While many philosophers of science have accorded special evidential significance to tests whose results are "novel facts", there continues to be disagreement over both the definition of novelty and why it should matter. The view of novelty favored by Giere, Lakatos, Worrall and many others is that of use-novelty: An accordance between evidence e and hypothesis h provides a genuine test of h only if e is not used in h's construction. I argue that what lies behind the intuition that (...) novelty matters is the deeper intuition that severe tests matter. I set out a criterion of severity akin to the notion of a test's power in Neyman-Pearson statistics. I argue that tests which are use-novel may fail to be severe, and tests that are severe may fail to be use-novel. I discuss the 1919 eclipse data as a severe test of Einstein's law of gravity. (shrink)

The traditional conception of knowledge is justified, true belief. If one looks at a modern textbook on epistemology, the great bulk of questions with which it deals are to do with personal knowledge, as embodied in beliefs and the proper experiences that someone ought to have had in order to have the right (or justification) to know. I intend to argue that due to the explosive growth of knowledge whose domain is “outside the head”, this conception has outlived its relevance. (...) -/- On the other hand, Karl Popper’s (1934) Falsificationism, with its emphasis on the objective character of knowledge, is not only a sounder, but also a more appropriate theory of knowledge for understanding the nature and growth of civilization. Later, Popper (1945) generalized this approach to obtain critical rationalism, in which all claims to knowledge, whether scientific or otherwise, are understood as objective solutions to objective problems and can be evaluated by other non-observational - types of criticism. I will first argue that Popper’s methodology is quite suited to the view that knowledge is an objective autonomous product and then adduce his theory of world 3, an ontology that neatly wraps up various considerations. World 3 is the domain of abstract products of the human mind that now have a life of their own, outside of human heads: theories, arguments, problems, plans, etc. I then adduce some other arguments for the autonomous quality of knowledge. (shrink)

Esta enciclopédia abrange, de uma forma introdutória mas desejavelmente rigorosa, uma diversidade de conceitos, temas, problemas, argumentos e teorias localizados numa área relativamente recente de estudos, os quais tem sido habitual qualificar como «estudos lógico-filosóficos». De uma forma apropriadamente genérica, e apesar de o território teórico abrangido ser extenso e de contornos por vezes difusos, podemos dizer que na área se investiga um conjunto de questões fundamentais acerca da natureza da linguagem, da mente, da cognição e do raciocínio humanos, bem (...) como questões acerca das conexões destes com a realidade não mental e extralinguística. A razão daquela qualificação é a seguinte: por um lado, a investigação em questão é qualificada como filosófica em virtude do elevado grau de generalidade e abstracção das questões examinadas (entre outras coisas); por outro, a investigação é qualificada como lógica em virtude de ser uma investigação logicamente disciplinada, no sentido de nela se fazer um uso intenso de conceitos, técnicas e métodos provenientes da disciplina de lógica. O agregado de tópicos que constitui a área de estudos lógico-filosóficos é já visível, pelo menos em parte, no Tractatus Logico-Philosophicus de Ludwig Wittgenstein, uma obra publicada em 1921. E uma boa maneira de ter uma ideia sinóptica do território disciplinar abrangido por esta enciclopédia, ou pelo menos de uma porção substancial dele, é extrair do Tractatus uma lista dos tópicos mais salientes aí discutidos; a lista incluirá certamente tópicos do seguinte género, muitos dos quais se podem encontrar ao longo desta enciclopédia: factos e estados de coisas; objectos; representação; crenças e estados mentais; pensamentos; a proposição; nomes próprios; valores de verdade e bivalência; quantificação; funções de verdade; verdade lógica; identidade; tautologia; o raciocínio matemático; a natureza da inferência; o cepticismo e o solipsismo; a indução; as constantes lógicas; a negação; a forma lógica; as leis da ciência; o número. (shrink)

ABSTRACTPossibly, the replication crisis constitutes the most important problem in psychology. It calls into question whether psychology is a science. Existing conceptualizations of replicability depend on effect sizes; the larger the population effect size, the greater the probability of replication. This is problematic and contributes to the replication crisis. A different conceptualization, not dependent on population effect sizes, is desirable. The proposed solution features the closeness of sample means to their corresponding population means, in both the original and replication experiments. (...) If the researcher has specified the sampling precision desired, it is possible to calculate the probability of replication, prior to data collection, and without dependence on the population effect size or expected population effect size. In addition, it is not necessary to know population means or standard deviations, nor sample means or standard deviations, to employ the proposed a priori way of thinking about... (shrink)

The controversy surrounding Popper's proposed solution to the problem of induction is beginning to display many of the symptoms of being interminable. For decades the discussion has continued, apparently without any progress being made. Again and again, Popperians and their critics have accused each other of ‘missing the point’. The essay attempts to explain what exactly is ‘the point’ of the problem of induction, and asks whether Popper does indeed miss it. An answer is proposed, and on this basis an (...) explanation for the puzzling interminability and emptiness of the above dialogue is put forward. (shrink)

This paper draws on the philosophy of Karl Popper to present a descriptive evolutionary epistemology that offers philosophical solutions to the following related problems: ‘What happens when learning takes place?’ and ‘What happens in human learning?’ It provides a detailed analysis of how learning takes place without any direct transfer of information from the environment to the learner, and it significantly extends the author's earlier published work on this topic. She proposes that learning should be construed as a special case (...) of ‘problem solving’ and as a fundamentally critical and creative process in which learning organisms develop ‘expectations’ that are not purely an outcome of genetic inheritance or random mutation. Human learning is then characterised with reference to: objectified knowledge; descriptive and argumentative language; theoretical problems; the search for error and specific limitation. If the author's evolutionary analysis of learning is valid, it would suggest that we should, if we wish to promote learning, be wary of corralling children and older students in environments that inhibit autonomous activity, that discourage criticality and creativity and generally limit opportunities for trial and error‐elimination. But education institutions, particularly those for older children and adolescents, are very often environments of this constraining kind. Traditionally, educationists have vastly underestimated the human potential for imaginative criticism—because in general they have not recognised the extent to which it lies at the heart of what humans, including the youngest children, do in order to succeed at even the most basic tasks. (shrink)

According to influential accounts of scientific method, such as critical rationalism, scientific knowledge grows by repeatedly testing our best hypotheses. But despite the popularity of hypothesis tests in statistical inference and science in general, their philosophical foundations remain shaky. In particular, the interpretation of non-significant results—those that do not reject the tested hypothesis—poses a major philosophical challenge. To what extent do they corroborate the tested hypothesis, or provide a reason to accept it? Popper sought for measures of corroboration that could (...) adequately answer this question. According to Popper, corroboration is different from probability-raising, and grounded in the predictive success and testability of a hypothesis. As such, corroboration becomes an indicator of the scientific value of a hypothesis and guides our practical preferences over hypotheses that have been subjected to severe tests. This article proves two impossibility results for corroboration measures based on statistical relevance. The generality of these results shows that Popper’s qualitative characterization of corroboration must be misguided. I explore what a more promising and scientifically useful concept of corroboration could look like. (shrink)

McLaughlin’s case for the theoretical relevance of either "Escape" or of Freudian social theory generally proves counter-productive. He offers very weak criteria for theory acceptance and often takes mere labels to be explanatory theories. He does so particularly in his promotion of the con- cept of ambivalence. I will engage the proposed case study and explain why the use of “ambivalence” in psychoanalysis (especially by Bleuler or Freud) and sociology (by Smelser and his followers) is untenable. I point to a (...) notable conflict between McLaughlin’s rationalist and other inten- tions, and will show how he shares the approach to social theories that makes for the state of affairs in the humanities which he deplores. (shrink)

ArgumentThis paper investigates whether there is a discrepancy between stated and actual aims in biomechanical research, particularly with respect to hypothesis testing. We present an analysis of one hundred papers recently published inThe Journal of Experimental BiologyandJournal of Biomechanics, and examine the prevalence of papers which have hypothesis testing as a stated aim, contain hypothesis testing claims that appear to be purely presentational, and have exploration as a stated aim. We found that whereas no papers had exploration as a stated (...) aim, 58 per cent of papers had hypothesis testing as a stated aim. We had strong suspicions, at the bare minimum, that presentational hypotheses were present in 31 per cent of the papers in this latter group. (shrink)

Whether educational research should employ the ‘scientific method’ has been a recurring issue in its history. Hence, textbooks on research methods continue to perpetuate the idea that research students ought to choose between competing camps: ‘positivist’ or ‘interpretivist’. In reference to one of the most widely referred to educational research methods textbooks on the market—namely Research Methods in Education by Cohen, Manion, and Morrison—this paper demonstrates (1) the misconception of science in operation and (2) the perversely false dichotomy that has (...) become enshrined in educational research. It then advocates a new approach, and suggests that the fixation with ‘science’ versus ‘non-science’ is counterproductive, when what is actually required for good inquiry is a critical approach to knowledge claims. (shrink)

This paper presents a new 'discontinuous' view of Popper's theory of corroboration, where theories cease to have corroboration values when new severe tests are devised which have not yet been performed, on the basis of a passage from The Logic of Scientific Discovery. Through subsequent analysis and discussion, a novel problem for Popper's account of corroboration, which holds also for the standard view, emerges. This is the problem of the Big Test : that the severest test of any hypothesis is (...) actually to perform all possible tests. But this means that Popper's demand for 'the severest tests' amounts simply to a demand for 'all possible tests'. The paper closes by considering how this bears on accommodation vs. prediction, with respect to corroboration. (shrink)

First, I answer the controversial question ’What is scientific realism?’ with extensive reference to the varied accounts of the position in the literature. Second, I provide an overview of the key developments in the debate concerning scientific realism over the past decade. Third, I provide a summary of the other contributions to this special issue.

This article shows that Popper’s measure of corroboration is inapplicable if, as Popper argued, the logical probability of synthetic universal statements is zero relative to any evidence that we might possess. It goes on to show that Popper’s definition of degree of testability, in terms of degree of logical content, suffers from a similar problem. 1 The Corroboration Function and P(h|b) 2 Degrees of Testability and P(h|b).

This paper is a supplement to, and provides a proof of principle of, Kuhn vs. Popper on Criticism and Dogmatism in Science: A Resolution at the Group Level. It illustrates how calculations may be performed in order to determine how the balance between different functions in science—such as imaginative, critical, and dogmatic—should be struck, with respect to confirmation (or corroboration) functions and rules of scientific method.

Stanford’s argument against scientific realism focuses on theories, just as many earlier arguments from inconceivability have. However, there are possible arguments against scientific realism involving unconceived (or inconceivable) entities of different types: observations, models, predictions, explanations, methods, instruments, experiments, and values. This paper charts such arguments. In combination, they present the strongest challenge yet to scientific realism.

This paper responds to Achinstein’s criticism of the thesis that the only empirical fact that can affect the truth of an objective evidence claim such as ‘e is evidence for h’ (or ‘e confirms h to degree r’) is the truth of e. It shows that cases involving evidential flaws, which form the basis for Achinstein’s objections to the thesis, can satisfactorily be accounted for by appeal to changes in background information and working assumptions. The paper also argues that the (...) a priori and empirical accounts of evidence are on a par when we consider scientific practice, but that a study of artificial intelligence might serve to differentiate them. (shrink)

This paper argues that talk of ‘the aim of science’ should be avoided in the philosophy of science, with special reference to the way that van Fraassen sets up the difference between scientific realism and constructive empiricism. It also argues that talking instead of ‘what counts as success in science as such’ is unsatisfactory. The paper concludes by showing what this talk may be profitably replaced with, namely specific claims concerning science that fall into the following categories: descriptive, evaluative, normative, (...) and definitional. There are two key advantages to this proposal. First, realism and its competitors may be understood to consist of highly nuanced variants. Second, scientific realism and its competitors may be understood as something other than ‘all or nothing’ theses about science. More particularly, one may accept that there are general claims concerning science in some of the identified categories, but deny that there are such claims in the others. (shrink)

Bayesian confirmation theory is rife with confirmation measures. Many of them differ from each other in important respects. It turns out, though, that all the standard confirmation measures in the literature run counter to the so-called “Reverse Matthew Effect” (“RME” for short). Suppose, to illustrate, that H1 and H2 are equally successful in predicting E in that p(E | H1)/p(E) = p(E | H2)/p(E) > 1. Suppose, further, that initially H1 is less probable than H2 in that p(H1) < p(H2). (...) Then by RME it follows that the degree to which E confirms H1 is greater than the degree to which it confirms H2. But by all the standard confirmation measures in the literature, in contrast, it follows that the degree to which E confirms H1 is less than or equal to the degree to which it confirms H2. It might seem, then, that RME should be rejected as implausible. Festa (2012), however, argues that there are scientific contexts in which RME holds. If Festa’s argument is sound, it follows that there are scientific contexts in which none of the standard confirmation measures in the literature is adequate. Festa’s argument is thus interesting, important, and deserving of careful examination. I consider five distinct respects in which E can be related to H, use them to construct five distinct ways of understanding confirmation measures, which I call “Increase in Probability”, “Partial Dependence”, “Partial Entailment”, “Partial Discrimination”, and “Popper Corroboration”, and argue that each such way runs counter to RME. The result is that it is not at all clear that there is a place in Bayesian confirmation theory for RME. (shrink)

The present paper is an attempt to explore the impact of Karl Popper's ideas on the views of a number of intellectual groups in post-revolutionary Iran. Throughout the text, we have tried to make use of original sources and our own personal experiences. The upshot of the arguments of the paper is that the Viennese philosopher has made a long-lasting impression on the intellectual scene of present-day Iran in that even those socio-political groups which are not in favour of his (...) ideas, especially his model of critical rationalism, have felt the urgent need to make themselves familiar with them. Moreover, many of Popper's ideas have directly or indirectly influenced the thinking of the decision-makers in Iran since 1978. (shrink)

The paradox of Gandhi being treated as an ivory-tower idealist despite being one of the most successful political leaders of the twentieth century, can be traced to his using a method to understand social processes that is fundamentally different from the dominant tendency to reduce reality to an underlying system. The fact that his method did not fit into the ideological systems that dominated the twentieth century contributed to it being ignored. This paper seeks to revisit the Gandhian method by (...) first identifying the limitations of viewing democracies entirely in terms of systems. It then goes on to explore Gandhi's alternative view of reality as a mass of actions. It finally uses this philosophical method to understand a rather violent example of identity politics, namely the destruction of the Babri Masjid in the Indian town of Ayodhya. (shrink)

This paper has two objectives, neither previously attempted in the published literature—first, to outline J. M. Keynes's theory of knowledge in some detail, and, secondly, to justify the contention that his epistemology is a variety of rationalism, and not, as many have asserted, a form of empiricism. Keynes's attitude to empirical data is also analysed as well as his views on prediction and theory choice. 1This paper is partly based on ideas initially advanced in O'Donnell [1982], a revised and expanded (...) version of which is to be published as O'Donnell [1989]. I should like to thank an anonymous referee for helpful comment, and King's College, Cambridge for permission to quote from the Keynes Papers. (shrink)

The notion of truthlikeness or verisimilitude has been a topic of intensive discussion ever since the definition proposed by Karl Popper was refuted in 1974. This paper gives an analysis of old and new debates about this notion. There is a fairly large agreement about the truthlikeness ordering of conjunctive theories, but the main rival approaches differ especially about false disjunctive theories. Continuing the debate between Niiniluoto’s min-sum measure and Schurz’s relevant consequence measure, the paper also gives a critical assessment (...) of Oddie’s new defense of the average measure and Kuipers’ refined definition of truth approximation. (shrink)

Alexander Bird argues for an epistemic account of scientific progress, whereas Darrell Rowbottom argues for a semantic account. Both appeal to intuitions about hypothetical cases in support of their accounts. Since the methodological significance of such appeals to intuition is unclear, I think that a new approach might be fruitful at this stage in the debate. So I propose to abandon appeals to intuition and look at scientific practice instead. I discuss two cases that illustrate the way in which scientists (...) make judgments about progress. As far as scientists are concerned, progress is made when scientific discoveries contribute to the increase of scientific knowledge of the following sorts: empirical, theoretical, practical, and methodological. I then propose to articulate an account of progress that does justice to this broad conception of progress employed by scientists. I discuss one way of doing so, namely, by expanding our notion of scientific knowledge to include both know-that and know-how. (shrink)

Despite the widespread use of key concepts of the Neyman–Pearson (N–P) statistical paradigm—type I and II errors, significance levels, power, confidence levels—they have been the subject of philosophical controversy and debate for over 60 years. Both current and long-standing problems of N–P tests stem from unclarity and confusion, even among N–P adherents, as to how a test's (pre-data) error probabilities are to be used for (post-data) inductive inference as opposed to inductive behavior. We argue that the relevance of error probabilities (...) is to ensure that only statistical hypotheses that have passed severe or probative tests are inferred from the data. The severity criterion supplies a meta-statistical principle for evaluating proposed statistical inferences, avoiding classic fallacies from tests that are overly sensitive, as well as those not sensitive enough to particular errors and discrepancies. Introduction and overview 1.1 Behavioristic and inferential rationales for Neyman–Pearson (N–P) tests 1.2 Severity rationale: induction as severe testing 1.3 Severity as a meta-statistical concept: three required restrictions on the N–P paradigm Error statistical tests from the severity perspective 2.1 N–P test T(): type I, II error probabilities and power 2.2 Specifying test T() using p-values Neyman's post-data use of power 3.1 Neyman: does failure to reject H warrant confirming H? Severe testing as a basic concept for an adequate post-data inference 4.1 The severity interpretation of acceptance (SIA) for test T() 4.2 The fallacy of acceptance (i.e., an insignificant difference): Ms Rosy 4.3 Severity and power Fallacy of rejection: statistical vs. substantive significance 5.1 Taking a rejection of H0 as evidence for a substantive claim or theory 5.2 A statistically significant difference from H0 may fail to indicate a substantively important magnitude 5.3 Principle for the severity interpretation of a rejection (SIR) 5.4 Comparing significant results with different sample sizes in T(): large n problem 5.5 General testing rules for T(), using the severe testing concept The severe testing concept and confidence intervals 6.1 Dualities between one and two-sided intervals and tests 6.2 Avoiding shortcomings of confidence intervals Beyond the N–P paradigm: pure significance, and misspecification tests Concluding comments: have we shown severity to be a basic concept in a N–P philosophy of induction? (shrink)

In this paper I argue that aim-oriented empiricism (AOE), a conception of natural science that I have defended at some length elsewhere[1], is a kind of synthesis of the views of Popper, Kuhn and Lakatos, but is also an improvement over the views of all three. Whereas Popper's falsificationism protects metaphysical assumptions implicitly made by science from criticism, AOE exposes all such assumptions to sustained criticism, and furthermore focuses criticism on those assumptions most likely to need revision if science is (...) to make progress. Even though AOE is, in this way, more Popperian than Popper, it is also, in some respects, more like the views of Kuhn and Lakatos than falsificationism is. AOE is able, however, to solve problems which Kuhn's and Lakatos's views cannot solve. [Back to Top]. (shrink)

The present article offers an introductory vision to the political philosophy of science. The political philosophy of science is a new field of study where the philosophy of science and political philosophy converge. We will see the main contents of this field. We will also note that it depends on the construction of a model of rationality where science and politics can meet each other. Finally, the article tries to outline such a model of rationality. In order to do so, (...) we will review the relationship between Karl Popper’s scientific and political philosophy. I suggest to read Popper’s critical rationalism in terms of a kind of prudential rationality. (shrink)