & Max Bazerman (2007). On the Robustness of the Winner's Curse Phenomenon. Theory and Decision 63 (4):389-418.score: 18.0
    We set out to find ways to help decision makers overcome the “winner’s curse,” a phenomenon commonly observed in asymmetric information bargaining situations, and instead found strong support for its robustness. In a series of manipulations of the “Acquiring a Company Task,” we tried to enhance decision makers’ cognitive understanding of the task. We did so by presenting them with different parameters of the task, having them compare and contrast these different parameters, giving them full feedback on their history (...)
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  37. Chiara Lisciandra (forthcoming). Robustness Analysis Versus Reliable Process Reasoning. Metascience:1-5.score: 18.0
    Robert Hudson’s book is a contribution to the recent debate on robustness analysis in scientific practice, with a specific focus on the empirical sciences. In this context, robustness analysis is defined as a way to increase the probability of a certain hypothesis by showing that the same result is obtained from several, alternative methods. The rationale underlying this practice is that it would be highly unlikely if different, independent means of observation provided the same wrong outcome.We do not (...)
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  38. Michael Trevor Bycroft (2010). Going Outside the Model: Robustness Analysis and Experimental Science. Spontaneous Generations 3 (1):123-141.score: 18.0
    In 1966 the population biologist Richard Levins gave a forceful and in?uential defence of a method called “robustness analysis” (RA). RA is a way of assessing the result of a model by showing that different but related models give the same result. As Levins put it, “our truth is the intersection of independent lies” (1966, 423). Steven Orzack and Elliott Sober (1993) responded with an equally forceful critique of this method, concluding that the idea of robustness “lacks proper (...)
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  39. Lars Peter Hansen & Thomas J. Sargent (2007). Robustness. Princeton University Press.score: 18.0
    Technical, rigorous, and self-contained, this book will be useful for macroeconomists who seek to improve the robustness of decision-making processes.
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  40. Lena Soler (ed.) (2012). Characterizing the Robustness of Science: After the Practice Turn in Philosophy of Science. Springer Verlag.score: 18.0
    Featuring contributions from the world’s leading experts on the subject and based partly on several detailed case studies, this volume is the first comprehensive analysis of the scientific notion of robustness as well as of the general ...
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  41. Mark Schroeder (2005). Realism and Reduction: The Quest for Robustness. Philosophers' Imprint 5 (1):1-18.score: 16.0
    It doesn’t seem possible to be a realist about the traditional Christian God while claiming to be able to reduce God talk in naturalistically acceptable terms. Reduction, in this case, seems obviously eliminativist. Many philosophers seem to think that the same is true of the normative—that reductive “realists” about the normative are not really realists about the normative at all, or at least, only in some attenuated sense. This paper takes on the challenge of articulating what it is that makes (...)
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  42. James R. Beebe & Mark Jensen (2012). Surprising Connections Between Knowledge and Action: The Robustness of the Epistemic Side-Effect Effect. Philosophical Psychology 25 (5):689 - 715.score: 16.0
    A number of researchers have begun to demonstrate that the widely discussed ?Knobe effect? (wherein participants are more likely to think that actions with bad side-effects are brought about intentionally than actions with good or neutral side-effects) can be found in theory of mind judgments that do not involve the concept of intentional action. In this article we report experimental results that show that attributions of knowledge can be influenced by the kinds of (non-epistemic) concerns that drive the Knobe effect. (...)
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  43. Joseph Heath (2002). The Robustness of Altruism as an Evolutionary Strategy. Biology and Philosophy 17 (4):567-590.score: 16.0
    Kin selection, reciprocity and group selection are widely regarded as evolutionary mechanisms capable of sustaining altruism among humans andother cooperative species. Our research indicates, however, that these mechanisms are only particular examples of a broader set of evolutionary possibilities.In this paper we present the results of a series of simple replicator simulations, run on variations of the 2–player prisoner's dilemma, designed to illustrate the wide range of scenarios under which altruism proves to be robust under evolutionary pressures. The set of (...)
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  44. Scott Woodcock & Joseph Heath (2002). The Robustness of Altruism as an Evolutionary Strategy. Biology and Philosophy 17 (4):567-590.score: 16.0
    Kin selection, reciprocity and group selection are widely regarded as evolutionary mechanisms capable of sustaining altruism among humans andother cooperative species. Our research indicates, however, that these mechanisms are only particular examples of a broader set of evolutionary possibilities.In this paper we present the results of a series of simple replicator simulations, run on variations of the 2–player prisoner's dilemma, designed to illustrate the wide range of scenarios under which altruism proves to be robust under evolutionary pressures. The set of (...)
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  45. Johan J. Graafland, S. C. W. Eijffinger & H. SmidJohan (2004). Benchmarking of Corporate Social Responsibility: Methodological Problems and Robustness. [REVIEW] Journal of Business Ethics 53 (1-2):137-152.score: 16.0
    This paper investigates the possibilities and problems of benchmarking Corporate Social Responsibility (CSR). After a methodological analysis of the advantages and problems of benchmarking, we develop a benchmark method that includes economic, social and environmental aspects as well as national and international aspects of CSR. The overall benchmark is based on a weighted average of these aspects. The weights are based on the opinions of companies and NGO's. Using different methods of weighting, we find that the outcome of the benchmark (...)
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  46. J. Dwarswaard, M. Hilhorst & M. Trappenburg (2009). The Robustness of Medical Professional Ethics When Times Are Changing: A Comparative Study of General Practitioner Ethics and Surgery Ethics in The Netherlands. Journal of Medical Ethics 35 (10):621-625.score: 16.0
    Society in the 21st century is in many ways different from society in the 1950s, the 1960s or the 1970s. Two of the most important changes relate to the level of education in the population and the balance between work and private life. These days a large percentage of people are highly educated. Partly as a result of economic progress in the 1950s and the 1960s and partly due to the fact that many women entered the labour force, people started (...)
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  47. Eliyahu V. Sapir & Sullivan (2013). Scale Matters: Addressing the Limited Robustness of Findings on Negative Advertising. Japanese Journal of Political Science 14 (4):521-541.score: 16.0
    Negative campaign advertising is a major component of the electoral landscape, and has received much attention in the literature. In many studies, political scientists have tried to explain why some campaign ads contain more negative messages than others and to identify the determinants of this form of campaign behavior. In recent years, a number of studies have acknowledged the differences between alternative measures of negativity, but, in most cases, it is assumed that since these measures are highly correlated, they are (...)
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  48. Jay Odenbaugh (2011). True Lies: Realism, Robustness, and Models. Philosophy of Science 78 (5):1177-1188.score: 15.0
  49. Simon M. Huttegger (2007). Robustness in Signaling Games. Philosophy of Science 74 (5):839-847.score: 15.0
    The spontaneous emergence of signaling has already been studied in terms of standard evolutionary dynamics of signaling games. Standard evolutionary dynamics is given by the replicator equations. Thus, it is not clear whether the results for standard evolutionary dynamics depend crucially on the functional form of the replicator equations. In this paper I show that the basic results for the replicator dynamics of signaling games carry over to a number of other evolutionary dynamics. ‡This research was supported by the Konrad (...)
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