Falsification and Refutation
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Truth, Rationality, and the Growth of Scientific Knowledge
....... CONJECTURES sense similar to that in which processes or things may be said to be parts of the world; that the world consists of facts in a sense in which it may be said to consist of (four dimensional) processes or of (three dimensional) things. They believe that, just as certain nouns are names of things, sentences are names of facts. And they sometimes even believe that sentences are some- thing like pictures of facts, or that they are projections of facts.7 But all this is mistaken. The fact that there is no elephant in this room is not one of the processes or parts ofthe world; nor is the fact that a hailstorm in Newfound- 10 land occurred exactIy I I I years after a tree collapsed in the New Zealand bush. Facts are something like a common product oflanguage and reality; they are reality pinned down by descriptive statements. They are like abstracts from TRUTH, RATIONALITY, AND THE a book, made in a language which is different from that of the original, and determined not only by the original book but nearly as much by the principles GROWTH OF SCIENTIFIC KNOWLEDGE of selection and by other methods of abstracting, and by the means of which the new language disposes. New linguistic means not only help us to describe 1. THE GROWTH OF KNOWLEDGE: THEORIES AND PROBLEMS new kinds of facts; in a way, they even create new kinds of facts. In a certain sense, these facts obviously existed before the new means were created which I were indispensable for their description; I say, 'obviously' because a calcula- tion, for example, ofthe movements of the planet Mercury of 100 years ago, MY aim in this lecture is to stress the significance of one particular aspect of carried out today with the help of the calculus of the theory of relativity, may science-its need to grow, or, if you like, its need to progress. -
Understanding the Progress of Science
Understanding the Progress of Science C. D. McCoy 30 May 2018 The central problem of epistemology has always been and still is the problem of the growth of knowledge. And the growth of knowledge can be studied best by studying the growth of scientific knowledge. —(Popper, 2002b, xix) Merely fact-minded sciences make merely fact-minded people. —(Husserl, 1970, 6) The growth of human knowledge is realized most dramatically in the growth of scientific knowledge. What we have come to know through science about the workings of our human bodies and the workings of heavenly bodies, among much else, astounds, especially in comparison to our accumulating knowledge of the commonplace and everyday. Impressed by the evident epistemic progress made by science, many philosophers during the 20th century thought that studying how scientific knowledge increases is a crucial task of epistemological inquiry, and, indeed, the progress of science has been a topic of considerable interest. Yet, eventually, late in the century, attention waned and for the most part shifted to other tasks. Recently, however, a provocative article by Bird has re-ignited philosophical interest in the topic of scientific progress (Bird, 2007). Bird criticizes what he takes to have been the most prominent accounts advanced in the 20th century and presses for what he views as a venerable but lately overlooked one. He claims that realist philosophers of science have often presumed that truth is the goal of science and progress to be properly characterized by an accu- mulation of truth or truths, and notes that anti-realists have often rejected truth as a goal of science and characterized progress in terms of, among other things, “problem-solving effectiveness.”1 He criticizes the former for overlooking the relevance of justification to progress and the latter for giving up on truth. -
A Coherentist Conception of Ad Hoc Hypotheses
A coherentist conception of ad hoc hypotheses Samuel Schindler [email protected] forthcoming in Studies in History and Philosophy of Science Abstract What does it mean for a hypothesis to be ad hoc? One prominent account has it that ad hoc hypotheses have no independent empirical support. Others have viewed ad hoc judgements as subjective. Here I critically review both of these views and defend my own Coherentist Conception of Ad hocness by working out its conceptual and descriptive attractions. Keywords: ad hoc; confirmation; independent support; novel success; coherence 1 Introduction It is widely agreed—amongst scientists and philosophers alike—that a good hypothesis ought not to be ad hoc. Consequently, a theory that requires ad hoc hypotheses in order to overcome empirical tests ought to be less acceptable for a rational agent than a theory that does without (or with fewer) ad hoc amendments. But what precisely does it mean for a hypothesis to be ad hoc? This is what this paper is about. Concept clarification is one of the central tasks of philosophy. Usually, it involves an explicandum and an explicatum, viz. a pre-analytic concept that is to be explicated and a concept which explicates this concept, respectively (Carnap 1950). For example, the concept TEMPERATURE explicates our pre- analytic concepts of WARM and COLD, and allows us to be much more precise and clear in the way we communicate with each other. In the case of ad hocness, the pre-analytic concept is something along the lines of “was introduced for the sole purpose of ‘saving’ a theory which faces observational anomalies”. -
The P–T Probability Framework for Semantic Communication, Falsification, Confirmation, and Bayesian Reasoning
philosophies Article The P–T Probability Framework for Semantic Communication, Falsification, Confirmation, and Bayesian Reasoning Chenguang Lu School of Computer Engineering and Applied Mathematics, Changsha University, Changsha 410003, China; [email protected] Received: 8 July 2020; Accepted: 16 September 2020; Published: 2 October 2020 Abstract: Many researchers want to unify probability and logic by defining logical probability or probabilistic logic reasonably. This paper tries to unify statistics and logic so that we can use both statistical probability and logical probability at the same time. For this purpose, this paper proposes the P–T probability framework, which is assembled with Shannon’s statistical probability framework for communication, Kolmogorov’s probability axioms for logical probability, and Zadeh’s membership functions used as truth functions. Two kinds of probabilities are connected by an extended Bayes’ theorem, with which we can convert a likelihood function and a truth function from one to another. Hence, we can train truth functions (in logic) by sampling distributions (in statistics). This probability framework was developed in the author’s long-term studies on semantic information, statistical learning, and color vision. This paper first proposes the P–T probability framework and explains different probabilities in it by its applications to semantic information theory. Then, this framework and the semantic information methods are applied to statistical learning, statistical mechanics, hypothesis evaluation (including falsification), confirmation, and Bayesian reasoning. Theoretical applications illustrate the reasonability and practicability of this framework. This framework is helpful for interpretable AI. To interpret neural networks, we need further study. Keywords: statistical probability; logical probability; semantic information; rate-distortion; Boltzmann distribution; falsification; verisimilitude; confirmation measure; Raven Paradox; Bayesian reasoning 1. -
Degrees of Riskiness, Falsifiability, and Truthlikeness. a Neo-Popperian
Degrees of riskiness, falsifiability, and truthlikeness. A neo-Popperian account applicable to probabilistic theories. Leander Vignero Sylvia Wenmackers [email protected] [email protected] KU Leuven, Institute of Philosophy, Centre for Logic and Philosophy of Science, Kardinaal Mercierplein 2 { bus 3200, 3000 Leuven, Belgium. July 7, 2021 (Forthcoming in Synthese.) Abstract In this paper, we take a fresh look at three Popperian concepts: riskiness, falsifiability, and truthlikeness (or verisimilitude) of scien- tific hypotheses or theories. First, we make explicit the dimensions that underlie the notion of riskiness. Secondly, we examine if and how degrees of falsifiability can be defined, and how they are related to var- ious dimensions of the concept of riskiness as well as the experimental context. Thirdly, we consider the relation of riskiness to (expected degrees of) truthlikeness. Throughout, we pay special attention to probabilistic theories and we offer a tentative, quantitative account of verisimilitude for probabilistic theories. \Modern logic, as I hope is now evident, has the effect of enlarging our abstract imagination, and providing an infinite number of possible hypotheses to be applied in the analysis of any complex fact." { Russell (1914, p. 58). A theory is falsifiable if it allows us to deduce predictions that can be compared to evidence, which according to our background knowledge could arXiv:2107.03772v1 [physics.hist-ph] 8 Jul 2021 show the prediction | and hence the theory | to be false. In his defense of falsifiability as a demarcation criterion, Popper has stressed the importance of bold, risky claims that can be tested, for they allow science to make progress. -
What Is Scientific Progress?
What is Scientific Progress? 1 Introduction What is scientific progress? The answer is simple. Science (or some particular scientific field or theory) makes progress precisely when it shows the accumulation of scientific knowledge; an episode in science is progressive when at the end of the episode there is more knowledge than at the beginning. This simple, cumulative conception of scientific progress is not original; indeed it has a venerable history.1 Yet philosophers of science have almost entirely ignored this conception, at least since it was condemned by Kuhn and others in the 1960s. Even in the realist reaction against positivism and relativism the cumulative conception has not been rehabilitated. Realists have typically sought an account of progress in terms of increasing verisimilitude (truth-likeness, approximate truth) rather than increasing knowledge. In this paper I will be comparing three approaches to characterising scientific progress: (i) the epistemic approach, (ii) the semantic approach, and (iii) the functional-internalist approach. The epistemic approach takes knowledge to be the concept we need in order to understand what progress is. (The only version of the epistemic approach I shall consider is the cumulative knowledge account I have already advertised.) The semantic approach takes truth (or verisimilitude) to be the central concept is defining progress. And the functional-internalist holds that progress is made when a scientific development succeeds in fulfilling a certain function (such as solving a scientific problem), where that function is understood in such a way that the scientific practitioners are themselves in a position to judge whether the function has been fulfilled. -
Doctoraat FINAAL .Pdf
Here be dragons Here Exploring the hinterland of science Maarten Boudry Here be dragons Exploring the hinterland of science Maarten Boudry ISBN978-90-7083-018-2 Proefschrift voorgedragen tot het bekomen van de graad van Doctor in de Wijsbegeerte Promotor: Prof. dr. Johan Braeckman Supervisor Prof. dr. Johan Braeckman Wijsbegeerte en moraalwetenschap Dean Prof. dr. Freddy Mortier Rector Prof. dr. Paul Van Cauwenberghe Nederlandse vertaling: Hic sunt dracones. Een filosofische verkenning van pseudowetenschap en randwetenschap Cover: The image on the front cover is an excerpt of a map by the Flemish cartographer Abraham Ortelius, originally published in Theatrum Orbis Terrarum (1570). ISBN: 978-90-7083-018-2 The author and the promoter give the authorisation to consult and to copy parts of this work for personal use only. Every other use is subject to the copyright laws. Permission to reproduce any material contained in this work should be obtained from the author. Faculty of Arts & Humanities Maarten Boudry Here be Dragons Exploring the Hinterland of Science Proefschrift voorgedragen tot het bekomen van de graad van Doctor in de Wijsbegeerte 2011 Acknowledgements This dissertation could not have been written without the invaluable help of a number of people (a philosopher cannot help but thinking of them as a set of individually necessary and jointly sufficient conditions). Different parts of this work have greatly benefited from stimulating discussions with many colleagues and friends, among whom Barbara Forrest, John Teehan, Herman Philipse, Helen De Cruz, Taner Edis, Nicholas Humphrey, Geerdt Magiels, Bart Klink, Glenn Branch, Larry Moran, Jerry Coyne, Michael Ruse, Steve Zara, Amber Griffioen, Johan De Smedt, Lien Van Speybroeck, and Evan Fales. -
Why Advocate Pancritical Rationalism?
Why Advocate Pancritical Rationalism? Darrell P. Rowbottom and Otávio Bueno Abstract This paper provides a rationale for advocating pancritical rationalism. First, it argues that the advocate of critical rationalism may accept (but not be internally justified in accepting) that there is ‘justification’ in an externalist sense, specifically that certain procedures can track truth, and suggest that this recognition should inform practice; that one should try to determine which sources and methods are appropriate for various aspects of inquiry, and to what extent they are. Second, it argues that if there is external justification, then a critical rationalist is better off than a dogmatist from an evolutionary perspective. Introduction Consider two individuals. One believes h dogmatically, and will never give it up. The other believes h just as strongly (i.e., has the same synchronic degree of belief), but is prepared to reconsider that belief in the light of criticism. Is the latter in a better position than the former? From an ordinary language point of view, it seems as if the advocate of (comprehensively) critical rationalism thinks so; and therefore also believes that the latter is ‘justified’ in believing h in a manner that the former is not. Why else recommend the critical attitude? A possible answer is that the former individual is incapable of learning (insofar as h is concerned), whereas the latter clearly is so capable. But if we accept that one can learn something that is false, as (comprehensively) critical rationalists tend to, then this seems insufficient. Learning could lead one to false beliefs, rather than just true ones. -
128 What Social Scientists Don't Understand
In D. W. Fiske and R. A. Shweder (Eds.) Metatheory in social science: Pluralisms and subjectivities. Chicago: University of 128 Chicago Press, 1986. (Chapter 14, pp.315-338) What Social Scientists Don’t Understand P. E. Meehl In the papers prepared for the conference on which this book is based and in the discussion, there were some matters almost universally agreed upon but repeated unnecessarily. Then there were some things that should have been agreed upon but were not. Finally, there were matters that were not agreed upon that needed more intensive examination—matters playing a central role in the philosophy of the social sciences and in the present intellectual gloominess that seems to prevail in all of the disciplines represented. THINGS GENERALLY AGREED ON FROM THE BEGINNING It was agreed that logical positivism and strict operationism won’t wash. Logical positivism, in anything like the sense of Vienna in the late twenties turned out not to be logically defensible, or even rigorously formulatable, by its adherents. It is epistemologically unsound from a variety of viewpoints (including ordinary-language analysis), it is not an accurate picture of the structure of advanced sciences such as physics, and it is grossly inadequate as a reconstruction of empirical history of science. So it is dead. All old surviving logical positivists agree, including my friend and teacher Feigl, who invented the phrase “logical positivism” and was the first to introduce the approach in the United States in 1931. The last remaining defender of anything like logical positivism was Gustav Bergmann, who ceased to do so by the late 1940s. -
Ad Hoc Hypotheses and the Monsters Within
Chapter 18 Ad Hoc Hypotheses and the Monsters Within Ioannis Votsis Abstract Science is increasingly becoming automated. Tasks yet to be fully automated include the conjecturing, modifying, extending and testing of hypotheses. At present scientists have an array of methods to help them carry out those tasks. These range from the well-articulated, formal and unexceptional rules to the semi- articulated and variously understood rules-of-thumb and intuitive hunches. If we are to hand over at least some of the aforementioned tasks to machines, we need to clarify, refine and make formal, not to mention computable, even the more obscure of the methods scientists successfully employ in their inquiries. The focus of this essay is one such less-than-transparent methodological rule. I am here referring to the rule that ad hoc hypotheses ought to be spurned. This essay begins with a brief examination of some notable conceptions of ad hoc-ness in the philosophical literature. It is pointed out that there is a general problem afflicting most such conceptions, namely the intuitive judgments that are supposed to motivate them are not universally shared. Instead of getting bogged down in what ad hoc-ness exactly means, I shift the focus of the analysis to one undesirable feature often present in alleged cases of ad hoc-ness. I call this feature the ‘monstrousness’ of a hypothesis. A fully articulated formal account of this feature is presented by specifying what it is about the internal constitution of a hypothesis that makes it monstrous. Using this account, a monstrousness measure is then proposed and somewhat sketchily compared with the minimum description length approach. -
Four Examples of Pseudoscience
Four Examples of Pseudoscience Marcos Villavicencio Tenerife, Canarias, Spain E-mail address: [email protected] ORCID iD: 0000-0001-6700-4872 January 2020 Abstract A relevant issue in the philosophy of science is the demarcation problem: how to distinguish science from nonscience, and, more specifically, science from pseudoscience. Sometimes, the demarcation problem is debated from a very general perspective, proposing demarcation criteria to separate science from pseudoscience, but without discussing any specific field in detail. This article aims to focus the demarcation problem on particular disciplines or theories. After considering a set of demarcation criteria, four pseudosciences are examined: psychoanalysis, speculative evolutionary psychology, universal grammar, and string theory. It is concluded that these theoretical frameworks do not meet the requirements to be considered genuinely scientific. Keywords Demarcation Problem · Pseudoscience · Psychoanalysis · Evolutionary psychology · Universal grammar · String theory 1 Introduction The demarcation problem is the issue of how to differentiate science from nonscience in general and pseudoscience in particular. Even though expressions such as “demarcation problem” or “pseudoscience” were still not used, some consider that an early interest for demarcation existed as far back as the time of ancient Greece, when Aristotle separated episteme (scientific knowledge) from mere doxa (opinion), holding that apodictic certainty is the basis of science (Laudan 1983, p. 112). Nowadays, the issue of demarcation continues being discussed. Certainly, demarcating science from pseudoscience is not a topic of exclusive philosophical interest. Scientists and members of skeptical organizations such as the Committee for Scientific Inquiry also deal with this crucial theme. The issue of how to recognize pseudoscience not only affects academia. -
Pre-Service Science Teachers' Discrimination Level Of
ORIGINAL ARTICLE Pre-service Science Teachers’ Discrimination Level of Science and Pseudoscience Murat Berat Uçar1* Elvan Sahin2 1Department of Mathematics and Science Education, M. R. Faculty of Education, Kilis 7 Aralik University, Kilis, Turkey, 2Department of Mathematics and Science Education, Faculty of Education, Middle East Technical University, Ankara, Turkey *Corresponding author: [email protected] ABSTRACT This quantitative study aimed to examine Turkish pre-service science teachers’ beliefs regarding the demarcating between science and pseudoscience. Participants completed the Science and Pseudoscience Distinction Scale. Data collected from the 123 pre-service science teachers were examined based on the dimensions of the instrument, namely science as a process of inquiry (SCI), demarcating between science and pseudoscience, and pseudoscientific beliefs (PS). This study found that these pre-service science teachers generally did not hold strong beliefs on distinguishing science and pseudoscience. Their beliefs regarding SCI were not highly favorable. Moreover, this study revealed that they had some PS. Considering the role of gender and year in the program, the results of two-way MANOVA indicated that there was no statistically significant difference on the related belief constructs for these pre-service science teachers. Thus, the present study intended to shed light on pre-service science teachers’ mindsets about identifying accurate scientific information rather than pseudoscientific confusions that could aid preparing scientifically