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  1. Reciprocity: Weak or strong? What punishment experiments do (and do not) demonstrate.Francesco Guala - 2012 - Behavioral and Brain Sciences 35 (1):1-15.
    Economists and biologists have proposed a distinction between two mechanisms – “strong” and “weak” reciprocity – that may explain the evolution of human sociality. Weak reciprocity theorists emphasize the benefits of long-term cooperation and the use of low-cost strategies to deter free-riders. Strong reciprocity theorists, in contrast, claim that cooperation in social dilemma games can be sustained by costly punishment mechanisms, even in one-shot and finitely repeated games. To support this claim, they have generated a large body of evidence concerning (...)
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  • Neuroeconomics and Confirmation Theory.Christopher Clarke - 2014 - Philosophy of Science 81 (2):195-215.
    Neuroeconomics is a research programme founded on the thesis that cognitive and neurobiological data constitute evidence for answering economic questions. I employ confirmation theory in order to reject arguments both for and against neuroeconomics. I also emphasize that some arguments for neuroeconomics will not convince the skeptics because these arguments make a contentious assumption: economics aims for predictions and deep explanations of choices in general. I then argue for neuroeconomics by appealing to a much more restrictive (and thereby skeptic-friendly) characterization (...)
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  • Robustness analysis disclaimer: please read the manual before use!Jaakko Kuorikoski, Aki Lehtinen & Caterina Marchionni - 2012 - Biology and Philosophy 27 (6):891-902.
    Odenbaugh and Alexandrova provide a challenging critique of the epistemic benefits of robustness analysis, singling out for particular criticism the account we articulated in Kuorikoski et al.. Odenbaugh and Alexandrova offer two arguments against the confirmatory value of robustness analysis: robust theorems cannot specify causal mechanisms and models are rarely independent in the way required by robustness analysis. We address Odenbaugh and Alexandrova’s criticisms in order to clarify some of our original arguments and to shed further light on the properties (...)
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  • Robustness, discordance, and relevance.Jacob Stegenga - 2009 - Philosophy of Science 76 (5):650-661.
    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 in ideal evidential circumstances (i.e., (...)
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  • Two styles of neuroeconomics.Don Ross - 2008 - Economics and Philosophy 24 (3):473-483.
    I distinguish between two styles of research that are both called . Neurocellular economics (NE) uses the modelling techniques and mathematics of economics to model relatively encapsulated functional parts of brains. This approach rests upon the fact that brains are, like markets, massively distributed information-processing networks over which executive systems can exert only limited and imperfect governance. Harrison's (2008) deepest criticisms of neuroeconomics do not apply to NE. However, the more famous style of neuroeconomics is behavioural economics in the scanner. (...)
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  • (1 other version)A bayesian account of independent evidence with applications.Branden Fitelson - 2000 - Proceedings of the Philosophy of Science Association 2001 (3):S123-.
    outlined. This account is partly inspired by the work of C.S. Peirce. When we want to consider how degree of confirmation varies with changing I show that a large class of quantitative Bayesian measures of con-.
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  • Robust evidence and secure evidence claims.Kent W. Staley - 2004 - Philosophy of Science 71 (4):467-488.
    Many philosophers have claimed that evidence for a theory is better when multiple independent tests yield the same result, i.e., when experimental results are robust. Little has been said about the grounds on which such a claim rests, however. The present essay presents an analysis of the evidential value of robustness that rests on the fallibility of assumptions about the reliability of testing procedures and a distinction between the strength of evidence and the security of an evidence claim. Robustness can (...)
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  • Robustness Analysis.Michael Weisberg - 2006 - Philosophy of Science 73 (5):730-742.
    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 is a nonempirical form of confirmation, effective only under unusual circumstances. This paper addresses Orzack and Sober's criticisms by giving a new account of robustness analysis and (...)
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  • Mesosomes: A study in the nature of experimental reasoning.Robert G. Hudson - 1999 - Philosophy of Science 66 (2):289-309.
    Culp (1994) provides a defense for a form of experimental reasoning entitled 'robustness'. Her strategy is to examine a recent episode in experimental microbiology--the case of the mistaken discovery of a bacterial organelle called a 'mesosome'--with an eye to showing how experimenters effectively used robust experimental reasoning (or could have used robust reasoning) to refute the existence of the mesosome. My plan is to criticize Culp's assessment of the mesosome episode and to cast doubt on the epistemic significance of robustness. (...)
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  • Saving the phenomena.James Bogen & James Woodward - 1988 - Philosophical Review 97 (3):303-352.
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  • Robustness, Diversity of Evidence, and Probabilistic Independence.Jonah N. Schupbach - 2015 - In Uskali Mäki, Stéphanie Ruphy, Gerhard Schurz & Ioannis Votsis (eds.), Recent Developments in the Philosophy of Science. Cham: Springer. pp. 305-316.
    In robustness analysis, hypotheses are supported to the extent that a result proves robust, and a result is robust to the extent that we detect it in diverse ways. But what precise sense of diversity is at work here? In this paper, I show that the formal explications of evidential diversity most often appealed to in work on robustness – which all draw in one way or another on probabilistic independence – fail to shed light on the notion of diversity (...)
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  • Using Multiple Means of Determination.Jutta Schickore & Klodian Coko - 2013 - International Studies in the Philosophy of Science 27 (3):295-313.
    This article examines a metaphilosophical issue, namely existing disagreements in philosophy of science about the significance of using multiple means of determination in scientific practice. We argue that this disagreement can, in part, be resolved by separating different questions that can be asked about the use of multiple means of determination, including the following: what can be concluded from the convergence of data or the convergence of claims about phenomena? Are the conclusions drawn from the convergence of data and of (...)
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  • Experimental, cultural, and neural evidence of deliberate prosociality.Colin F. Camerer - 2013 - Trends in Cognitive Sciences 17 (3):106-108.
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  • The futile search for true utility.Roberto Fumagalli - 2013 - Economics and Philosophy 29 (3):325-347.
    In traditional decision theory, utility is regarded as a mathematical representation of preferences to be inferred from agents hedonic experiences. Some go as far as to contend that utility is literally computed by specific neural areas and urge economists to complement or substitute their notion of utility with some neuro-psychological construct. In this paper, I distinguish three notions of utility that are frequently mentioned in debates about decision theory and examine some critical issues regarding their definition and measurability. Moreover, I (...)
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  • Data, phenomena, and reliability.James Woodward - 2000 - Philosophy of Science 67 (3):179.
    This paper explores how data serve as evidence for phenomena. In contrast to standard philosophical models which invite us to think of evidential relationships as logical relationships, I argue that evidential relationships in the context of data-to-phenomena reasoning are empirical relationships that depend on holding the right sort of pattern of counterfactual dependence between the data and the conclusions investigators reach on the phenomena themselves.
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  • Causality: Models, Reasoning and Inference.Judea Pearl - 2000 - Tijdschrift Voor Filosofie 64 (1):201-202.
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  • The Methodological Strategy of Robustness in the Context of Experimental WIMP Research.Robert Hudson - 2009 - Foundations of Physics 39 (2):174-193.
    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), one of (...)
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  • Economic Modelling as Robustness Analysis.Jaakko Kuorikoski, Aki Lehtinen & Caterina Marchionni - 2010 - British Journal for the Philosophy of Science 61 (3):541-567.
    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 usually difficult to tell (...)
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  • Robust and Discordant Evidence: Methodological Lessons from Clinical Research.Spencer Phillips Hey - 2015 - Philosophy of Science 82 (1):55-75.
    The concordance of results that are “robust” across multiple scientific modalities is widely considered to play a critical role in the epistemology of science. But what should we make of those cases where such multimodal evidence is discordant? Jacob Stegenga has recently argued that robustness is “worse than useless” in these cases, suggesting that “different kinds of evidence cannot be combined in a coherent way.” In this article I respond to this critique and illustrate the critical methodological role that robustness (...)
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  • Buyer beware: robustness analyses in economics and biology.Jay Odenbaugh & Anna Alexandrova - 2011 - Biology and Philosophy 26 (5):757-771.
    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 robustness analysis has (...)
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  • Bayesian Networks and the Problem of Unreliable Instruments.Luc Bovens & Stephan Hartmann - 2002 - Philosophy of Science 69 (1):29-72.
    We appeal to the theory of Bayesian Networks to model different strategies for obtaining confirmation for a hypothesis from experimental test results provided by less than fully reliable instruments. In particular, we consider (i) repeated measurements of a single test consequence of the hypothesis, (ii) measurements of multiple test consequences of the hypothesis, (iii) theoretical support for the reliability of the instrument, and (iv) calibration procedures. We evaluate these strategies on their relative merits under idealized conditions and show some surprising (...)
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  • Independent evidence about a common cause.Elliott Sober - 1989 - Philosophy of Science 56 (2):275-287.
    To infer the state of a cause from the states of its effects, independent lines of evidence are preferable to dependent ones. This familiar idea is here investigated, the goal being to identify its presuppositions. Connections are drawn with Reichenbach's (1956) and Salmon's (1984) discussions of the principle of the common cause.
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  • No revolution necessary: Neural mechanisms for economics.Carl F. Craver - 2008 - Economics and Philosophy 24 (3):381-406.
    We argue that neuroeconomics should be a mechanistic science. We defend this view as preferable both to a revolutionary perspective, according to which classical economics is eliminated in favour of neuroeconomics, and to a classical economic perspective, according to which economics is insulated from facts about psychology and neuroscience. We argue that, like other mechanistic sciences, neuroeconomics will earn its keep to the extent that it either reconfigures how economists think about decision-making or how neuroscientists think about brain mechanisms underlying (...)
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  • (1 other version)A Bayesian Account of Independent Evidence with Applications.Branden Fitelson - 2001 - Philosophy of Science 68 (S3):S123-S140.
    A Bayesian account of independent evidential support is outlined. This account is partly inspired by the work of C. S. Peirce. I show that a large class of quantitative Bayesian measures of confirmation satisfy some basic desiderata suggested by Peirce for adequate accounts of independent evidence. I argue that, by considering further natural constraints on a probabilistic account of independent evidence, all but a very small class of Bayesian measures of confirmation can be ruled out. In closing, another application of (...)
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  • Economic man – or straw man?Ken Binmore - 2005 - Behavioral and Brain Sciences 28 (6):817-818.
    The target article by Henrich et al. describes some economic experiments carried out in fifteen small-scale societies. The results are broadly supportive of an approach to understanding social norms that is commonplace among game theorists. It is therefore perverse that the rhetorical part of the paper should be devoted largely to claiming that “economic man” is an experimental failure that needs to be replaced by an alternative paradigm. This brief commentary contests the paper's caricature of economic theory, and offers a (...)
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  • Explanatory relevance across disciplinary boundaries: the case of neuroeconomics.Jaakko Kuorikoski & Petri Ylikoski - 2010 - Journal of Economic Methodology 17 (2):219–228.
    Many of the arguments for neuroeconomics rely on mistaken assumptions about criteria of explanatory relevance across disciplinary boundaries and fail to distinguish between evidential and explanatory relevance. Building on recent philosophical work on mechanistic research programmes and the contrastive counterfactual theory of explanation, we argue that explaining an explanatory presupposition or providing a lower-level explanation does not necessarily constitute explanatory improvement. Neuroscientific findings have explanatory relevance only when they inform a causal and explanatory account of the psychology of human decision-making.
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