The article revisits the large n problem as it relates to the Jeffreys-Lindley paradox to compare the frequentist, Bayesian, and likelihoodist approaches to inference and evidence. It is argued that what is fallacious is to interpret a rejection of as providing the same evidence for a particular alternative, irrespective of n; this is an example of the fallacy of rejection. Moreover, the Bayesian and likelihoodist approaches are shown to be susceptible to the fallacy of acceptance. The key difference is that (...) in frequentist testing the severity evaluation circumvents both fallacies but no such principled remedy exists for the other approaches. (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)

This article calls into question the charge that frequentist testing is susceptible to the base-rate fallacy. It is argued that the apparent similarity between examples like the Harvard Medical School test and frequentist testing is highly misleading. A closer scrutiny reveals that such examples have none of the basic features of a proper frequentist test, such as legitimate data, hypotheses, test statistics, and sampling distributions. Indeed, the relevant error probabilities are replaced with the false positive/negative rates that constitute deductive calculations (...) based on known probabilities among events. As a result, the ampliative dimension of frequentist induction—learning from data about the underlying data-generating mechanism—is missing. *Received August 2009; revised January 2010. †To contact the author, please write to: Department of Economics, Virginia Tech, Blacksburg, VA 24061; e-mail: aris@vt.edu. (shrink)

The main aim of this paper is to revisit the curve fitting problem using the reliability of inductive inference as a primary criterion for the ‘fittest' curve. Viewed from this perspective, it is argued that a crucial concern with the current framework for addressing the curve fitting problem is, on the one hand, the undue influence of the mathematical approximation perspective, and on the other, the insufficient attention paid to the statistical modeling aspects of the problem. Using goodness-of-fit as the (...) primary criterion for ‘best', the mathematical approximation perspective undermines the reliability of inference objective by giving rise to selection rules which pay insufficient attention to ‘accounting for the regularities in the data'. A more appropriate framework is offered by the error-statistical approach, where (i) statistical adequacy provides the criterion for assessing when a curve captures the regularities in the data adequately, and (ii) the relevant error probabilities can be used to assess the reliability of inductive inference. Broadly speaking, the fittest curve (statistically adequate) is not determined by the smallness if its residuals, tempered by simplicity or other pragmatic criteria, but by the nonsystematic (e.g. white noise) nature of its residuals. The advocated error-statistical arguments are illustrated by comparing the Kepler and Ptolemaic models on empirical grounds. ‡I am grateful to Deborah Mayo and Clark Glymour for many valuable suggestions and comments on an earlier draft of the paper; estimating the Ptolemaic model was the result of Glymour's prompting and encouragement. †To contact the author, please write to: Department of Economics, Virginia Tech 3019 Pamplin Hall (0316), Blacksburg, VA 24061; e-mail: aris@vt.edu. (shrink)

Rayleigh and Ramsay discovered the inert gas argon in the atmospheric air in 1895 using a carefully designed sequence of experiments guided by an informal statistical analysis of the resulting data. The primary objective of this article is to revisit this remarkable historical episode in order to make a case that the error‐statistical perspective can be used to bring out and systematize (not to reconstruct) these scientists' resourceful ways and strategies for detecting and eliminating error, as well as dealing with (...) Duhemian ambiguities and underdetermination problems as they arose in the context of their local research settings. *Received December 2009; revised January 2010. †To contact the author, please write to: Department of Economics, 3016 Pamplin Hall, Virginia Tech, Blacksburg, VA 24061; e‐mail: aris@vt.edu. (shrink)

In empirical modeling, an important desiderata for deeming theoretical entities and processes as real is that they can be reproducible in a statistical sense. Current day crises regarding replicability in science intertwines with the question of how statistical methods link data to statistical and substantive theories and models. Different answers to this question have important methodological consequences for inference, which are intertwined with a contrast between the ontological commitments of the two types of models. The key to untangling them is (...) the realization that behind every substantive model there is a statistical model that pertains exclusively to the probabilistic assumptions imposed on the data. It is not that the methodology determines whether to be a realist about entities and processes in a substantive field. It is rather that the substantive and statistical models refer to different entities and processes, and therefore call for different criteria of adequacy. (shrink)

The main objective of the paper is to propose a frequentist interpretation of probability in the context of model-based induction, anchored on the Strong Law of Large Numbers (SLLN) and justifiable on empirical grounds. It is argued that the prevailing views in philosophy of science concerning induction and the frequentist interpretation of probability are unduly influenced by enumerative induction, and the von Mises rendering, both of which are at odds with frequentist model-based induction that dominates current practice. The differences between (...) the two perspectives are brought out with a view to defend the model-based frequentist interpretation of probability against certain well-known charges, including [i] the circularity of its definition, [ii] its inability to assign ‘single event’ probabilities, and [iii] its reliance on ‘random samples’. It is argued that charges [i]–[ii] stem from misidentifying the frequentist ‘long-run’ with the von Mises collective. In contrast, the defining characteristic of the long-run metaphor associated with model-based induction is neither its temporal nor its physical dimension, but its repeatability (in principle); an attribute that renders it operational in practice. It is also argued that the notion of a statistical model can easily accommodate non-IID samples, rendering charge [iii] simply misinformed. (shrink)

Although both philosophers and scientists are interested in how to obtain reliable knowledge in the face of error, there is a gap between their perspectives that has been an obstacle to progress. By means of a series of exchanges between the editors and leaders from the philosophy of science, statistics and economics, this volume offers a cumulative introduction connecting problems of traditional philosophy of science to problems of inference in statistical and empirical modelling practice. Philosophers of science and scientific practitioners (...) are challenged to reevaluate the assumptions of their own theories - philosophical or methodological. Practitioners may better appreciate the foundational issues around which their questions revolve and thereby become better 'applied philosophers'. Conversely, new avenues emerge for finally solving recalcitrant philosophical problems of induction, explanation and theory testing. (shrink)

The growing availability of computer power and statistical software has greatly increased the ease with which practitioners apply statistical methods, but this has not been accompanied by attention to checking the assumptions on which these methods are based. At the same time, disagreements about inferences based on statistical research frequently revolve around whether the assumptions are actually met in the studies available, e.g., in psychology, ecology, biology, risk assessment. Philosophical scrutiny can help disentangle 'practical' problems of model validation, and conversely, (...) a methodology of statistical model validation can shed light on a number of issues of interest to philosophers of science. (shrink)

Bernoulli’s 1713 golden theorem is viewed retrospectively in the context of modern model-based frequentist inference that revolves around the concept of a prespecified statistical model Mθx\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${\mathcal{M}}_{{{\varvec{\uptheta}}}} \left( {\mathbf{x}} \right)$$\end{document}, defining the inductive premises of inference. It is argued that several widely-accepted claims relating to the golden theorem and frequentist inference are either misleading or erroneous: (a) Bernoulli solved the problem of inference ‘from probability to frequency’, and thus (b) the golden theorem (...) cannot justify an approximate Confidence Interval (CI) for the unknown parameter θ\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\theta$$\end{document}, (c) Bernoulli identified the probability PA\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$P\left( A \right)$$\end{document} with the relative frequency 1n∑k=1nxk\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\frac{1}{n}\sum\nolimits_{k = 1}^{n} {x_{k} }$$\end{document} of event A as a result of conflating f(x0|θ)\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$f({\mathbf{x}}_{0} |\theta )$$\end{document} with f(θ|x0),\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$f(\theta |{\mathbf{x}}_{0} ),$$\end{document} where x0\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${\mathbf{x}}_{0}$$\end{document} denotes the observed data, and (d) the same ‘swindle’ is currently perpetrated by the p value testers. In interrogating the claims (a)–(d), the paper raises several foundational issues that are particularly relevant for statistical induction as it relates to the current discussions on the replication crises and the trustworthiness of empirical evidence, arguing that: [i] The alleged Bernoulli swindle is grounded in the unwarranted claim θ^nx0≃θ∗,\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\hat{\theta }_{n} \left( {{\mathbf{x}}_{0} } \right) \simeq \theta^{*},$$\end{document} for a large enough n, where θ^nX\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\hat{\theta }_{n} \left( {\mathbf{X}} \right)$$\end{document} is an optimal estimator of the true value θ∗\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\theta^{*}$$\end{document} of θ. [ii] Frequentist error probabilities are not conditional on hypotheses (H0 and H1) framed in terms of an unknown parameter θ since θ is neither a random variable nor an event. [iii] The direct versus inverse inference problem is a contrived and misplaced charge since neither conditional distribution f(x0|θ)\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$f({\mathbf{x}}_{0} |\theta )$$\end{document} and f(θ|x0)\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$f(\theta |{\mathbf{x}}_{0} )$$\end{document} exists (formally or logically) in model-based (Mθx\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${\mathcal{M}}_{{{\varvec{\uptheta}}}} \left( {\mathbf{x}} \right)$$\end{document}) frequentist inference. (shrink)

For model-based frequentist statistics, based on a parametric statistical model ${{\cal M}_\theta }$, the trustworthiness of the ensuing evidence depends crucially on the validity of the probabilistic assumptions comprising ${{\cal M}_\theta }$, the optimality of the inference procedures employed, and the adequateness of the sample size to learn from data by securing –. It is argued that the criticism of the postdata severity evaluation of testing results based on a small n by Rochefort-Maranda is meritless because it conflates [a] misuses (...) of testing with [b] genuine foundational problems. Interrogating this criticism reveals several misconceptions about trustworthy evidence and estimation-based effect sizes, which are uncritically embraced by the replication crisis literature. (shrink)

Statistical model specification and validation raise crucial foundational problems whose pertinent resolution holds the key to learning from data by securing the reliability of frequentist inference. The paper questions the judiciousness of several current practices, including the theory-driven approach, and the Akaike-type model selection procedures, arguing that they often lead to unreliable inferences. This is primarily due to the fact that goodness-of-fit/prediction measures and other substantive and pragmatic criteria are of questionable value when the estimated model is statistically misspecified. Foisting (...) one's favorite model on the data often yields estimated models which are both statistically and substantively misspecified, but one has no way to delineate between the two sources of error and apportion blame. The paper argues that the error statistical approach can address this Duhemian ambiguity by distinguishing between statistical and substantive premises and viewing empirical modeling in a piecemeal way with a view to delineate the various issues more effectively. It is also argued that Hendry's general to specific procedures does a much better job in model selection than the theory-driven and the Akaike-type procedures primary because of its error statistical underpinnings. (shrink)

The objective of the paper is threefold. First, to argue that some of Haavelmo's methodological ideas and insights have been neglected because they are largely at odds with the traditional perspective that views empirical modeling in economics as an exercise in curve-fitting. Second, to make a case that this neglect has contributed to the unreliability of empirical evidence in economics that is largely due to statistical misspecification. The latter affects the reliability of inference by inducing discrepancies between the actual and (...) nominal error probabilities. Third, to argue that the ‘bridge pier’ between theory and data, as envisaged by Haavelmo, T [The Probability Approach to Econometrics, Econometrica, 12, 1–115], can be completed by blending some of his key methodological ideas and insights into a refined/extended version of the frequentist approach to inference. This new perspective is used to revisit dynamic stochastic general equilibrium modeling in an attempt to bring.. (shrink)

We argue that a responsible analysis of today's evidence-based risk assessments and risk debates in biology demands a critical or metascientific scrutiny of the uncertainties, assumptions, and threats of error along the manifold steps in risk analysis. Without an accompanying methodological critique, neither sensitivity to social and ethical values, nor conceptual clarification alone, suffices. In this view, restricting the invitation for philosophical involvement to those wearing a "bioethicist" label precludes the vitally important role philosophers of science may be able to (...) play as bioevidentialists. The goal of this paper is to give a brief and partial sketch of how a metascientific scrutiny of risk evidence might work. (shrink)

According to Marr, a computational-level theory consists of two elements, the what and the why. This article highlights the distinct role of the Why element in the computational analysis of vision. Three theses are advanced: that the Why element plays an explanatory role in computational-level theories, that its goal is to explain why the computed function is appropriate for a given visual task, and that the explanation consists in showing that the functional relations between the representing cells are similar to (...) the “external” mathematical relations between the entities that these cells represent. (shrink)

Deborah Mayo's view of science is that learning occurs by severely testing specific hypotheses. Mayo expounded this thesis in her (1996) Error and the Growth of Experimental Knowledge (EGEK). This volume consists of a series of exchanges between Mayo and distinguished philosophers representing competing views of the philosophy of science. The tone of the exchanges is lively, edifying and enjoyable. Mayo's error-statistical philosophy of science is critiqued in the light of positions which place more emphasis on large-scale theories. The result (...) clarifies Mayo's account and highlights her contribution to the philosophy of science -- in particular, her contribution to the philosophy of those sciences that rely heavily on statistical analysis. The second half of the volume considers the application (or extension) of an error-statistical philosophy of science to theory testing in economics, causal modelling and legal epistemology. The volume also includes a contribution to the frequentist philosophy of statistics written by Mayo in collaboration with Sir David Cox. (shrink)

When do data provide good evidence for a hypothesis, evidence that warrants an inference to the hypothesis? Standard answers either reject the legitimacy of induction or else allow warranted inference from data to hypothesis when there are suitable relationships between and among the data and hypotheses. The severity account rejects all of these, maintaining instead that the good evidence relation concerns not only relations between data and hypotheses but also the methods for obtaining the data and the sensitivity of these (...) methods to detecting falsehood. So, for example, the severity account allows two rival hypotheses to fit the data equally well, even to the point of having the same prior and posterior probabilities relative to those data, while the data nonetheless favour one hypothesis over the other by virtue of those data providing a severe test of one hypothesis and not the other. The contributions to Error and Inference variously trace the genesis of the severity account from statistics-oriented sciences, elaborate upon the account’s details, apply the account to various philosophical issues, and offer challenges to the account’s adequacy and replies to major criticisms. The editors have developed the severity account in detail elsewhere, and this anthology is an effort …. (shrink)

This paper is an extended review of the book Error and Inference, edited by Deborah Mayo and Aris Spanos, about their frequentist and philosophical perspective on testing of hypothesis and on the criticisms of alternatives like the Bayesian approach.

Error and Inference discusses Deborah Mayo’s theory that connects the reliability of science to scientific evidence. She sees it as an essential supplement to the negative principles of critical rationalism. She and Aris Spanos, her co-editor, declare that the discussions in the book amount to tremendous progress. Yet most contributors to the book misconstrue the Socratic character of critical rationalism because they ignore a principal tenet: criticism in and of itself comprises progress, and empirical refutation comprises learning from (...) experience. Critical rationalism should be recommended in the critical spirit, not as dogma. (shrink)

Error and Inference discusses Deborah Mayo’s theory that connects the reliability of science to scientific evidence. She sees it as an essential supplement to the negative principles of critical rationalism. She and Aris Spanos, her co-editor, declare that the discussions in the book amount to tremendous progress. Yet most contributors to the book misconstrue the Socratic character of critical rationalism because they ignore a principal tenet: criticism in and of itself comprises progress, and empirical refutation comprises learning from (...) experience. Critical rationalism should be recommended in the critical spirit, not as dogma. (shrink)

Error and Inference discusses Deborah Mayo’s theory that connects the reliability of science to scientific evidence. She sees it as an essential supplement to the negative principles of critical rationalism. She and Aris Spanos, her co-editor, declare that the discussions in the book amount to tremendous progress. Yet most contributors to the book misconstrue the Socratic character of critical rationalism because they ignore a principal tenet: criticism in and of itself comprises progress, and empirical refutation comprises learning from (...) experience. Critical rationalism should be recommended in the critical spirit, not as dogma. (shrink)

Ariès traces Western man's attitudes toward mortality from the early medieval conception of death as the familiar collective destiny of the human race to the modern tendency, so pronounced in industrial societies, to hide death as if it were an embarrassing family secret.

行動経済学によって、さまざまに系統的な不合理さが見えてきた。手をかけることが高評価をもたらすIKEA効果、やる気をそいでいる高額ボーナス、自分で思いついた(と思わせられた)意見は好ましい、雑用は一気に 片づけるほうが楽...。行動経済学研究の第一人者が、わたしたちがなぜ、どのように不合理な行動をしてしまうのかをユニークな実験で紹介。わかりやすい数々の実例で経済の真の姿を解明し、よりよい決断へとつなげ る話題作。.

In this article, I analyze the working principle and associated concepts of the method of eidetic variation as illustrated by Husserl in Experience and Judgment. In so doing, I scrutinize the very specific sense in which, for Husserl, variation must be free in order to have intuition of a universal as pure, that is, as having a priori validity. I then discuss Husserl’s problematic claim that, even if totally free, the eidetic variation is actually not sufficient to achieve purity. The (...) reason for its insufficiency, I argue, must be sought in the habits of phantasy. To this aim, I first undertake a phenomenological analysis of the essence of these habits as passive tendencies of the phantasizing ego. Then, I show that they hinder the intuition of the universal as pure by contaminating the purity of the free possibilities to be varied. Finally, I discuss whether habits of phantasy can be put out of play and whether, depending on the realizability of such a task, the whole method of eidetic variation, and, in relation to it, the possibility of a priori knowledge advocated by Husserl is to be put into question. (shrink)

This article explores Gerardus van der Leeuw’s view of phenomenology of religion. The phenomenological method he defended is basically a hermeneutical approach in which an observer relates personally and even existentially to the “phenomena” (s)he studies in order to determine their essence (Wesensschau). In his anthropology (that reflects on the basic structure of human beings) a similar way of relating to the world is discussed: the “primitive mentality” that is characterized by the “need to participate” (besoin de participation). Both phenomenology (...) and mentalité primitive imply a critique of modern scholarship. This fundamental criticism of the prevailing (historical) approach in the humanities including religious studies explains the growing distance between van der Leeuw and the majority of scholars of religion in the decades after his death in 1950. (shrink)

This article explores Gerardus van der Leeuw’s view of phenomenology of religion. The phenomenological method he defended is basically a hermeneutical approach in which an observer relates personally and even existentially to the “phenomena” (s)he studies in order to determine their essence (Wesensschau). In his anthropology (that reflects on the basic structure of human beings) a similar way of relating to the world is discussed: the “primitive mentality” that is characterized by the “need to participate” (besoin de participation). Both phenomenology (...) and mentalité primitive imply a critique of modern scholarship. This fundamental criticism of the prevailing (historical) approach in the humanities including religious studies explains the growing distance between van der Leeuw and the majority of scholars of religion in the decades after his death in 1950. (shrink)

In this paper we provide a proof theoretical investigation of logical argumentation, where arguments are represented by sequents, conflicts between arguments are represented by sequent elimination rules, and deductions are made by dynamic proof systems extending standard sequent calculi. The idea is to imitate argumentative movements in which certain claims are introduced or withdrawn in the presence of counter-claims. This is done by a dynamic evaluation of sequences of sequents, in which the latter are considered ‘derived’ or ‘not derived’ according (...) to the content of the sequence. We show that decisive conclusions of such a process correspond to well-accepted consequences of the underlying argumentation framework. The outcome is therefore a general and modular proof-theoretical approach for paraconsistent and non-monotonic reasoning with argumentation systems. (shrink)

Constructions of Intersubjectivity shows that the meaning of grammatical constructions often has more to do with the human cognitive capacity for taking other peoples' points of view than with describing the world. Treating pragmatics, semantics, and syntax in parallel and integrating insights from linguistics, psychology, and animal communication, Arie Verhagen develops a new understanding of linguistic communication. In doing so he shows the continuity between language and animal communication and reveals the nature of human linguistic specialization. Professor Verhagen uses Dutch (...) and English data from a wide variety of sources and considers the contributions of grammar to the coherence of discourse. He argues that important problems in semantics and syntax may be resolved if language is understood as an instrument for exerting influence and coordinating different perspectives. The grammatical phenomena he discusses include negative expressions, the let alone construction, complementation constructions, and discourse connectives.This powerfully argued and original explanation of the nature and operation of communication will interest a wide range of scholars and advanced students in linguistics, cognitive science, and human evolution. (shrink)

In the present article, I introduce Husserl’s analyses of ‘natural causality’ and ‘volitional causality’, which are collected in the volume ‘Wille und Handlung’ of the Husserliana edition Studien zur Struktur des Bewußtseins. My aim is to show that Husserl’s insight into these phenomena enables us to understand more clearly both the specificity of, and the relation between, the motivational nexus belonging to the sphere of the will in contrast with the causal laws of nature. In light of this understanding, in (...) the last part of the article I reflect on whether and to what extent there is, in fact, an ontological and epistemological compatibility between volitional causality and natural causality. (shrink)

This study offers a fresh reappraisal of the philosopher, political thinker, and historian of ideas Sir Isaiah Berlin (1909-1997) from childhood to the height of his intellectual career. It provides the first historically contextualized study of Berlin's formative years and identifies different stages in his intellectual development, allowing a reappraisal of his theory of liberalism. Applying a 'double perspective' that examines Berlin both as an East European Jewish émigré; as well as a British Liberal intellectual, author Arie Dubnov stresses the (...) very ambivalent relation between Berlin's liberal philosophy and his pro-Zionist sentiments. (shrink)

This work focuses on the conception of God of the medieval Jewish philosopher and legal scholar, Hasdai Crescas (1340-1410/11). It demonstrates that Crescas’ God is infinitely creative and good and explores the parallel that Crescas implicitly draws between God as creator and legislator.

The public sphere, be it the Greek agora or the New York Times op-ed page, is the realm of appearances - not citizenship. Its central event is spectacle - not dialogue. Public dialogue, the mantra of many intellectuals and political commentators, is but a contradiction in terms. Marked by an asymmetry between the few who act and the many who watch, the public sphere can undermine liberal democracy, law, and morality. Inauthenticity, superficiality, and objectification are the very essence of the (...) public sphere. But the public sphere also liberates us from the bondages of private life and fosters an existentially vital aesthetic experience. Reign of Appearances uses a variety of cases to reveal the logic of the public sphere, including homosexuality in Victorian England, the 2008 crash, antisemitism in Europe, confidence in American presidents, communications in social media, special prosecutor investigations, the visibility of African-Americans, violence during the French Revolution, the Islamic veil, and contemporary sexual politics. This unconventional account of the public sphere is critical reading for anyone who wants to understand the effects of visibility in urban life, politics, and the media. (shrink)

In the present article, I discuss Husserl’s analysis of the genesis of action in the Husserliana edition Studien zur Struktur des Bewusstseins. My aim is to clarify how a “voluntary action” has its...

Some people claim that evolution is "just a theory". Do you know what a scientific theory really is? Just a theory is an overview of the modern concepts of science. A clear understanding of the nature of science will enable you to distinguish science from pseudoscience (which illegitimately wraps itself in the mantle of science), and real social issues in science from the caricatures portrayed in postmodernist critiques. Prof. Ben-Ari's style is light (even humorous) and easy to read, bringing the (...) latest concepts of science to the general reader. Of particular interest is his analysis of the terminology of science (fact, law, proof, theory) in relation to the colloquial meaning of these terms. Between chapters are biographical vignettes of scientists — both familiar and unfamiliar — showing their common commitment to the enterprise of science, together with a diversity of backgrounds and personalities. This accessible, informative, and comprehensive work will give lay readers a good grasp of real science. (shrink)

In the present article, I address the issue of categorial representative contents, which, according to Husserl’s phenomenological theory, make knowledge possible by providing fullness to intuitive categorial acts. First, I discuss Husserl’s assertion that he no longer approves of his theory of categorial representation developed in Logical Investigations. I argue that the influential interpretation of Husserl’s self-criticism advanced by Dieter Lohmar is unfortunately misleading, as Husserl does not actually claim that categorial representatives are contents of reflection belonging to the realm (...) of inner sensibility, as Lohmar contends. After offering an alternative view of Husserl’s authentic position in Logical Investigations, I examine other possible reasons for his later dissatisfaction. These reasons relate to Husserl’s changing views on the role of categorial representatives in empty thinking acts—necessarily involved in cognition—and the necessity of spontaneously repeating the passive synthesis between the intentional matters that function as categorial representatives in the predicative activity yielding knowledge. (shrink)