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  1. Betting blind: coping with uncertainty through redundancy.Makmiller Pedroso - 2022 - Synthese 200 (3):1-17.
    Multiple biological groups, such as ant colonies, appear to have a noteworthy inefficiency: they contain vast amounts of redundant members that are not strictly needed to maintain the group. Philosophers and biologists have proposed that such inefficiency is illusory because redundancy enhances the resilience of groups when living under harsh conditions. Still, this proposal is unsatisfactory in different respects. First, it is too vague to account for when redundancy is selectively advantageous. Furthermore, it overlooks cases in which redundancy fails to (...)
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  • Confirmation by Robustness Analysis: A Bayesian Account.Lorenzo Casini & Jürgen Landes - forthcoming - Erkenntnis.
    Some authors claim that minimal models have limited epistemic value. Others defend the epistemic benefits of modelling by invoking the role of robustness analysis for hypothesis confirmation but such arguments find much resistance. In this paper, we offer a Bayesian rationalization and defence of the view that robustness analysis can play a confirmatory role, and thereby shed light on the potential of minimal models for hypothesis confirmation. We illustrate our argument by reference to a case study from macroeconomics. At the (...)
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  • Experimental Design: Ethics, Integrity and the Scientific Method.Jonathan Lewis - 2020 - In Ron Iphofen (ed.), Handbook of Research Ethics and Scientific Integrity. Cham, Switzerland: pp. 459-474.
    Experimental design is one aspect of a scientific method. A well-designed, properly conducted experiment aims to control variables in order to isolate and manipulate causal effects and thereby maximize internal validity, support causal inferences, and guarantee reliable results. Traditionally employed in the natural sciences, experimental design has become an important part of research in the social and behavioral sciences. Experimental methods are also endorsed as the most reliable guides to policy effectiveness. Through a discussion of some of the central concepts (...)
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  • The Fate of Tensor-Vector-Scalar Modified Gravity.Shannon Sylvie Abelson - 2022 - Foundations of Physics 52 (1):1-19.
    The 2017 codetection of electromagnetic radiation and gravitational waves was the first of its kind and marked the beginning of multimessenger astronomy. But this event has been treated within recent literature as something of an end as well. The 2017 detection is often regarded as an instance of falsification for all theories of modified gravity which postulate gravitational waves propagate along separate geodesics from electromagnetic radiation, perhaps most notably Jacob Bekenstein’s Tensor-Vector-Scalar gravity. I critically examine this explicit endorsement of falsification (...)
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  • Confirming (Climate) Change: A Dynamical Account of Model Evaluation.Suzanne Kawamleh - 2022 - Synthese 200 (2):1-26.
    Philosophers of science have offered various accounts of climate model evaluation which have largely centered on model-fit assessment. However, despite the wide-spread prevalence of process-based evaluation in climate science practice, this sort of model evaluation has been undertheorized by philosophers of science. In this paper, I aim to expand this narrow philosophical view of climate model evaluation by providing a philosophical account of process evaluation that is rooted in a close examination of scientific practice. I propose dynamical adequacy as a (...)
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  • Model robustness in economics: the admissibility and evaluation of tractability assumptions.Ryan O’Loughlin & Dan Li - 2022 - Synthese 200 (1):1-23.
    Lisciandra poses a challenge for robustness analysis as applied to economic models. She argues that substituting tractability assumptions risks altering the main mathematical structure of the model, thereby preventing the possibility of meaningfully evaluating the same model under different assumptions. In such cases RA is argued to be inapplicable. However, Lisciandra is mistaken to take the goal of RA as keeping the mathematical properties of tractability assumptions intact. Instead, RA really aims to keep the modeling component while varying the corresponding (...)
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  • Mathematical Models and Robustness Analysis in Epistemic Democracy: A Systematic Review of Diversity Trumps Ability Theorem Models.Ryota Sakai - 2020 - Philosophy of the Social Sciences 50 (3):195-214.
    This article contributes to the revision of the procedure of robustness analysis of mathematical models in epistemic democracy using the systematic review method. It identifies the drawbacks of robustness analysis in epistemic democracy in terms of sample universality and inference from samples with the same results. To exemplify the effectiveness of systematic review, this article conducted a pilot review of diversity trumps ability theorem models, which are mathematical models of deliberation often cited by epistemic democrats. A review of nine models (...)
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  • The Epistemic Value of Independent Lies: False Analogies and Equivocations.Margherita Harris - 2021 - Synthese 199 (5-6):14577-14597.
    Here I critically assess an argument put forward by Kuorikoski et al. :541–567, 2010) for the epistemic import of model-based robustness analysis. I show that this argument is not sound since the sort of probabilistic independence on which it relies is unfeasible. By revising the notion of probabilistic independence imposed on the models’ results, I introduce a prima-facie more plausible argument. However, despite this prima-facie plausibility, I show that even this new argument is unsound in most if not all cases (...)
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  • Why Simpler Computer Simulation Models Can Be Epistemically Better for Informing Decisions.Casey Helgeson, Vivek Srikrishnan, Klaus Keller & Nancy Tuana - 2021 - Philosophy of Science 88 (2):213-233.
    For computer simulation models to usefully inform climate risk management, uncertainties in model projections must be explored and characterized. Because doing so requires running the model many ti...
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  • Abductively Robust Inference.Finnur Dellsén - 2017 - Analysis 77 (1):20-29.
    Inference to the Best Explanation (IBE) is widely criticized for being an unreliable form of ampliative inference – partly because the explanatory hypotheses we have considered at a given time may all be false, and partly because there is an asymmetry between the comparative judgment on which an IBE is based and the absolute verdict that IBE is meant to license. In this paper, I present a further reason to doubt the epistemic merits of IBE and argue that it motivates (...)
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  • What Does Robustness Teach Us in Climate Science: A Re-Appraisal.Eric Winsberg - 2018 - Synthese 198 (Suppl 21):5099-5122.
    In the philosophy of climate science, debate surrounding the issue of variety of evidence has mostly taken the form of attempting to connect these issues in climate science and climate modeling with philosophical accounts of what has come to be known as “robustness analysis.” I argue that an “explanatory” conception of robustness is the best candidate for understanding variety of evidence in climate science. I apply the analysis to both examples of model agreement, as well at to the convergence of (...)
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  • An analysis of the disagreement about added value by regional climate models.Elisabeth A. Lloyd, Melissa Bukovsky & Linda O. Mearns - 2021 - Synthese 198 (12):11645-11672.
    In this paper we consider some questions surrounding whether or not regional climate models “add value,” a controversial issue in climate science today. We highlight some objections frequently made about regional climate models both within and outside the community of modelers, including several claims that regional climate models do not “add value.” We show that there are a number of issues involved in the latter claims, the primary ones centering on the fact that different research questions are being pursued by (...)
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  • Variety of Evidence.Jürgen Landes - 2020 - Erkenntnis 85 (1):183-223.
    Varied evidence confirms more strongly than less varied evidence, ceteris paribus. This epistemological Variety of Evidence Thesis enjoys widespread intuitive support. We put forward a novel explication of one notion of varied evidence and the Variety of Evidence Thesis within Bayesian models of scientific inference by appealing to measures of entropy. Our explication of the Variety of Evidence Thesis holds in many of our models which also pronounce on disconfirmatory and discordant evidence. We argue that our models pronounce rightly. Against (...)
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  • Model Spread and Progress in Climate Modelling.Julie Jebeile & Anouk Barberousse - 2021 - European Journal for Philosophy of Science 11 (3):1-19.
    Convergence of model projections is often considered by climate scientists to be an important objective in so far as it may indicate the robustness of the models’ core hypotheses. Consequently, the range of climate projections from a multi-model ensemble, called “model spread”, is often expected to reduce as climate research moves forward. However, the successive Assessment Reports of the Intergovernmental Panel on Climate Change indicate no reduction in model spread, whereas it is indisputable that climate science has made improvements in (...)
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  • Derivational Robustness and Indirect Confirmation.Aki Lehtinen - 2018 - Erkenntnis 83 (3):539-576.
    Derivational robustness may increase the degree to which various pieces of evidence indirectly confirm a robust result. There are two ways in which this increase may come about. First, if one can show that a result is robust, and that the various individual models used to derive it also have other confirmed results, these other results may indirectly confirm the robust result. Confirmation derives from the fact that data not known to bear on a result are shown to be relevant (...)
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  • Allocating Confirmation with Derivational Robustness.Aki Lehtinen - 2016 - Philosophical Studies 173 (9):2487-2509.
    Robustness may increase the degree to which the robust result is indirectly confirmed if it is shown to depend on confirmed rather than disconfirmed assumptions. Although increasing the weight with which existing evidence indirectly confirms it in such a case, robustness may also be irrelevant for confirmation, or may even disconfirm. Whether or not it confirms depends on the available data and on what other results have already been established.
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  • Measurement Perspective, Process, and the Pandemic.Vadim Keyser & Hannah Howland - 2020 - European Journal for Philosophy of Science 11 (1):1-26.
    This discussion centers on two desiderata: the role of measurement in information-gathering and physical interaction in scientific practice. By taking inspiration from van Fraassen’s view, we present a methodological account of perspectival measurement that addresses empirical practice where there is complex intervention, disagreeing results, and limited theory. The specific aim of our account is to provide a methodological prescription for developing measurement processes in the context of limited theory. The account should be useful to philosophers of science, who are interested (...)
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  • The Epistemic Virtue of Robustness in Climate Modeling (MA Dissertation).Parjanya Joshi - 2019 - Dissertation, Tata Institute of Social Sciences
    The aim of this dissertation is to comprehensively study various robustness arguments proposed in the literature from Levins to Lloyd as well as the opposition offered to them and pose enquiry into the degree of epistemic virtue that they provide to the model prediction results with respect to climate science and modeling. Another critical issue that this dissertation strives to examine is that of the actual epistemic notion that is operational when scientists and philosophers appeal to robustness. In attempting to (...)
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  • Idealizations and Partitions: A Defense of Robustness Analysis.Gareth P. Fuller & Armin W. Schulz - 2021 - European Journal for Philosophy of Science 11 (4):1-15.
    We argue that the robustness analysis of idealized models can have confirmational power. This responds to concerns recently raised in the literature, according to which the robustness analysis of models whose idealizations are not discharged is unable to confirm the causal mechanisms underlying these models, and the robustness analysis of models whose idealizations are discharged is unnecessary. In response, we make clear that, where idealizations sweep out, in a specific way, the space of possibilities— which is sometimes, though not always, (...)
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  • Even for Objectivists, Sleeping Beauty Isn’T so Simple.Kai Draper - 2017 - Analysis 77 (1):29-37.
    Writing collectively as the Oscar Seminar in 2008, John Pollock and several colleagues advance an objectivist argument for a 1/3 solution to the Sleeping Beauty problem. In 2011, Joel Pust raises a serious objection to their argument to which Paul D. Thorn, a member of the Oscar Seminar, offers a subtle reply. I argue that the Oscar Seminar s argument for 1/3 is unsound. I do not, however, defend Pust’s objection. Rather I develop a new objection, one that is not (...)
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  • Aggregating Evidence in Climate Science: Consilience, Robustness and the Wisdom of Multiple Models.Martin A. Vezér - unknown
    The goal of this dissertation is to contribute to the epistemology of science by addressing a set of related questions arising from current discussions in the philosophy and science of climate change: Given the imperfection of computer models, how do they provide information about large and complex target systems? What is the relationship between consilient reasoning and robust evidential support in the production of scientific knowledge? Does taking the mean of a set of model outputs provide epistemic advantages over using (...)
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  • Similarity, Adequacy, and Purpose: Understanding the Success of Scientific Models.Melissa Jacquart - 2016 - Dissertation, University of Western Ontario
    A central component to scientific practice is the construction and use of scientific models. Scientists believe that the success of a model justifies making claims that go beyond the model itself. However, philosophical analysis of models suggests that drawing inferences about the world from successful models is more complex. In this dissertation I develop a framework that can help disentangle the related strands of evaluation of model success, model extendibility, and the ability to draw ampliative inferences about the world from (...)
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  • The Strategy of Model Building in Climate Science.Lachlan Douglas Walmsley - 2020 - Synthese 199 (1-2):745-765.
    In the 1960s, theoretical biologist Richard Levins criticised modellers in his own discipline of population biology for pursuing the “brute force” strategy of building hyper-realistic models. Instead of exclusively chasing complexity, Levins advocated for the use of multiple different kinds of complementary models, including much simpler ones. In this paper, I argue that the epistemic challenges Levins attributed to the brute force strategy still apply to state-of-the-art climate models today: they have big appetites for unattainable data, they are limited by (...)
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  • How to Make Value-Driven Climate Science for Policy More Ethical.Justin Donhauser - 2021 - Studies in History and Philosophy of Science Part A 89:31-40.
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  • Value Management and Model Pluralism in Climate Science.Julie Jebeile & Michel Crucifix - 2021 - Studies in History and Philosophy of Science Part A 88 (August 2021):120-127.
    Non-epistemic values pervade climate modelling, as is now well documented and widely discussed in the philosophy of climate science. Recently, Parker and Winsberg have drawn attention to what can be termed “epistemic inequality”: this is the risk that climate models might more accurately represent the future climates of the geographical regions prioritised by the values of the modellers. In this paper, we promote value management as a way of overcoming epistemic inequality. We argue that value management can be seriously considered (...)
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  • Variety-of-Evidence Reasoning About the Distant Past: A Case Study in Paleoclimate Reconstruction.Martin Vezér - 2017 - European Journal for Philosophy of Science 7 (2):257-265.
    The epistemology of studies addressing questions about historical and prehistorical phenomena is a subject of increasing discussion among philosophers of science. A related field of inquiry that has yet to be connected to this topic is the epistemology of climate science. Branching these areas of research, I show how variety-of-evidence reasoning accounts for scientific inferences about the past by detailing a case study in paleoclimate reconstruction. This analysis aims to clarify the logic of historical inquiry in general and, by focusing (...)
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  • Robustness Reasoning in Climate Model Comparisons.Ryan O’Loughlin - 2021 - Studies in History and Philosophy of Science Part A 85:34-43.
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  • Climate Models: How to Assess Their Reliability.Martin Carrier & Johannes Lenhard - 2019 - International Studies in the Philosophy of Science 32 (2):81-100.
    The paper discusses modelling uncertainties in climate models and how they can be addressed based on physical principles as well as based on how the models perform in light of empirical data. We ar...
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  • Computer Models and the Evidence of Anthropogenic Climate Change: An Epistemology of Variety-of-Evidence Inferences and Robustness Analysis.Martin A. Vezér - 2016 - Studies in History and Philosophy of Science Part A 56:95-102.
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