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  1. Justifying Idealization by Abstraction.Sebastian Lutz -
    I show how omissions lead to robustness and can justify distortions, and I give inferentially relevant explications of abstraction and idealization. Abstraction is explicated as the omission of all and only those claims that use a specific vocabulary; idealization is explicated as the distortion of only those claims that use a specific vocabulary. With these explications, abstraction can justify idealization. As examples of how abstraction justifies idealization and leads to robustness, I discuss Beauchamp and Childress's four principles of biomedical ethics (...)
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  2. From Phenomenological-Hermeneutical Approaches to Realist Perspectivism.Mahdi Khalili - 2022 - European Journal for Philosophy of Science 12 (4).
    This paper draws on the phenomenological-hermeneutical approaches to philosophy of science to develop realist perspectivism, an integration of experimental realism and perspectivism. Specifically, the paper employs the distinction between “manifestation” and “phenomenon” and it advances the view that the evidence of a real entity is “explorable” in order to argue that instrumentally-mediated robust evidence indicates real entities. Furthermore, it underpins the phenomenological notion of the horizonal nature of scientific observation with perspectivism, so accounting for scientific pluralism even in the cases (...)
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  3. 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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  4. Objectivity as Independence.Alexander Reutlinger - 2021 - Episteme:1-8.
    Building on Nozick's invariantism about objectivity, I propose to define scientific objectivity in terms of counterfactual independence. I will argue that such a counterfactual independence account is (a) able to overcome the decisive shortcomings of Nozick's original invariantism and (b) applicable to three paradigmatic kinds of scientific objectivity (that is, objectivity as replication, objectivity as robustness, and objectivity as Mertonian universalism).
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  5. Making Confident Decisions with Model Ensembles.Joe Roussos, Richard Bradley & Roman Frigg - 2021 - Philosophy of Science 88 (3):439-460.
    Many policy decisions take input from collections of scientific models. Such decisions face significant and often poorly understood uncertainty. We rework the so-called confidence approach to tackle decision-making under severe uncertainty with multiple models, and we illustrate the approach with a case study: insurance pricing using hurricane models. The confidence approach has important consequences for this case and offers a powerful framework for a wide class of problems. We end by discussing different ways in which model ensembles can feed information (...)
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  6. Multiple Discoveries, Inevitability, and Scientific Realism.Luca Tambolo & Gustavo Cevolani - 2021 - Studies in History and Philosophy of Science Part A 90 (December 2021):30-38.
    When two or more (groups of) researchers independently investigating the same domain arrive at the same result, a multiple discovery occurs. The pervasiveness of multiple discoveries in science suggests the intuition that they are in some sense inevitable—that one should view them as results that force themselves upon us, so to speak. We argue that, despite the intuitive force of such an “inevitabilist insight,” one should reject it. More specifically, we distinguish two facets of the insight and argue that: (a) (...)
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  7. Should Explanations Omit the Details?Darren Bradley - 2020 - British Journal for the Philosophy of Science 71 (3):827-853.
    There is a widely shared belief that the higher-level sciences can provide better explanations than lower-level sciences. But there is little agreement about exactly why this is so. It is often suggested that higher-level explanations are better because they omit details. I will argue instead that the preference for higher-level explanations is just a special case of our general preference for informative, logically strong, beliefs. I argue that our preference for informative beliefs entirely accounts for why higher-level explanations are sometimes (...)
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  8. Jean Perrin and the Philosophers’ Stories: The Role of Multiple Determination in Determining Avogadro’s Number.Klodian Coko - 2020 - Hopos: The Journal of the International Society for the History of Philosophy of Science 10 (1):143-193.
    The French physicist Jean Baptiste Perrin is widely credited with providing the conclusive argument for atomism. The most well-known part of Perrin’s argument is his description of thirteen different procedures for determining Avogadro’s number (N)–the number of atoms, ions, and molecules contained in a gram-atom, gram-ion, and gram-mole of a substance, respectively. Because of its success in ending the atomism debates Perrin’s argument has been the focus of much philosophical interest. The various philosophers, however, have reached different conclusions, not only (...)
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  9. Crystallized Regularities.Verónica Gómez Sánchez - 2020 - Journal of Philosophy 117 (8):434-466.
    This essay proposes a reductive account of robust macro-regularities. On the view proposed, regularities can earn their elite scientific status by featuring in good summaries of restricted regions in the space of physical possibilities: our “modal neighborhoods.” I argue that this view vindicates “nomic foundationalism”, while doing justice to the practice of invoking physically contingent generalizations in higher-level explanations. Moreover, the view suggests an explanation for the particular significance of robust macro-regularities: we rely on summaries of our modal neighborhoods when (...)
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  10. What Was Perrin Really Doing in His Proof of the Reality of Atoms?Robert Hudson - 2020 - Hopos: The Journal of the International Society for the History of Philosophy of Science 10 (1):194-218.
    It is commonly thought that Jean Perrin argued for the reality of atoms in the early twentieth century by using what Wesley Salmon calls a “common cause” argument, also known as robustness reasoning. After citing some concerns with this interpretation of Perrin, I offer a different interpretation of Perrin’s work that more closely depicts the details of Perrin’s reasoning in his relevant published writings. I then offer a historical argument that supports this interpretation and discuss the philosophical merits of Perrin’s (...)
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  11. Reflections on the Reception of Jean Perrin’s Experiments by His Contemporaries.Milena Ivanova - 2020 - Hopos: The Journal of the International Society for the History of Philosophy of Science 10 (1):219-224.
  12. Robust Biomarkers: Methodologically Tracking Causal Processes in Alzheimer’s Measurement.Vadim Keyser & Louis Sarry - 2020 - In Barbara Osimani & Adam La Caze (eds.), Uncertainty in Pharmacology. pp. 289-318.
    In biomedical measurement, biomarkers are used to achieve reliable prediction of, and useful causal information about patient outcomes while minimizing complexity of measurement, resources, and invasiveness. A biomarker is an assayable metric that discloses the status of a biological process of interest, be it normative, pathophysiological, or in response to intervention. The greatest utility from biomarkers comes from their ability to help clinicians (and researchers) make and evaluate clinical decisions. In this paper we discuss a specific methodological use of clinical (...)
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  13. ¿Cómo retractarse en ciencia?Quan-Hoang Vuong - 2020 - Investigación y Ciencia 45 (530):1-2.
    La comunidad científica debe acordar cuál es la información esencial que hay que comunicar al retirar un artículo.
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  14. Retractions: The Good, the Bad, and the Ugly.Quan-Hoang Vuong - 2020 - LSE Impact of Social Sciences 2020 (2):1-4.
    Retractions play an important role in research communication by highlighting and explaining how research projects have failed and thereby preventing these mistakes from being repeated. However, the process of retraction and the data it produces is often sparse or incomplete. Drawing on evidence from 2046 retraction records, Quan-Hoang Vuong discusses the emerging trends this data highlights and argues for the need to enforce reporting standards for retractions, as a means of de-stigmatising retraction and rewarding practising integrity in the scholarly record.
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  15. Vindicating Methodological Triangulation.Remco Heesen, Liam Kofi Bright & Andrew Zucker - 2019 - Synthese 196 (8):3067-3081.
    Social scientists use many different methods, and there are often substantial disagreements about which method is appropriate for a given research question. In response to this uncertainty about the relative merits of different methods, W. E. B. Du Bois advocated for and applied “methodological triangulation”. This is to use multiple methods simultaneously in the belief that, where one is uncertain about the reliability of any given method, if multiple methods yield the same answer that answer is confirmed more strongly than (...)
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  16. What Types of Values Enter Simulation Validation and What Are Their Roles?Gertrude Hirsch Hadorn & Christoph Baumberger - 2019 - In Claus Beisbart & Nicole J. Saam (eds.), Computer Simulation Validation - Fundamental Concepts, Methodological Frameworks, and Philosophical Perspectives. Springer. pp. 961-979.
    Based on a framework that distinguishes several types, roles and functions of values in science, we discuss legitimate applications of values in the validation of computer simulations. We argue that, first, epistemic valuesEpistemic values, such as empirical accuracyAccuracy and coherence with background knowledgeBackground knowledge, have the role to assess the credibilityCredibility of simulation results, whereas, second, cognitive valuesCognitive values, such as comprehensiveness of a conceptual modelConceptual model or easy handling of a numerical model, have the role to assess the usefulness (...)
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  17. 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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  18. Artifacts and Artefacts: A Methodological Classification of Context-Specific Regularities.Vadim Keyser - 2019 - In History and Philosophy of Technoscience: Perspectives on Classification in Synthetic Sciences: Unnatural Kinds. London, UK: pp. 63-77.
    Traditionally, in the literature on robustness analysis objects are classified as genuine phenomena (natural objects, events, and processes) or artifacts (results produced in error). But much of biological measurement requires the manipulation of local experimental conditions in order to produce new effects. These types of intervention-based regularities are neither natural objects nor artifacts; characterizing them as either fails adequately to address key ontological properties as well as their role in scientific practice. It is argued that a new classification, based on (...)
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  19. The Instrument of Science: Scientific Anti-Realism Revitalised.Darrell P. Rowbottom - 2019 - New York: Routledge.
    Roughly, instrumentalism is the view that science is primarily, and should primarily be, an instrument for furthering our practical ends. It has fallen out of favour because historically influential variants of the view, such as logical positivism, suffered from serious defects. -/- In this book, however, Darrell P. Rowbottom develops a new form of instrumentalism, which is more sophisticated and resilient than its predecessors. This position—‘cognitive instrumentalism’—involves three core theses. First, science makes theoretical progress primarily when it furnishes us with (...)
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  20. What We (Should) Talk About When We Talk About Fruitfulness.Silvia Ivani - 2018 - European Journal for Philosophy of Science 9 (1):1-18.
    What are the relevant values to the appraisal of research programs? This question remains hotly debated, as philosophers have recently proposed many lists of values potentially relevant to scientific appraisal. Surprisingly, despite being mentioned in many lists, little attention has been paid to fruitfulness. It is unclear how fruitfulness should be explicated, and whether it has any substantial role in scientific appraisal. In this paper, I argue we should explicate fruitfulness as the capacity to develop of research programs. Moreover, I (...)
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  21. Inference to the More Robust Explanation.Nicholaos Jones - 2018 - British Journal for the Philosophy of Science 69 (1):75-102.
    ABSTRACT There is a new argument form within theoretical biology. This form takes as input competing explanatory models; it yields as output the conclusion that one of these models is more plausible than the others. The driving force for this argument form is an analysis showing that one model exhibits more parametric robustness than its competitors. This article examines these inferences to the more robust explanation, analysing them as variants of inference to the best explanation. The article defines parametric robustness (...)
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  22. Systematizing the Theoretical Virtues.Michael Keas - 2018 - Synthese 195 (6):2761-2793.
    There are at least twelve major virtues of good theories: evidential accuracy, causal adequacy, explanatory depth, internal consistency, internal coherence, universal coherence, beauty, simplicity, unification, durability, fruitfulness, and applicability. These virtues are best classified into four classes: evidential, coherential, aesthetic, and diachronic. Each virtue class contains at least three virtues that sequentially follow a repeating pattern of progressive disclosure and expansion. Systematizing the theoretical virtues in this manner clarifies each virtue and suggests how they might have a coordinated and cumulative (...)
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  23. Robust Fractional-Order PID Controller Tuning Based on Bode’s Optimal Loop Shaping.Lu Liu & Shuo Zhang - 2018 - Complexity 2018:1-14.
    This paper presents a novel fractional-order PID controller tuning strategy based on Bode’s optimal loop shaping which is commonly used for LTI feedback systems. Firstly, the controller parameters are achieved based on flat phase property and Bode’s optimal reference model, so that the controlled system is robust to gain variations and can achieve desirable transient performance according to various control requirements. Then, robustness analysis of the controlled system is carried out to support the results. Furthermore, the parameter setting is analyzed (...)
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  24. Replicability or Reproducibility? On the Replication Crisis in Computational Neuroscience and Sharing Only Relevant Detail.Marcin Miłkowski, Witold M. Hensel & Mateusz Hohol - 2018 - Journal of Computational Neuroscience 3 (45):163-172.
    Replicability and reproducibility of computational models has been somewhat understudied by “the replication movement.” In this paper, we draw on methodological studies into the replicability of psychological experiments and on the mechanistic account of explanation to analyze the functions of model replications and model reproductions in computational neuroscience. We contend that model replicability, or independent researchers' ability to obtain the same output using original code and data, and model reproducibility, or independent researchers' ability to recreate a model without original code, (...)
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  25. The Main Faces of Robustness.Giovanni Boniolo, Mattia Andreoletti, Federico Boem & Emanuele Ratti - 2017 - Dialogue and Universalism 27 (3):157-172.
    In the last decade, robustness has been extensively mentioned and discussed in biology as well as in the philosophy of the life sciences. Nevertheless, from both fields, someone has affirmed that this debate has resulted in more semantic confusion than in semantic clearness. Starting from this claim, we wish to offer a sort of prima facie map of the different usages of the term. In this manner we would intend to predispose a sort of “semantic platform” which could be exploited (...)
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  26. 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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  27. Robustness Analysis and Tractability in Modeling.Chiara Lisciandra - 2017 - European Journal for Philosophy of Science 7 (1):79-95.
    In the philosophy of science and epistemology literature, robustness analysis has become an umbrella term that refers to a variety of strategies. One of the main purposes of this paper is to argue that different strategies rely on different criteria for justifications. More specifically, I will claim that: i) robustness analysis differs from de-idealization even though the two concepts have often been conflated in the literature; ii) the comparison of different model frameworks requires different justifications than the comparison of models (...)
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  28. Robustness and Independent Evidence.Jacob Stegenga & Tarun Menon - 2017 - Philosophy of Science 84 (3):414-435.
    Robustness arguments hold that hypotheses are more likely to be true when they are confirmed by diverse kinds of evidence. Robustness arguments require the confirming evidence to be independent. We identify two kinds of independence appealed to in robustness arguments: ontic independence —when the multiple lines of evidence depend on different materials, assumptions, or theories—and probabilistic independence. Many assume that OI is sufficient for a robustness argument to be warranted. However, we argue that, as typically construed, OI is not a (...)
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  29. Derivational Robustness, Credible Substitute Systems and Mathematical Economic Models: The Case of Stability Analysis in Walrasian General Equilibrium Theory.D. Wade Hands - 2016 - European Journal for Philosophy of Science 6 (1):31-53.
    This paper supports the literature which argues that derivational robustness can have epistemic import in highly idealized economic models. The defense is based on a particular example from mathematical economic theory, the dynamic Walrasian general equilibrium model. It is argued that derivational robustness first increased and later decreased the credibility of the Walrasian model. The example demonstrates that derivational robustness correctly describes the practices of a particular group of influential economic theorists and provides support for the arguments of philosophers who (...)
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  30. The Belief Illusion.J. Christopher Jenson - 2016 - British Journal for the Philosophy of Science 67 (4):965-995.
    I offer a new argument for the elimination of ‘beliefs’ from cognitive science based on Wimsatt’s concept of robustness and a related concept of fragility. Theoretical entities are robust if multiple independent means of measurement produce invariant results in detecting them. Theoretical entities are fragile when multiple independent means of detecting them produce highly variant results. I argue that sufficiently fragile theoretical entities do not exist. Recent studies in psychology show radical variance between what self-report and non-verbal behaviour indicate about (...)
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  31. 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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  32. Robustness and Evidence of Mechanisms in Early Experimental Atherosclerosis Research.Veli-Pekka Parkkinen - 2016 - Studies in History and Philosophy of Science Part C: Studies in History and Philosophy of Biological and Biomedical Sciences 60:44-55.
  33. Counterfactually Robust Inferences, Modally Ruled Out Inferences, and Semantic Holism.Pietro Salis - 2016 - AL-Mukhatabat (16):111-35.
    It is often argued that inferential role semantics (IRS) entails semantic holism as long as theorists fail to answer the question about which inferences, among the many, are meaning-constitutive. Since analyticity, as truth in virtue of meaning, is a widely dismissed notion in indicating which inferences determine meaning, it seems that holism follows. Semantic holism is often understood as facing problems with the stability of content and many usual explanations of communication. Thus, we should choose between giving up IRS, to (...)
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  34. The Structure and Epistemic Import of Multiple Determination in Scientific Practice.Klodian Coko - 2015 - Dissertation, Indiana University
    Empirical multiple determination (multiple determination, for short) is the epistemic strategy of establishing the same result by means of multiple and independent procedures. It is an important epistemic strategy praised by both philosophers of science and practicing scientists. Commentators from different contexts have referred to multiple determination as one of the main strategies that researchers use to establish the reliability of their results. Multiple determination has been used to address a variety of problems that arise because of the fallibility of (...)
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  35. Robustness and Reality.Markus I. Eronen - 2015 - Synthese 192 (12):3961-3977.
    Robustness is often presented as a guideline for distinguishing the true or real from mere appearances or artifacts. Most of recent discussions of robustness have focused on the kind of derivational robustness analysis introduced by Levins, while the related but distinct idea of robustness as multiple accessibility, defended by Wimsatt, has received less attention. In this paper, I argue that the latter kind of robustness, when properly understood, can provide justification for ontological commitments. The idea is that we are justified (...)
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  36. Probability and the Explanatory Virtues: Figure 1.Clark Glymour - 2015 - British Journal for the Philosophy of Science 66 (3):591-604.
    Recent literature in philosophy of science has addressed purported notions of explanatory virtues—‘explanatory power’, ‘unification’, and ‘coherence’. In each case, a probabilistic relation between a theory and data is said to measure the power of an explanation, or degree of unification, or degree of coherence. This essay argues that the measures do not capture cases that are paradigms of scientific explanation, that the available psychological evidence indicates that the measures do not capture judgements of explanatory power, and, finally, that the (...)
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  37. 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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  38. Robustness Analysis Versus Reliable Process Reasoning: Robert Hudson: Seeing Things: The Philosophy of Reliable Observation. Oxford: Oxford University Press, 2014, Xii+274pp, £41.99, $58.50 HB.Chiara Lisciandra - 2014 - Metascience 24 (1):37-41.
    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 believe in (...)
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  39. Corroborating Evidence‐Based Medicine.Alexander Mebius - 2014 - Journal of Evaluation in Clinical Practice 20 (6):915-920.
    Proponents of evidence-based medicine have argued convincingly for applying this scientific method to medicine. However, the current methodological framework of the EBM movement has recently been called into question, especially in epidemiology and the philosophy of science. The debate has focused on whether the methodology of randomized controlled trials provides the best evidence available. This paper attempts to shift the focus of the debate by arguing that clinical reasoning involves a patchwork of evidential approaches and that the emphasis on evidence (...)
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  40. Against Robustness? Strategies to Support the Reliability of Scientific Results.Léna Soler - 2014 - International Studies in the Philosophy of Science 28 (2):203-215.
  41. Philosophie der Lebenswissenschaften.Susanne Bauer, Lara Huber, Marie I. Kaiser, Lara Keuck, Ulrich Krohs, Maria Kronfeldner, Peter McLaughlin, Kären Nickelson, Thomas Reydon, Neil Roughley, Christian Sachse, Marianne Schark, Georg Toepfer, Marcel Weber & Markus Wild - 2013 - Information Philosophie 4:14-27.
    This paper summarizes (in German) recent tendencies in the philosophy of the life sciences.
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  42. Seeing Things: The Philosophy of Reliable Observation.Robert Hudson - 2013 - Oxford and New York: Oxford University Press.
    In Seeing Things, Robert Hudson assesses a common way of arguing about observation reports called "robustness reasoning." Robustness reasoning claims that an observation report is more likely to be true if the report is produced by multiple, independent sources. Seeing Things argues that robustness reasoning lacks the special value it is often claimed to have. Hudson exposes key flaws in various popular philosophical defenses of robustness reasoning. This philosophical critique of robustness is extended by recounting five episodes in the history (...)
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  43. Common Method Variance & Bias dalam Penelitian Psikologis. Juneman - 2013 - Jurnal Pengukuran Psikologi Dan Pendidikan Indonesia 2 (5):364-381.
    The issue of common method variance and bias in Indonesia still has not gained much attention; even the terminology is less popular, except among psychometric enthusiasts and experts. In fact, the potential for common method variance and bias infiltrating in research results is very high, especially in studies that use a single method, a single source, and concurrent design, which are highly favored by psychological lecturers and researchers in Indonesia. This paper is a critical review, exposing the debate and serious (...)
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  44. Robustness and Sensitivity of Biological Models.Jani Raerinne - 2013 - Philosophical Studies 166 (2):285-303.
    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 robustness analysis, which they have inadequately distinguished (...)
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  45. On Algorithm and Robustness in a Non-Standard Sense.Sam Sanders - 2013 - In Hanne Andersen, Dennis Dieks, Wenceslao González, Thomas Uebel & Gregory Wheeler (eds.), New Challenges to Philosophy of Science. Springer Verlag. pp. 99--112.
  46. Robustness of Logical Depth.Luís Antunes, Andre Souto & Andreia Teixeira - 2012 - In S. Barry Cooper (ed.), How the World Computes. pp. 29--34.
  47. Nonuniformly Hyperbolic Cocycles: Admissibility and Robustness.Luis Barreira & Claudia Valls - 2012 - Annali della Scuola Normale Superiore di Pisa- Classe di Scienze 11 (3):545-564.
  48. The Elusive Basis of Inferential Robustness.James Justus - 2012 - Philosophy of Science 79 (5):795-807.
    Robustness concepts are often invoked to manage two obstacles confronting models of ecological systems: complexity and uncertainty. The intuitive idea is that any result derived from many idealized but credible models is thereby made more reliable or is better confirmed. An appropriate basis for this inference has proven elusive. Here, several representations of robustness analysis are vetted, paying particular attention to complex models of ecosystems and the global climate. The claim that robustness is itself confirmatory because robustness analysis employs a (...)
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  49. 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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  50. Values in Science.Ernan McMullin - 2012 - Zygon 47 (4):686-709.
    In this essay, which was his presidential address to the Philosophy of Science Association, Ernan McMullin argued that the watershed between “classic” philosophy of science and the “new” philosophy of science can best be understood by analyzing the change in our perception of the role played by values in science. He begins with some general remarks about the nature of value, goes on to explore some of the historical sources for the claim that judgement in science is value‐laden, and concludes (...)
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