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  1. William W. Agresti & Mark S. Mayzner (1978). Robustness of the Dynamic Visual Movement Effect. Bulletin of the Psychonomic Society 12 (2):147-148.
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  2. Luís Antunes, Andre Souto & Andreia Teixeira (2012). Robustness of Logical Depth. In S. Barry Cooper (ed.), How the World Computes. 29--34.
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  3. D. J. Balestra (1979). Non-Falsifiability: An Inductivist Perspective. International Logic Review 19:118.
  4. Sorin Bangu (2006). Pythagorean Heuristic in Physics. Perspectives on Science 14 (4):387-416.
    : Some of the great physicists' belief in the existence of a connection between the aesthetical features of a theory (such as beauty and simplicity) and its truth is still one of the most intriguing issues in the aesthetics of science. In this paper I explore the philosophical credibility of a version of this thesis, focusing on the connection between the mathematical beauty and simplicity of a theory and its truth. I discuss a heuristic interpretation of this thesis, attempting to (...)
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  5. Cameron Buckner (2013). Morgan's Canon, Meet Hume's Dictum: Avoiding Anthropofabulation in Cross-Species Comparisons. Biology and Philosophy 28 (5):853-871.
    How should we determine the distribution of psychological traits—such as Theory of Mind, episodic memory, and metacognition—throughout the Animal kingdom? Researchers have long worried about the distorting effects of anthropomorphic bias on this comparative project. A purported corrective against this bias was offered as a cornerstone of comparative psychology by C. Lloyd Morgan in his famous “Canon”. Also dangerous, however, is a distinct bias that loads the deck against animal mentality: our tendency to tie the competence criteria for cognitive capacities (...)
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  6. Mario Bunge (1965). The Myth of Simplicity: Problems of Scientific Philosophy. Philosophical Review 74 (3):402-404.
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  7. Mario Bunge (1961). The Weight of Simplicity in the Construction and Assaying of Scientific Theories. Philosophy of Science 28 (2):120-149.
  8. H. G. Callaway (2014). Abduction, Competing Models and the Virtues of Hypotheses. In Lorenzo Magnani (ed.), (2014) Model-Based Reasoning in Science and Technology. Springer 263-280.
    This paper focuses on abduction as explicit or readily formulatable inference to possible explanatory hypotheses--as contrasted with inference to conceptual innovations or abductive logic as a cycle of hypotheses, deduction of consequences and inductive testing. Inference to an explanation is often a matter of projection or extrapolation of elements of accepted theory for the solution of outstanding problems in particular domains of inquiry. I say "projections or extrapolation" of accepted theory, but I mean to point to something broader and suggest (...)
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  9. James D. Church & Edward L. Wike (1976). The Robustness of Homogeneity of Variance Tests for Asymmetric Distributions: A Monte Carlo Study. Bulletin of the Psychonomic Society 7 (5):417-420.
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  10. Mark Colyvan (2008). The Ontological Commitments of Inconsistent Theories. Philosophical Studies 141 (1):115 - 123.
    In this paper I present an argument for belief in inconsistent objects. The argument relies on a particular, plausible version of scientific realism, and the fact that often our best scientific theories are inconsistent. It is not clear what to make of this argument. Is it a reductio of the version of scientific realism under consideration? If it is, what are the alternatives? Should we just accept the conclusion? I will argue (rather tentatively and suitably qualified) for a positive answer (...)
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  11. Richard Dawkins (1998). Unweaving the Rainbow: Science, Delusion, and the Appetite for Wonder. Houghton Mifflin.
    Did Newton "unweave the rainbow" by reducing it to its prismatic colors, as Keats contended? Did he, in other words, diminish beauty? Far from it, says Dawkins--Newton's unweaving is the key too much of modern astronomy and to the breathtaking poetry of modern cosmology. Mysteries don't lose their poetry because they are solved: the solution often is more beautiful than the puzzle, uncovering deeper mystery. (The Keats who spoke of "unweaving the rainbow" was a very young man, Dawkins reminds us.) (...)
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  12. Craig Dilworth (2012). Simplicity: A Meta-Metaphysics. Lexington Books.
    Simplicity provides a new logic with which to approach intellectual situations. Using the simplicity way of thinking as a tool helps clarify intellectual standpoints and conceptually problematic situations in philosophy, mathematics and physics.
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  13. Arthur Anthony Dobos (1972). Simplicity in Scientific Theory: A Case History Approach. Dissertation, Saint Louis University
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  14. Heather Douglas (2014). The Value of Cognitive Values. Philosophy of Science 80 (5):796-806.
    Traditionally, cognitive values have been thought of as a collective pool of considerations in science that frequently trade against each other. I argue here that a finer-grained account of the value of cognitive values can help reduce such tensions. I separate the values into groups, minimal epistemic criteria, pragmatic considerations, and genuine epistemic assurance, based in part on the distinction between values that describe theories per se and values that describe theory-evidence relationships. This allows us to clarify why these values (...)
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  15. Malcolm Forster, Chapter 3: Simplicity and Unification in Model Selection.
    This chapter examines four solutions to the problem of many models, and finds some fault or limitation with all of them except the last. The first is the naïve empiricist view that best model is the one that best fits the data. The second is based on Popper’s falsificationism. The third approach is to compare models on the basis of some kind of trade off between fit and simplicity. The fourth is the most powerful: Cross validation testing.
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  16. Malcolm Forster, Discussion: Unification and Predictive Accuracy.
    Wayne Myrvold (2003) has captured an important feature of unified theories, and he has done so in Bayesian terms. What is not clear is whether the virtue of such unification is most clearly understood in terms of Bayesian confirmation. I argue that the virtue of such unification is better understood in terms of other truth-related virtues such as predictive accuracy.
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  17. Kenneth S. Friedman (1972). Empirical Simplicity as Testability. British Journal for the Philosophy of Science 23 (1):25-33.
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  18. L. C. G. (1963). The Myth of Simplicity: Problems of Scientific Philosophy. [REVIEW] Review of Metaphysics 17 (1):143-143.
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  19. Ian Glynn (2010). Elegance in Science: The Beauty of Simplicity. Oxford University Press.
    The meaning of elegance -- Celestial mechanics : the route to Newton -- Bringing the heavens down to earth -- So what is heat? -- Elegance and electricity -- Throwing light on light : with the story of Thomas Young -- How do nerves work? -- Information handling in the brain -- The genetic code -- Epilogue : a cautionary tale.
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  20. I. J. Good (1968). Corroboration, Explanation, Evolving Probability, Simplicity and a Sharpened Razor. British Journal for the Philosophy of Science 19 (2):123-143.
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  21. Lars Peter Hansen & Thomas J. Sargent (2007). Robustness. Princeton University Press.
    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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  22. Katherine Hawley (1997). Review of Beauty and Revolution in Science. [REVIEW] British Journal for the Philosophy of Science 48 (2):297-299.
    Review of Beauty and Revolution in Science, by JW McAllister.
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  23. C. Held (2011). Truth Does Not Explain Predictive Success. Analysis 71 (2):232-234.
    Laudan famously argued that neither truth nor approximate truth can be part of an explanation of a scientific theory's predictive success because in the history of science there were theories that enjoyed some limited success but now are considered outright false. The power of his argument lay in the many historic examples he listed . Realists have disputed that all theories on Laudan's list can be regarded as predictively successful but let's suppose momentarily that at least some exist that support (...)
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  24. David Henderson, Rethinking the Connection Between Truth-Conducivity and Justification.
    Contents/Links I. The Referentialist's Objection and the Issues it Raises II. From Uses of Descriptions to Aspects of Concepts III. A Straightforward Understanding IV. A More Sophisticated Understanding V. What is Attributively Associated with "Justification"?
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  25. Dan Hicks (2014). A New Direction for Science and Values. Synthese 191 (14):3271-95.
    The controversy over the old ideal of “value-free science” has cooled significantly over the past decade. Many philosophers of science now agree that even ethical and political values may play a substantial role in all aspects of scientific inquiry. Consequently, in the last few years, work in science and values has become more specific: Which values may influence science, and in which ways? Or, how do we distinguish illegitimate from illegitimate kinds of influence? In this paper, I argue that this (...)
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  26. James Justus (2012). The Elusive Basis of Inferential Robustness. Philosophy of Science 79 (5):795-807.
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  27. Kevin Kelly, Simplicity, Truth, and the Unending Game of Science.
    This paper presents a new explanation of how preferring the simplest theory compatible with experience assists one in finding the true answer to a scientific question when the answers are theories or models. Inquiry is portrayed as an unending game between science and nature in which the scientist aims to converge to the true theory on the basis of accumulating information. Simplicity is a topological invariant reflecting sequences of theory choices that nature can force an arbitrary, convergent scientist to produce. (...)
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  28. Kevin T. Kelly, Simplicity, Truth, and Probability.
    Simplicity has long been recognized as an apparent mark of truth in science, but it is difficult to explain why simplicity should be accorded such weight. This chapter examines some standard, statistical explanations of the role of simplicity in scientific method and argues that none of them explains, without circularity, how a reliance on simplicity could be conducive to finding true models or theories. The discussion then turns to a less familiar approach that does explain, in a sense, the elusive (...)
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  29. Andre Kukla (1994). Non-Empirical Theoretical Virtues and the Argument From Underdetermination. Erkenntnis 41 (2):157 - 170.
    The antirealist argument from the underdetermination of theories by data relies on the premise that the empirical content of a theory is the only determinant of its belief-worthiness (premise NN). Several authors have claimed that the antirealist cannot endorse NN, on pain of internal inconsistency. I concede this point. Nevertheless, this refutation of the underdetermination argument fails because there are weaker substitutes for NN that will serve just as well as a premise to the argument. On the other hand, antirealists (...)
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  30. Jaakko Kuorikoski & Aki Lehtinen (2009). Incredible Worlds, Credible Results. Erkenntnis 70 (1):119 - 131.
    Robert Sugden argues that robustness analysis cannot play an epistemic role in grounding model-world relationships because the procedure is only a matter of comparing models with each other. We posit that this argument is based on a view of models as being surrogate systems in too literal a sense. In contrast, the epistemic importance of robustness analysis is easy to explicate if modelling is viewed as extended cognition, as inference from assumptions to conclusions. Robustness analysis is about assessing the reliability (...)
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  31. Chiara Lisciandra (2015). Robustness Analysis Versus Reliable Process Reasoning. 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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  32. Helen E. Longino (1995). Gender, Politics, and the Theoretical Virtues. Synthese 104 (3):383 - 397.
    Traits like simplicity and explanatory power have traditionally been treated as values internal to the sciences, constitutive rather than contextual. As such they are cognitive virtues. This essay contrasts a traditional set of such virtues with a set of alternative virtues drawn from feminist writings about the sciences. In certain theoretical contexts, the only reasons for preferring a traditional or an alternative virtue are socio-political. This undermines the notion that the traditional virtues can be considered purely cognitive.
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  33. Sebastian Lutz & Stephan Hartmann (2010). Conventional and Objective Invariance: Debs and Redhead on Symmetry. [REVIEW] Metascience 19:15-23.
    This review is a critical discussion of three main claims in Debs and Redhead’s thought-provoking book Objectivity, Invariance, and Convention. These claims are: (i) Social acts impinge upon formal aspects of scientific representation; (ii) symmetries introduce the need for conventional choice; (iii) perspectival symmetry is a necessary and sufficient condition for objectivity, while symmetry simpliciter fails to be necessary.
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  34. Adolfas Mackonis (2013). Inference to the Best Explanation, Coherence and Other Explanatory Virtues. Synthese 190 (6):975-995.
    This article generalizes the explanationist account of inference to the best explanation. It draws a clear distinction between IBE and abduction and presents abduction as the first step of IBE. The second step amounts to the evaluation of explanatory power, which consist in the degree of explanatory virtues that a hypothesis exhibits. Moreover, even though coherence is the most often cited explanatory virtue, on pain of circularity, it should not be treated as one of the explanatory virtues. Rather, coherence should (...)
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  35. Brian Paul MacPherson, Simplicity and Falsifiability a Critical Examination of Karl Popper's Stipulative Definition of Simplicity.
    Source: Masterss International, Volume: 40-07, page:. Thesis --University of Windsor, 1982.
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  36. James W. McAllister (1996). Beauty & Revolution in Science. Cornell University Press.
  37. James W. McAllister (1991). The Simplicity of Theories: Its Degree and Form. [REVIEW] Journal for General Philosophy of Science / Zeitschrift für Allgemeine Wissenschaftstheorie 22 (1):1-14.
    Almost all commentators acknowledge that among the grounds on which scientists perform theory-choices are criteria of simplicity. In general, simplicity is regarded either as only a logico-empirical quality of a theory, diagnostic of the theory's future predictive success, or as a purely aesthetic or otherwise extra-empirical property of it. This paper attempts to demonstrate that the simplicity-criteria applied in scientific practice include both a logico-empirical and a quasi-aesthetic criterion: to conflate these in an account of scientists' theory-choice is to court (...)
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  38. James W. Mcallister (1989). Truth and Beauty in Scientific Reason. Synthese 78 (1):25 - 51.
    A rationalist and realist model of scientific revolutions will be constructed by reference to two categories of criteria of theory-evaluation, denominated indicators of truth and of beauty. Whereas indicators of truth are formulateda priori and thus unite science in the pursuit of verisimilitude, aesthetic criteria are inductive constructs which lag behind the progression of theories in truthlikeness. Revolutions occur when the evaluative divergence between the two categories of criteria proves too wide to be recomposed or overlooked. This model of revolutions (...)
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  39. Kevin Meeker (2006). Pluralism, Exclusivism, and the Theoretical Virtues. Religious Studies 42 (2):193-206.
    This paper argues that John Hick's commitment to the moral principle of altruism undermines his pluralistic claim that all of the major world religions are equally efficacious from a soteriological perspective. This argument is placed in a context of a discussion evaluating the theoretical virtues of various hypotheses about religious diversity. (Published Online April 7 2006).
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  40. David Marshall Miller (2013). Seeing and Believing: Galileo, Aristotelians, and the Mountains on the Moon. In Daniel De Simone & John Hessler (eds.), The Starry Messenger. Levenger Press 131-145.
  41. Michael Morreau (2013). Mr. Fit, Mr. Simplicity and Mr. Scope: From Social Choice to Theory Choice. Erkenntnis (S6):1-16.
    An analogue of Arrow’s theorem has been thought to limit the possibilities for multi-criterial theory choice. Here, an example drawn from Toy Science, a model of theories and choice criteria, suggests that it does not. Arrow’s assumption that domains are unrestricted is inappropriate in connection with theory choice in Toy Science. There are, however, variants of Arrow’s theorem that do not require an unrestricted domain. They require instead that domains are, in a technical sense, ‘rich’. Since there are rich domains (...)
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  42. Margaret Morrison (1988). Reduction and Realism. PSA: Proceedings of the Biennial Meeting of the Philosophy of Science Association 1988:286 - 293.
    In The Foundations of Space-Time Theories Friedman argues for a literal realistic interpretation about theoretical structures that participate in theory unification. His account of the relationship between observational and theoretical structure is characterized as that of model to submodel and involves a reductivist strategy that allows for the conjunction of certain theoretical structures with other structures which, taken together, form a truly unified theory. Friedman criticizes the representational account for its failure to allow for a literal interpretation and conjunction of (...)
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  43. Wayne C. Myrvold & William L. Harper (2002). Model Selection, Simplicity, and Scientific Inference. Proceedings of the Philosophy of Science Association 2002 (3):S135-S149.
    The Akaike Information Criterion can be a valuable tool of scientific inference. This statistic, or any other statistical method for that matter, cannot, however, be the whole of scientific methodology. In this paper some of the limitations of Akaikean statistical methods are discussed. It is argued that the full import of empirical evidence is realized only by adopting a richer ideal of empirical success than predictive accuracy, and that the ability of a theory to turn phenomena into accurate, agreeing measurements (...)
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  44. Edmund Nierlich (2005). An “Empirical Science” of Literature. Journal for General Philosophy of Science / Zeitschrift für Allgemeine Wissenschaftstheorie 36 (2):351 - 376.
    In this article the outlines are sketched of an empirical science of literature as close as possible to the model of the natural sciences. This raises the question of what the standards of an empirical science in the strictest sense should generally be. Practical relevance of its results soon turns up as the fundamental condition for an explanatory empirical science, if the ideology of nearing an empirical truth is no longer accepted and a mere pragmatic justification rejected as its insufficient (...)
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  45. Ilkka Niiniluoto (2008). Unification and Abductive Confirmation. Proceedings of the Xxii World Congress of Philosophy 43:151-156.
    According to the traditional requirement, formulated already by William Whewell in his account of the “consilience of inductions” in 1840, an explanatory scientific theory should be independently testable by new kinds of phenomena. A good theory should have unifying power in the sense that it explains and predicts several mutually independent phenomena. This paper studies the prospects of Bayesianism to motivate this kind of unification criterion for abductive confirmation.
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  46. Graham Oddie (2013). The Content, Consequence and Likeness Approaches to Verisimilitude: Compatibility, Trivialization, and Underdetermination. Synthese 190 (9):1647-1687.
    Theories of verisimilitude have routinely been classified into two rival camps—the content approach and the likeness approach—and these appear to be motivated by very different sets of data and principles. The question thus naturally arises as to whether these approaches can be fruitfully combined. Recently Zwart and Franssen (Synthese 158(1):75–92, 2007) have offered precise analyses of the content and likeness approaches, and shown that given these analyses any attempt to meld content and likeness orderings violates some basic desiderata. Unfortunately their (...)
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  47. H. R. Post (1960). Simplicity in Scientific Theories. British Journal for the Philosophy of Science 11 (41):32-41.
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  48. Nicholas Rescher (1989). Aesthetic Factors in Natural Science. Upa.
    This collection of essays originated from an interdisciplinary conference held at the University of Pittsburgh. Contents: Aesthetic Factors in Natural Science, by Nicholas Rescher; Three Arguments against Simplicity, by Kristin Shrader-Frechette; Simplicity and the Aesthetics of Explanation, by Joseph C. Pitt; Simplicity as an Epistemic Virtue: The View from the Neuronal Level, by Paul M. Churchland; Taming a Regulative Principle: From Kant to Schlick, by Matti Sintonen; Simplicity and Distinctness: The Limits of Referential Semantics, by Ulrich Majer; The Aesthetics of (...)
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  49. Samuel A. Richmond (1996). A Simplification of the Theory of Simplicity. Synthese 107 (3):373 - 393.
    Nelson Goodman has constructed two theories of simplicity: one of predicates; one of hypotheses. I offer a simpler theory by generalization and abstraction from his. Generalization comes by dropping special conditions Goodman imposes on which unexcluded extensions count as complicating and which excluded extensions count as simplifying. Abstraction is achieved by counting only nonisomorphic models and subinterpretations. The new theory takes into account all the hypotheses of a theory in assessing its complexity, whether they were projected prior to, or result (...)
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  50. Howard L. Rolston (1976). A Note of Simplicity as a Principle for Evaluating Rival Scientific Theories. Philosophy of Science 43 (3):438-440.
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