Legal formalism is the foil for many theories of law. Yet formalism remains controversial, meaning that its critics focus on claims that are not central. This paper sets out a view of formalism using a methodology that embraces one of formalism’s most distinct claims, that formalism is a scientific theory of law. This naturalistic view of formalism helps to distinguish two distinct types of formalism, “doctrinal formalism,” the view that judicial behaviour can be represented using rules, and “rule formalism,” the (...) view that judges follow external rules when they are deciding cases. Doctrinal formalism, understood in naturalistic terms, overcomes many of the criticisms that have been levelled at formalism and can also be used to rehabilitate the currently out‐of‐favour “declaratory theory of law.” Doctrinal formalism is also a longstanding view of law, reflecting both what the original formalists thought of law, and what many present‐day doctrinal lawyers seem to believe. The naturalistic methodology is used to show that the main dispute between doctrinal formalism and American legal realism can be explained by a difference of assumptions concerning whether the values of judges are relative to society, or relative to other judges. (shrink)

The suppression of the Modus Ponens inference is described as a loss of confidence in the conclusion C of an argument ''If A1 then C; If A2 then C; A1'' where A2 is a requirement for C to happen. It is hypothesised that this loss of confidence is due to the derivation of the conversational implicature ''there is a chance that A2 might not be satisfied'', and that different syntactic introductions of the requirement A2 (e.g., ''If C then A2'') will (...) lead to various frequencies in the derivation of this implicature, according to previous studies in the field of causal explanation. An experiment is conducted, whose results support those claims. Results are discussed in the light of the Mental Logic and Mental Model theories, as well as in the light of the pragmatic approach to uncertain reasoning. (shrink)

The suppression of the Modus Ponens inference is described as a loss of confidence in the conclusion C of an argument “If A1 then C; If A2 then C; A1” where A2 is a requirement for C to happen. It is hypothesised that this loss of confidence is due to the derivation of the conversational implicature “there is a chance that A2 might not be satisfied”, and that different syntactic introductions of the requirement A2 (e.g., “If C then A2”) will (...) lead to various frequencies in the derivation of this implicature, according to previous studies in the field of causal explanation. An experiment is conducted, whose results support those claims. Results are discussed in the light of the Mental Logic and Mental Model theories, as well as in the light of the pragmatic approach to uncertain reasoning. (shrink)

The relation between logic and thought has long been controversial, but has recently influenced theorizing about the nature of mental processes in cognitive science. One prominent tradition argues that to explain the systematicity of thought we must posit syntactically structured representations inside the cognitive system which can be operated upon by structure sensitive rules similar to those employed in systems of natural deduction. I have argued elsewhere that the systematicity of human thought might better be explained as resulting from the (...) fact that we have learned natural languages which are themselves syntactically structured. According to this view, symbols of natural language are external to the cognitive processing system and what the cognitive system must learn to do is produce and comprehend such symbols. In this paper I pursue that idea by arguing that ability in natural deduction itself may rely on pattern recognition abilities that enable us to operate on external symbols rather than encodings of rules that might be applied to internal representations. To support this suggestion, I present a series of experiments with connectionist networks that have been trained to construct simple natural deductions in sentential logic. These networks not only succeed in reconstructing the derivations on which they have been trained, but in constructing new derivations that are only similar to the ones on which they have been trained. (shrink)

In agreement with some of the ideas expressed by Perruchet & Vinter (P&V), we believe that some phenomena hitherto attributed to processing may in fact reflect a fundamental distinction between direct and reflexive forms of consciousness. This dichotomy, developed by the phenomenological tradition, is substantiated by examples coming from experimental psychology and lesion neuropsychology.

The aim of this study was to initiate the exploration of debiasing methods applicable in real-life settings for achieving lasting improvement in decision making competence regarding multiple decision biases. Here, we tested the potentials of the analogical encoding method for decision debiasing. The advantage of this method is that it can foster the transfer from learning abstract principles to improving behavioral performance. For the purpose of the study, we devised an analogical debiasing technique for 10 biases (covariation detection, insensitivity to (...) sample size, base rate neglect, regression to the mean, outcome bias, sunk cost fallacy, framing effect, anchoring bias, overconfidence bias, planning fallacy) and assessed the susceptibility of the participants ( N = 154) to these biases before and 4 weeks after the training. We also compared the effect of the analogical training to the effect of ‘awareness training’ and a ‘no-training’ control group. Results suggested improved performance of the analogical training group only on tasks where the violations of statistical principles are measured. The interpretation of these findings require further investigation, yet it is possible that analogical training may be the most effective in the case of learning abstract concepts, such as statistical principles, which are otherwise difficult to master. The study encourages a systematic research of debiasing trainings and the development of intervention assessment methods to measure the endurance of behavior change in decision debiasing. (shrink)

The question “What is the nature of experience?” is of perennial philosophical concern. It deals not only with the nature of experience qua experience, but additionally with related questions about the experiencing subject and that which is experienced. In other words, to speak of the philosophical problem of experience, one must also address questions about mind, world, and the various relations that link them together. Both William James and Kitarō Nishida were deeply concerned with these issues. Their shared notion of (...) “pure experience” is the conceptual cornerstone of their attempt to deal with the philosophical problem of experience. This dissertation is an analysis of “pure experience” and its relevance to several issues in contemporary hilosophy of mind. Drawing upon James’s and Nishida’s “pure experience”, I argue both for a sensorimotor-based, “extended” conception of consciousness and a bodily skills-based account of moral psychology. (shrink)

Critics of appraisal theory have difficulty accepting appraisal (with its constructive flavor) as an automatic process, and hence as a potential cause of most emotions. In response, some appraisal theorists have argued that appraisal was never meant as a causal process but as a constituent of emotional experience. Others have argued that appraisal is a causal process, but that it can be either rule-based or associative, and that the associative variant can be automatic. This article first proposes empirically investigating whether (...) rule-based appraisal can also be automatic and then proposes investigating the automatic nature of constructive (instead of rule-based) appraisal because the distinction between rule-based and associative is problematic. Finally, it discusses experiments that support the view that constructive appraisal can be automatic. (shrink)

Over the past few decades, cognitive science has identified several forms of reasoning that make essential use of conceptual knowledge. Despite significant theoretical and empirical progress, there is still no unified framework for understanding how concepts are used in reasoning. This paper argues that the theory of conceptual spaces is capable of filling this gap. Our strategy is to demonstrate how various inference mechanisms which clearly rely on conceptual information—including similarity, typicality, and diagnosticity-based reasoning—can be modeled using principles derived from (...) conceptual spaces. Our first topic analyzes the role of expectations in inductive reasoning and their relation to the structure of our concepts. We examine the relationship between using generic expressions in natural language and common-sense reasoning as a second topic. We propose that the strength of a generic can be described by distances between properties and prototypes in conceptual spaces. Our third topic is category-based induction. We demonstrate that the theory of conceptual spaces can serve as a comprehensive model for this type of reasoning. The final topic is analogy. We review some proposals in this area, present a taxonomy of analogical relations, and show how to model them in terms of distances in conceptual spaces. We also briefly discuss the implications of the model for reasoning with concepts in artificial systems. (shrink)

The distinction between rules and similarity is central to our understanding of much of cognitive psychology. Two aspects of existing research have motivated the present work. First, in different cognitive psychology areas we typically see different conceptions of rules and similarity; for example, rules in language appear to be of a different kind compared to rules in categorization. Second, rules processes are typically modeled as separate from similarity ones; for example, in a learning experiment, rules and similarity influences would be (...) described on the basis of separate models. In the present article, I assume that the rules versus similarity distinction can be understood in the same way in learning, reasoning, categorization, and language, and that a unified model for rules and similarity is appropriate. A rules process is considered to be a similarity one where only a single or a small subset of an object's properties are involved. Hence, rules and overall similarity operations are extremes in a single continuum of similarity operations. It is argued that this viewpoint allows adequate coverage of theory and empirical findings in learning, reasoning, categorization, and language, and also a reassessment of the objectives in research on rules versus similarity. Key Words: categorization; cognitive explanation; language; learning; reasoning; rules; similarity. (shrink)

In this article we focus on the concept of concept in conceptual change. We argue that (1) theories of higher learning must often employ two different notions of concept that should not be conflated: psychological and scientific concepts. The usages for these two notions are partly distinct and thus straightforward identification between them is unwarranted. Hence, the strong analogy between scientific theory change and individual learning should be approached with caution. In addition, we argue that (2) research in psychology and (...) cognitive science provides a promising theoretical basis for developing explanatory mechanistic models of conceptual change. Moreover, we argue that (3) arguments against deeper integration between the fields of psychology and conceptual change are not convincing, and that recent theoretical developments in the cognitive sciences might prove indispensable in filling in the details in mechanisms of conceptual change. (shrink)

The present research investigates the role of voluntary, conscious processing in strategy change. In 2 experiments, we address whether the switch to a new strategy is the result of data - driven, automatic processes or of voluntary processes. Experiment 1 demonstrates that participants performing an alphabet verification task are able to transfer a newly adopted strategy to dissimilar information never encountered before, verbally describe the task regularity that allows for the generation and application of the new strategy immediately after the (...) strategy was adopted. Using the same experimental task, Experiment 2 shows that participants, and decide against adopting a new strategy when the available evidence suggests that the new strategy cannot be used for the entire range of problems encountered. Overall, the obtained results support the view that strategy change is mediated by voluntary controlled processing. They do not support the view that strategy change is an inevitable, automatic consequence of task practice. The present research thus highlights a potential function of conscious human processing. (shrink)

This article proposes a unified framework for understanding creative problem solving, namely, the explicit–implicit interaction theory. This new theory of creative problem solving constitutes an attempt at providing a more unified explanation of relevant phenomena (in part by reinterpreting/integrating various fragmentary existing theories of incubation and insight). The explicit–implicit interaction theory relies mainly on 5 basic principles, namely, (a) the coexistence of and the difference between explicit and implicit knowledge, (b) the simultaneous involvement of implicit and explicit processes in most (...) tasks, (c) the redundant representation of explicit and implicit knowledge, (d) the integration of the results of explicit and implicit processing, and (e) the iterative (and possibly bidirectional) processing. A computational implementation of the theory is developed based on the CLARION cognitive architecture and applied to the simulation of relevant human data. This work represents an initial step in the development of process-based theories of creativity encompassing incubation, insight, and various other related.. (shrink)

The authors examined cultural preferences for formal versus intuitive reasoning among East Asian (Chinese and Korean), Asian American, and European American university students. We investigated categorization (Studies 1 and 2), conceptual structure (Study 3), and deductive reasoning (Studies 3 and 4). In each study a cognitive conflict was activated between formal and intuitive strategies of reasoning. European Americans, more than Chinese and Koreans, set aside intuition in favor of formal reasoning. Conversely, Chinese and Koreans relied on intuitive strategies more than (...) European Americans. Asian Americans' reasoning was either identical to that of European Americans, or intermediate. Differences emerged against a background of similar reasoning tendencies across cultures in the absence of conflict between formal and intuitive strategies. (shrink)

A number of ways of taxonomizing human learning have been proposed. We examine the evidence for one such proposal, namely, that there exist independent explicit and implicit learning systems. This combines two further distinctions, between learning that takes place with versus without concurrent awareness, and between learning that involves the encoding of instances versus the induction of abstract rules or hypotheses. Implicit learning is assumed to involve unconscious rule learning. We examine the evidence for implicit learning derived from subliminal learning, (...) conditioning, artificial grammar learning, instrumental learning, and reaction times in sequence learning. We conclude that unconscious learning has not been satisfactorily established in any of these areas. The assumption that learning in some of these tasks is predominantly based on rule abstraction is questionable. When subjects cannot report the “implicitly learned” rules that govern stimulus selection, this is often because their knowledge consists of instances or fragments of the training stimuli rather than rules. In contrast to the distinction between conscious and unconscious learning, the distinction between instance and rule learning is a sound and meaningful way of taxonomizing human learning. We discuss various computational models of these two forms of learning. (shrink)

Recently, a cottage industry has formed with the goal of analyzing reasoning. The relevant notion of reasoning in which philosophers are expressly interested is fixed through an epistemic functional description: reasoning—whatever it is—is our personal-level, rationally evaluable means of meeting our rational requirements through managing and updating our attitudes. Roughly, the dominant view in the extant literature as developed by Paul Boghossian, John Broome, and others is that reasoning is a rule-governed operation over propositional attitudes that results in a change (...) in attitude. In this paper, I argue that our personal-level operations over mental models and visuospatial imagery, which are representations in a non-propositional/analogue format, can be rationally evaluable processes of managing our attitudes and, thus, should be considered reasoning in the relevant sense. Furthermore, I show that if reasoning can occur through operations over mental models and imagery, then the dominant rule-following account mischaracterizes the cognitive operations and representational states assumed to be constitutive of reasoning and what grounds the rational status of a line of reasoning. (shrink)