Induction and Epistemological Naturalism
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Would ''Direct Realism'' Resolve the Classical Problem of Induction?
NOU^S 38:2 (2004) 197–232 Would ‘‘Direct Realism’’ Resolve the Classical Problem of Induction? MARC LANGE University of North Carolina at Chapel Hill I Recently, there has been a modest resurgence of interest in the ‘‘Humean’’ problem of induction. For several decades following the recognized failure of Strawsonian ‘‘ordinary-language’’ dissolutions and of Wesley Salmon’s elaboration of Reichenbach’s pragmatic vindication of induction, work on the problem of induction languished. Attention turned instead toward con- firmation theory, as philosophers sensibly tried to understand precisely what it is that a justification of induction should aim to justify. Now, however, in light of Bayesian confirmation theory and other developments in epistemology, several philosophers have begun to reconsider the classical problem of induction. In section 2, I shall review a few of these developments. Though some of them will turn out to be unilluminating, others will profitably suggest that we not meet inductive scepticism by trying to justify some alleged general principle of ampliative reasoning. Accordingly, in section 3, I shall examine how the problem of induction arises in the context of one particular ‘‘inductive leap’’: the confirmation, most famously by Henrietta Leavitt and Harlow Shapley about a century ago, that a period-luminosity relation governs all Cepheid variable stars. This is a good example for the inductive sceptic’s purposes, since it is difficult to see how the sparse background knowledge available at the time could have entitled stellar astronomers to regard their observations as justifying this grand inductive generalization. I shall argue that the observation reports that confirmed the Cepheid period- luminosity law were themselves ‘‘thick’’ with expectations regarding as yet unknown laws of nature. -
1.2. INDUCTIVE REASONING Much Mathematical Discovery Starts with Inductive Reasoning – the Process of Reaching General Conclus
1.2. INDUCTIVE REASONING Much mathematical discovery starts with inductive reasoning – the process of reaching general conclusions, called conjectures, through the examination of particular cases and the recognition of patterns. These conjectures are then more formally proved using deductive methods, which will be discussed in the next section. Below we look at three examples that use inductive reasoning. Number Patterns Suppose you had to predict the sixth number in the following sequence: 1, -3, 6, -10, 15, ? How would you proceed with such a question? The trick, it seems, is to discern a specific pattern in the given sequence of numbers. This kind of approach is a classic example of inductive reasoning. By identifying a rule that generates all five numbers in this sequence, your hope is to establish a pattern and be in a position to predict the sixth number with confidence. So can you do it? Try to work out this number before continuing. One fact is immediately clear: the numbers alternate sign from positive to negative. We thus expect the answer to be a negative number since it follows 15, a positive number. On closer inspection, we also realize that the difference between the magnitude (or absolute value) of successive numbers increases by 1 each time: 3 – 1 = 2 6 – 3 = 3 10 – 6 = 4 15 – 10 = 5 … We have then found the rule we sought for generating the next number in this sequence. The sixth number should be -21 since the difference between 15 and 21 is 6 and we had already determined that the answer should be negative. -
There Is No Pure Empirical Reasoning
There Is No Pure Empirical Reasoning 1. Empiricism and the Question of Empirical Reasons Empiricism may be defined as the view there is no a priori justification for any synthetic claim. Critics object that empiricism cannot account for all the kinds of knowledge we seem to possess, such as moral knowledge, metaphysical knowledge, mathematical knowledge, and modal knowledge.1 In some cases, empiricists try to account for these types of knowledge; in other cases, they shrug off the objections, happily concluding, for example, that there is no moral knowledge, or that there is no metaphysical knowledge.2 But empiricism cannot shrug off just any type of knowledge; to be minimally plausible, empiricism must, for example, at least be able to account for paradigm instances of empirical knowledge, including especially scientific knowledge. Empirical knowledge can be divided into three categories: (a) knowledge by direct observation; (b) knowledge that is deductively inferred from observations; and (c) knowledge that is non-deductively inferred from observations, including knowledge arrived at by induction and inference to the best explanation. Category (c) includes all scientific knowledge. This category is of particular import to empiricists, many of whom take scientific knowledge as a sort of paradigm for knowledge in general; indeed, this forms a central source of motivation for empiricism.3 Thus, if there is any kind of knowledge that empiricists need to be able to account for, it is knowledge of type (c). I use the term “empirical reasoning” to refer to the reasoning involved in acquiring this type of knowledge – that is, to any instance of reasoning in which (i) the premises are justified directly by observation, (ii) the reasoning is non- deductive, and (iii) the reasoning provides adequate justification for the conclusion. -
A Philosophical Treatise on the Connection of Scientific Reasoning
mathematics Review A Philosophical Treatise on the Connection of Scientific Reasoning with Fuzzy Logic Evangelos Athanassopoulos 1 and Michael Gr. Voskoglou 2,* 1 Independent Researcher, Giannakopoulou 39, 27300 Gastouni, Greece; [email protected] 2 Department of Applied Mathematics, Graduate Technological Educational Institute of Western Greece, 22334 Patras, Greece * Correspondence: [email protected] Received: 4 May 2020; Accepted: 19 May 2020; Published:1 June 2020 Abstract: The present article studies the connection of scientific reasoning with fuzzy logic. Induction and deduction are the two main types of human reasoning. Although deduction is the basis of the scientific method, almost all the scientific progress (with pure mathematics being probably the unique exception) has its roots to inductive reasoning. Fuzzy logic gives to the disdainful by the classical/bivalent logic induction its proper place and importance as a fundamental component of the scientific reasoning. The error of induction is transferred to deductive reasoning through its premises. Consequently, although deduction is always a valid process, it is not an infallible method. Thus, there is a need of quantifying the degree of truth not only of the inductive, but also of the deductive arguments. In the former case, probability and statistics and of course fuzzy logic in cases of imprecision are the tools available for this purpose. In the latter case, the Bayesian probabilities play a dominant role. As many specialists argue nowadays, the whole science could be viewed as a Bayesian process. A timely example, concerning the validity of the viruses’ tests, is presented, illustrating the importance of the Bayesian processes for scientific reasoning. -
The Intrinsic Probability of Grand Explanatory Theories
Faith and Philosophy: Journal of the Society of Christian Philosophers Volume 37 Issue 4 Article 3 10-1-2020 The Intrinsic Probability of Grand Explanatory Theories Ted Poston Follow this and additional works at: https://place.asburyseminary.edu/faithandphilosophy Recommended Citation Poston, Ted (2020) "The Intrinsic Probability of Grand Explanatory Theories," Faith and Philosophy: Journal of the Society of Christian Philosophers: Vol. 37 : Iss. 4 , Article 3. DOI: 10.37977/faithphil.2020.37.4.3 Available at: https://place.asburyseminary.edu/faithandphilosophy/vol37/iss4/3 This Article is brought to you for free and open access by the Journals at ePLACE: preserving, learning, and creative exchange. It has been accepted for inclusion in Faith and Philosophy: Journal of the Society of Christian Philosophers by an authorized editor of ePLACE: preserving, learning, and creative exchange. applyparastyle "fig//caption/p[1]" parastyle "FigCapt" applyparastyle "fig" parastyle "Figure" AQ1–AQ5 THE INTRINSIC PROBABILITY OF GRAND EXPLANATORY THEORIES Ted Poston This paper articulates a way to ground a relatively high prior probability for grand explanatory theories apart from an appeal to simplicity. I explore the possibility of enumerating the space of plausible grand theories of the universe by using the explanatory properties of possible views to limit the number of plausible theories. I motivate this alternative grounding by showing that Swinburne’s appeal to simplicity is problematic along several dimensions. I then argue that there are three plausible grand views—theism, atheism, and axiarchism—which satisfy explanatory requirements for plau- sibility. Other possible views lack the explanatory virtue of these three theo- ries. Consequently, this explanatory grounding provides a way of securing a nontrivial prior probability for theism, atheism, and axiarchism. -
Argument, Structure, and Credibility in Public Health Writing Donald Halstead Instructor and Director of Writing Programs Harvard TH Chan School of Public Heath
Argument, Structure, and Credibility in Public Health Writing Donald Halstead Instructor and Director of Writing Programs Harvard TH Chan School of Public Heath Some of the most important questions we face in public health include what policies we should follow, which programs and research should we fund, how and where we should intervene, and what our priorities should be in the face of overwhelming needs and scarce resources. These questions, like many others, are best decided on the basis of arguments, a word that has its roots in the Latin arguere, to make clear. Yet arguments themselves vary greatly in terms of their strength, accuracy, and validity. Furthermore, public health experts often disagree on matters of research, policy and practice, citing conflicting evidence and arriving at conflicting conclusions. As a result, critical readers, such as researchers, policymakers, journal editors and reviewers, approach arguments with considerable skepticism. After all, they are not going to change their programs, priorities, practices, research agendas or budgets without very solid evidence that it is necessary, feasible, and beneficial. This raises an important challenge for public health writers: How can you best make your case, in the face of so much conflicting evidence? To illustrate, let’s assume that you’ve been researching mother-to-child transmission (MTCT) of HIV in a sub-Saharan African country and have concluded that (claim) the country’s maternal programs for HIV counseling and infant nutrition should be integrated because (reasons) this would be more efficient in decreasing MTCT, improving child nutrition, and using scant resources efficiently. The evidence to back up your claim might consist of original research you have conducted that included program assessments and interviews with health workers in the field, your assessment of the other relevant research, the experiences of programs in other countries, and new WHO guidelines. -
Evidential Relevance and the Grue Paradox
科 学 哲 学31-1(1998) Evidential Relevance and the Grue Paradox Robert T. Pennock Philosophy Department The University of Texas at Austin Abstract Goodman's Grue Paradox may be intransigent as a version of the problem of induction, but may be resolved within the more lim ited context of confirmation theory in which the task is to explicate the basic notion of evidential relevance. Although the green and grue hypotheses are equivalently confirmed if we follow Goodman's use of the Hempelian instance confirmation relation, there are asym metries than can be exploited if we adopt an "ontic" confirmation theory that uses a causal notion of evidential relevance. I sort out a variety of interpretive confusions about the intended content of the definition of grue and show how the causal approach resolves each in a way that is not paradoxical. 1. Introduction If we are to make progress in confirmation theory, we must distinguish local problems having to do with the nature of evidence from the global problem of induction. Nelson Goodman posed the Grue Paradox as "The New Riddle of In- duction," but his presentation set up the problem within a Hempelian model of confirmation. In what follows I do not address the aspect of the paradox that participates in the old problem of induction but focus upon the aspect that deals with the explication of the confirmation relation, that is, the relation having to do with what counts as evidence of what. In •˜2-•˜5 1 highlight features of the para- 101 dox that are problematic when viewed with this particular question of evidential relevance in mind and in •˜6 I show how we may avoid the problems by moving from a syntactic/semantic to an ontic/causal relevance relation.' 2. -
Pragmatism Is As Pragmatism Does: of Posner, Public Policy, and Empirical Reality
Volume 31 Issue 3 Summer 2001 Summer 2001 Pragmatism Is as Pragmatism Does: Of Posner, Public Policy, and Empirical Reality Linda E. Fisher Recommended Citation Linda E. Fisher, Pragmatism Is as Pragmatism Does: Of Posner, Public Policy, and Empirical Reality, 31 N.M. L. Rev. 455 (2001). Available at: https://digitalrepository.unm.edu/nmlr/vol31/iss3/2 This Article is brought to you for free and open access by The University of New Mexico School of Law. For more information, please visit the New Mexico Law Review website: www.lawschool.unm.edu/nmlr PRAGMATISM IS AS PRAGMATISM DOES: OF POSNER, PUBLIC POLICY, AND EMPIRICAL REALITY LINDA E. FISHER* Stanley Fish believes that my judicial practice could not possibly be influenced by my pragmatic jurisprudence. Pragmatism is purely a method of description, so I am guilty of the "mistake of thinking that a description of a practice has cash value in a game other than the game of description." But he gives no indication that he has tested this assertion by reading my judicial opinions.' I. INTRODUCTION Richard Posner, until recently the Chief Judge of the United States Court of Appeals for the Seventh Circuit, has been much studied; he is frequently controversial, hugely prolific, candid, and often entertaining.2 Judge Posner is repeatedly in the news, most recently as a mediator in the Microsoft antitrust litigation3 and as a critic of President Clinton.4 Posner's shift over time, from a wealth-maximizing economist to a legal pragmatist (with wealth maximization as a prominent pragmatic goal), is by now well documented.' This shift has been set forth most clearly in The Problematics of Moral and Legal Theory,6 as well as Overcoming Law7 and The Problems of Jurisprudence.8 The main features of his pragmatism include a Holmesian emphasis on law as a prediction of how a judge will rule.9 An important feature of law, then, is its ability to provide clear, stable guidance to those affected by it. -
A WIN-WIN SOLUTION the Empirical Evidence on School Choice FOURTH EDITION Greg Forster, Ph.D
A WIN-WIN SOLUTION The Empirical Evidence on School Choice FOURTH EDITION Greg Forster, Ph.D. MAY 2016 About the Friedman Foundation for Educational Choice The Friedman Foundation for Educational Choice is a 501(c)(3) nonprofit and nonpartisan organization, solely dedicated to advancing Milton and Rose Friedman’s vision of school choice for all children. First established as the Milton and Rose D. Friedman Foundation in 1996, the Foundation promotes school choice as the most effective and equitable way to improve the quality of K–12 education in America. The Friedman Foundation is dedicated to research, education, and outreach on the vital issues and implications related to school choice. A WIN-WIN SOLUTION The Empirical Evidence on School Choice FOURTH EDITION Greg Forster, Ph.D. MAY 2016 Table of Contents Executive Summary .......................................................................................................................1 Introduction ....................................................................................................................................3 Choice in Education .................................................................................................................3 Why Science Matters—the “Gold Standard” and Other Methods ....................................4 The Method of This Report .....................................................................................................6 Criteria for Study Inclusion or Exclusion .......................................................................6 -
Sacred Rhetorical Invention in the String Theory Movement
University of Nebraska - Lincoln DigitalCommons@University of Nebraska - Lincoln Communication Studies Theses, Dissertations, and Student Research Communication Studies, Department of Spring 4-12-2011 Secular Salvation: Sacred Rhetorical Invention in the String Theory Movement Brent Yergensen University of Nebraska-Lincoln, [email protected] Follow this and additional works at: https://digitalcommons.unl.edu/commstuddiss Part of the Speech and Rhetorical Studies Commons Yergensen, Brent, "Secular Salvation: Sacred Rhetorical Invention in the String Theory Movement" (2011). Communication Studies Theses, Dissertations, and Student Research. 6. https://digitalcommons.unl.edu/commstuddiss/6 This Article is brought to you for free and open access by the Communication Studies, Department of at DigitalCommons@University of Nebraska - Lincoln. It has been accepted for inclusion in Communication Studies Theses, Dissertations, and Student Research by an authorized administrator of DigitalCommons@University of Nebraska - Lincoln. SECULAR SALVATION: SACRED RHETORICAL INVENTION IN THE STRING THEORY MOVEMENT by Brent Yergensen A DISSERTATION Presented to the Faculty of The Graduate College at the University of Nebraska In Partial Fulfillment of Requirements For the Degree of Doctor of Philosophy Major: Communication Studies Under the Supervision of Dr. Ronald Lee Lincoln, Nebraska April, 2011 ii SECULAR SALVATION: SACRED RHETORICAL INVENTION IN THE STRING THEORY MOVEMENT Brent Yergensen, Ph.D. University of Nebraska, 2011 Advisor: Ronald Lee String theory is argued by its proponents to be the Theory of Everything. It achieves this status in physics because it provides unification for contradictory laws of physics, namely quantum mechanics and general relativity. While based on advanced theoretical mathematics, its public discourse is growing in prevalence and its rhetorical power is leading to a scientific revolution, even among the public. -
Hempel and Confirmation Theory
Hempel and Confirmation Theory Jan Sprenger* June 15, 2020 Carl Gustav Hempel (1905–1997) was one of the primary exponents of logical empiricism. As a student and member of the Gesellschaft für em- pirische Philosophie in Berlin, alongside Reichenbach and Grelling, he wit- nessed the emergence of logical empiricism as a philosophical program. From the mid-1930s onwards, his contributions shaped its development, too. Hempel studied primarily in Göttingen and Berlin, but in 1929/30, he also spent a semester in Vienna studying with Carnap and partici- pated in the activities of the Vienna Circle. Both societies joined forces for organizing scientific events, and founded the journal Erkenntnis in 1930, where many seminal papers of logical empiricism were published, with Carnap and Reichenbach as editors. While the work of the Berlin philosophers is congenial to the project of the Vienna Circle, there are important differences, too. Neither Hempel nor his mentor Reichenbach identified “scientific philosophy” with the project of cleansing science of meaningless statements (e.g., Carnap 1930). Rather, Hempel extensively used a method that Carnap would apply in later works on probability and confirmation (Carnap 1950, 1952): expli- cation, that is, the replacement of a vague and imprecise pre-theoretical concept (e.g., “confirmation”) by a fruitful and precise concept (e.g., a formal confirmation criterion). Relying on the method of explication, Hempel developed adequacy conditions on a qualitative concept of con- firmation (Hempel 1943, 1945a,b), a probabilistic measure of degree of *Contact information: Center for Logic, Language and Cognition (LLC), Department of Philosophy and Education Sciences, Università degli Studi di Torino, Via Sant’Ottavio 20, 10124 Torino, Italy. -
Notes on Hume's Problem of Induction 1748 - Inquiry Concerning Human Understanding
1740 - Treatise of Human Nature Notes on Hume's Problem of Induction 1748 - Inquiry Concerning Human Understanding Recall: Subject of confirmation = How scientific claims are justified. This assumes that they are capable of justification in the first place. Hume asks: Is there a rational basis for inductive inferences? Hume response: No! Consequence: To the extent that scientific claims are based on inductive inferences, they cannot be justified. Example: All observed ravens are black. Hume asks, Can we ever be justified in believing the conclusion? All ravens are black. Two types of objects of knowledge, according to Hume (I) Relations of ideas = Products of deductive (truth-preserving) Ex: 2 + 2 = 4 inferences; negation entails a contradiction. (II) Matters of fact = Products of inductive inferences; negation does Ex: All ravens are black. not entail a contradiction. Outline of Hume's Argument (1) Matters of fact can only be known through experience ("a posteriori"). (2) Therefore matters of fact can only be justified by recourse to experience. (3) But any attempt to do so is circular. ∴ There is no justification for inductive inferences. ASIDE 1. Hume is not just saying that we can never be certain about inductive inferences (i.e., we can never be 100% certain that all ravens are black). This would be uncontentious: Most people would agree that there's always room for error in making an inductive inference. However, most people would at the same time claim that we are justified in making (some) inductive inferences, even though they aren't 100% guaranteed to work (i.e., we think there are standards by which we can judge good inductive inferences from bad ones).