Argumentation logicians have recognized a specter of relativism to haunt their philosophy of argument. However, their attempts to dispel pernicious relativism by invoking notions of a universal audience or a community of model interlocutors have not been entirely successful. In fact, their various discussions of a universal audience invoke the context-eschewing formalism of Kant’s categorical imperative. Moreover, they embrace the Kantian method for resolving the antinomies that continually vacillates between opposing extremes – here between a transcendent universal audience and a (...) context-embedded particular audience. This tack ironically restores the very external mediation they thought to obviate in their aim to ‘dethrone’ the absolutism and totalitarianism of formal logic with a democratic turn to audience adherence, the acceptability of premises and inferential links, and a contextual, or participant-relative, notion of cogency. (shrink)

In this paper we defend a particular version of the epistemic approach to argumentation. We advance some general considerations in favor of the approach and then examine the ways in which different versions of it play out with respect to the theory of fallacies, which we see as central to an understanding of argumentation. Epistemic theories divide into objective and subjective versions. We argue in favor of the objective version, showing that it provides a better account than its subjectivist rival (...) of the central fallacy of begging the question. We suggest that the strengths of the objective epistemic theory of fallacies provide support for the epistemic approach to argumentation more generally. (shrink)

Probabilistic models have much to offer to philosophy. We continually receive information from a variety of sources: from our senses, from witnesses, from scientific instruments. When considering whether we should believe this information, we assess whether the sources are independent, how reliable they are, and how plausible and coherent the information is. Bovens and Hartmann provide a systematic Bayesian account of these features of reasoning. Simple Bayesian Networks allow us to model alternative assumptions about the nature of the information sources. (...) Measurement of the coherence of information is a controversial matter: arguably, the more coherent a set of information is, the more confident we may be that its content is true, other things being equal. The authors offer a new treatment of coherence which respects this claim and shows its relevance to scientific theory choice. Bovens and Hartmann apply this methodology to a wide range of much discussed issues regarding evidence, testimony, scientific theories, and voting. Bayesian Epistemology is an essential tool for anyone working on probabilistic methods in philosophy, and has broad implications for many other disciplines. (shrink)

Deductivism is not merely a logical technique, but also a theory of normativity: it provides an objective and universal standard of evaluation. Contemporary dialectical logic rejects deductive normativity, replacing its universal standard by an intersubjective standard. It is argued in this paper that dialectical normativity does not improve upon deductive normativity. A dialogico-rhetorical alternative is proposed.

In Biro and Siegel we argued that a theory of argumentation mustfully engage the normativity of judgments about arguments, and we developedsuch a theory. In this paper we further develop and defend our theory.

Good informal arguments offer justification for their conclusions. They go wrong if the justifications double back, rendering the arguments circular. Circularity, however, is not necessarily a single property of an argument, but may depend on (a) whether the argument repeats an earlier claim, (b) whether the repetition occurs within the same line of justification, and (c) whether the claim is properly grounded in agreed‐upon information. The experiments reported here examine whether people take these factors into account in their judgments of (...) whether arguments are circular and whether they are reasonable. The results suggest that direct judgments of circularity depend heavily on repetition and structural role of claims, but only minimally on grounding. Judgments of reasonableness take repetition and grounding into account, but are relatively insensitive to structural role. (shrink)

This article approaches the relationship of normative argumentation studies and descriptive persuasion effects research by pointing to several empirical findings that raise questions or puzzles about normatively-proper argumentative conduct. These findings indicate some complications in the analysis of normatively desirable argumentative conduct – including some ways in which practical persuasive success may not be entirely compatible with normatively-desirable advocacy practices.

This paper addresses the apparent mismatch between the normative and descriptive literatures in the cognitive science of conditional reasoning. Descriptive psychological theories still regard material implication as the normative theory of the conditional. However, over the last 20 years in the philosophy of language and logic the idea that material implication can account for everyday indicative conditionals has been subject to severe criticism. The majority view is now apparently in favour of a subjective conditional probability interpretation. A comparative model fitting (...) exercise is presented that shows that a conditional probability model can explain as much of the data on abstract indicative conditional reasoning tasks as psychological theories that supplement material implication with various rationally unjustified processing assumptions. Consequently, when people are asked to solve laboratory reasoning tasks, they can be seen as simply generalising their everyday probabilistic reasoning strategies to this novel context. (shrink)

Bayesian reasoning has been applied formally to statistical inference, machine learning and analysing scientific method. Here I apply it informally to more common forms of inference, namely natural language arguments. I analyse a variety of traditional fallacies, deductive, inductive and causal, and find more merit in them than is generally acknowledged. Bayesian principles provide a framework for understanding ordinary arguments which is well worth developing.

Philosophically, the study of argumentation is important because it holds out the prospect of an interpretation of rationality. For this we need to identify a transcendent perspective on the argumentative interaction. We need a normative theory of argumentation that provides an answer to the question: should the hearer accept the argument of the speaker. In this article I argue that formal logic implies a notion of transcendence that is not suitable for the study of argumentation, because, from a logical point (...) of view, argumentation ’disappears from sight‘. We should therefore not expect formal logic to provide an interesting interpretation of the rationality intrinsic in argument and discussion. (shrink)

We examine in detail three classic reasoning fallacies, that is, supposedly ``incorrect'' forms of argument. These are the so-called argumentam ad ignorantiam, the circular argument or petitio principii, and the slippery slope argument. In each case, the argument type is shown to match structurally arguments which are widely accepted. This suggests that it is not the form of the arguments as such that is problematic but rather something about the content of those examples with which they are typically justified. This (...) leads to a Bayesian reanalysis of these classic argument forms and a reformulation of the conditions under which they do or do not constitute legitimate forms of argumentation. (shrink)

The evaluation of arguments and argumentation is best understood epistemologically. Epistemic circularity is not formally defective but it may be epistemologically objectionable. Sorenson's doubts about the syntactic approach to circularity are endorsed with qualifications. One explanation of an argument's goodness is its ability to produce justified belief in its conclusion by means of justified belief in its premises, but matters are not so simple for interpersonal argumentation. Even when an argument's premises and conclusion are justified for a speaker, this justifiedness (...) may not be transmissible to every hearer. Still, an epistemic approaeh is instructive. Arguing in enthymemes can be legitimate, e.g., because enthymemes can help produce justified persuasion in an audience that supplies the missing premises. (shrink)

What is a good argument? That depends on what is meant by 'argument'. In formal logic, an argument is a set of sentences or propositions, one designated as conclusion and the remainder as premises. On this conception of argument, there are two kinds of goodness. An argument is good in a weak sense if the conclusion either follows deductively from the premises or receives strong evidential support from them. An argument is good in a strong sense if, in addition to (...) this, it has only true premises. Thus, in the strong sense, the paradigm of a good argument is a sound argument. (shrink)

The study of deductive reasoning has been a major paradigm in psychology for approximately the past 40 years. Research has shown that people make many logical errors on such tasks and are strongly influenced by problem content and context. It is argued that this paradigm was developed in a context of logicist thinking that is now outmoded. Few reasoning researchers still believe that logic is an appropriate normative system for most human reasoning, let alone a model for describing the process (...) of human reasoning, and many use the paradigm principally to study pragmatic and probabilistic processes. It is suggested that the methods used for studying reasoning be reviewed, especially the instructional context, which necessarily defines pragmatic influences as biases. (shrink)

He further argues that it is necessary to rethink traditional conceptions of argument, and to find a position that avoids the limitations of both the highly abstract approach of formal logic and the highly contextualized approaches of rhetoric and communication theory.".

Although fallacies have been common since Aristotle, until recently little attention has been devoted to identifying and defining them. Furthermore, the concept of fallacy itself has lacked a sufficiently clear meaning to make it a useful tool for evaluating arguments. Douglas Walton takes a new analytical look at the concept of fallacy and presents an up-to-date analysis of its usefulness for argumentation studies. Walton uses case studies illustrating familiar arguments and tricky deceptions in everyday conversation where the charge of fallaciousness (...) is at issue. The numerous case studies show in concrete terms many practical aspects of how to use textual evidence to identify and analyze fallacies and to evaluate arguments as fallacious. Walton looks at how an argument is used in the context of conversation. He defines a fallacy as a conversational move, or sequence of moves, that is supposed to be an argument that contributes to the purpose of the conversation but in reality interferes with it. The view is a pragmatic one, based on the assumption that when people argue, they do so in a context of dialogue, a conventionalized normative framework that is goal-directed. Such a contextual framework is shown to be crucial in determining whether an argument has been used correctly. Walton also shows how examples of fallacies given in the logic textbooks characteristically turn out to be variants of reasonable, even if defeasible or questionable arguments, based on presumptive reasoning. This is the essence of the evaluation problem. A key thesis of the book, which must not be taken for granted as previous textbooks have so often done, is that you can spot a fallacy from how it was used in a context of dialogue. This is an innovative and even, as Walton notes, "a radical and controversial" theory of fallacy. (shrink)

Fallacies and Argument Appraisal presents an introduction to the nature, identification, and causes of fallacious reasoning, along with key questions for evaluation. Drawing from the latest work on fallacies as well as some of the standard ideas that have remained relevant since Aristotle, Christopher Tindale investigates central cases of major fallacies in order to understand what has gone wrong and how this has occurred. Dispensing with the approach that simply assigns labels and brief descriptions of fallacies, Tindale provides fuller treatments (...) that recognize the dialectical and rhetorical contexts in which fallacies arise. This volume analyzes major fallacies through accessible, everyday examples. Critical questions are developed for each fallacy to help the student identify them and provide considered evaluations. (shrink)

There is currently no viable alternative to the Bayesian analysis of scientific inference, yet the available versions of Bayesianism fail to do justice to several aspects of the testing and confirmation of scientific hypotheses. Bayes or Bust? provides the first balanced treatment of the complex set of issues involved in this nagging conundrum in the philosophy of science. Both Bayesians and anti-Bayesians will find a wealth of new insights on topics ranging from Bayes's original paper to contemporary formal learning theory. (...) In a paper published posthumously in 1763, the Reverend Thomas Bayes made a seminal contribution to the understanding of "analogical or inductive reasoning." Building on his insights, modem Bayesians have developed an account of scientific inference that has attracted numerous champions as well as numerous detractors. Earman argues that Bayesianism provides the best hope for a comprehensive and unified account of scientific inference, yet the presently available versions of Bayesianisin fail to do justice to several aspects of the testing and confirming of scientific theories and hypotheses. By focusing on the need for a resolution to this impasse, Earman sharpens the issues on which a resolution turns. John Earman is Professor of History and Philosophy of Science at the University of Pittsburgh. (shrink)

Bayesian reasoning has been applied formally to statistical inference, machine learning and analysing scientific method. Here I apply it informally to more common forms of inference, namely natural language arguments. I analyse a variety of traditional fallacies, deductive, inductive and causal, and find more merit in them than is generally acknowledged. Bayesian principles provide a framework for understanding ordinary arguments which is well worth developing.