Steve Oswald: Pragmatics and rhetoric

The idea that the language we speak influences the way we think has evoked perennial fascination and intense controversy. According to the strong version of this hypothesis, called the Sapir-Whorf hypothesis after the American linguists who propounded it, languages vary in their semantic partitioning of the world, and the structure of one's language influences how one understands the world. Thus speakers of different languages perceive the world differently. Although the last two decades have been marked by extreme skepticism concerning the possible effects of language on thought, recent theoretical and methodological advances in cognitive science have given the question new life. Research in linguistics and linguistic anthropology has revealed striking differences in cross-linguistic semantic patterns, and cognitive psychology has developed subtle techniques for studying how people represent and remember experience. It is now possible to test predictions about how a given language influences the thinking of its speakers. Language in Mind includes contributions from both skeptics and believers and from a range of fields. It contains work in cognitive psychology, cognitive development, linguistics, anthropology, and animal cognition. The topics discussed include space, number, motion, gender, theory of mind, thematic roles, and the ontological distinction between objects and substances. Contributors Melissa Bowerman, Eve Clark, Jill de Villiers, Peter de Villiers, Giyoo Hatano, Stan Kuczaj, Barbara Landau, Stephen Levinson, John Lucy, Barbara Malt, Dan Slobin, Steven Sloman, Elizabeth Spelke, and Michael Tomasello Bradford Books imprint

GENERAL COMMENTARY article Front. Psychol., 21 December 2015Sec. Comparative Psychology Volume 6 - 2015 | https://doi.org/10.3389/fpsyg.2015.01928

A capacity to act for reasons is a key indicator of intelligence. A leaf floats this way and that as the wind currents shift, a drone moves up or down with the movements of its controller, but a cognitive agent decides to walk to the store to get some food. This deliberative capacity to think through hypothetical situations, to choose between the grocery store or the restaurant, requires representational intentionality, the ability to think about real and possible situations in the world. According to the mainstream zeitgeist in the cognitive sciences, this capacity exhaustively reduces to lower level processes and, as a consequence, cognitive research has been driven increasingly inwards and downwards to focus on activity at the neural and molecular levels. Here, Nancy Salay argues that this move is deeply misguided. After revealing the central problems with this internalist idea, Salay puts forward an externalist paradigm of intentionality supported by recent empirical work in neuroscience, computer science, philosophy, animal cognition and developmental psychology. Drawing all of these insights together, she provides a unified framework in which to situate externalist views of intentionality, making progress towards a viable theory of cognition. This is a comprehensive theoretical guide and a valuable empirical resource for those who view cognition through an extended and enactive lens.

In a case study of the growth of cognitive science, we analyzed the activities of the Cognitive Science Society with a particular emphasis on the multidisciplinary nature of the field. Analyses of departmental affiliations, training back‐grounds, research methodology, and paper citations suggest that the journal Cognitive Science and the Annual Meeting of the Cognitive Science Society are dominated by cognitive psychology and computer science, rather than being an equal division among the constituent disciplines of cognitive science. However, at many levels, a growing percentage of work was found to involve a conjunction of multiple disciplines, such that approximately 30–50% of recent work in the Cognitive Science Society is multidisciplinary. In a questionnaire study of cognitive scientists involved in collaborative research, multidisciplinarity was found to shape the research process and affect the factors associated with successful research.

Although language is the primary medium by which we communicate our thoughts and feelings with others, only a fraction of published studies in psychology, communication, and allied fields have addressed the underlying psychology of language. Historically, the complexity of language was simply too overwhelming to tackle. The advent of computational techniques along with digital communication and social media has changed everything. We are now witnessing an exponential growth in the number of studies that link natural language use and real-world behaviors. Over the last thirty years, computer-based text analysis has grown from relatively simple word counting methods to revolutionary Large Language Models (LLMs) that can generate natural language in ways similar to human beings. The psychological study of language has roots in philosophy, with considerable influence and overlap with the fields of anthropology, sociology, linguistics, and communications. Since the 1990s, work in language psychology has been associated with a host of newer disciplines involving natural language processing, such as cognitive science, artificial intelligence, computational linguistics, and even subfields of engineering. The different approaches to the study of language adopted by these various fields are often complementary, with each approach informing the others. Oftentimes, language scholars from different disciplines fail to appreciate each other’s perspectives. Linguists, for example, are primarily interested in the structure and function of language. Computational linguists are usually interested in developing models to best classify two or more groups of language processes. Psychologists who study language are actually interested in the psychological states of the people who are generating the language samples. Accordingly, the readings in this bibliography come from a wide variety of fields but with an emphasis on what might be useful to psychologists in their research on language. The new world of language psychology has largely been built on expanding technologies in computer and data science in parallel with developments in social and cognitive psychology. As a result of cross-disciplinary collaborations, new approaches to data collection, research and statistical methods, and theoretical orientations have evolved. Given the rapid growth of the field, the current bibliography should be viewed as a placeholder as the field will continue to expand over the next few years.

Seeing — perception and vision — is implicitly the fundamental building block of the literature on rationality and cognition. Herbert Simon and Daniel Kahneman's arguments against the omniscience of economic agents — and the concept of bounded rationality — depend critically on a particular view of the nature of perception and vision. We propose that this framework of rationality merely replaces economic omniscience with perceptual omniscience. We show how the cognitive and social sciences feature a pervasive but problematic meta-assumption that is characterized by an eye. We raise concerns about this assumption and discuss different ways in which the all-seeing eye manifests itself in existing research on (bounded) rationality. We first consider the centrality of vision and perception in Simon's pioneering work. We then point to Kahneman's work — particularly his article Maps of Bounded Rationality — to illustrate the pervasiveness of an all-seeing view of perception, as manifested in the extensive use of visual examples and illusions. Similar assumptions about perception can be found across a large literature in the cognitive sciences. The central problem is the present emphasis on inverse optics — the objective nature of objects and environments, e.g., size, contrast, and color. This framework ignores the nature of the organism and perceiver. We argue instead that reality is constructed and expressed, and we discuss the species-specificity of perception, as well as perception as a user interface. We draw on vision science as well as the arts to develop an alternative understanding of rationality in the cognitive and social sciences. We conclude with a discussion of the implications of our arguments for the rationality and decision-making literature in cognitive psychology and behavioral economics, along with suggesting some ways forward.

Theopsych: A Psychological Science Primer for Theologians

Teaching and Learning Guide for: Pragmatics: From Theory to Experiment and Back Again

Thriving with Stone Age Minds: Evolutionary Psychology, Christian Faith, and the Quest for Human Flourishing

When rejecting and accepting hypotheses, it is important to determine the risk of false positive conclusions. Hierarchical Bayesian models are frequently applied in cognitive science, psychology, cognitive neuroscience, and psychiatry to reduce the variability of low-level parameters through partial pooling, and to obtain more robust parameter estimates for complex models using limited data. This may lower the risk of false positive inferences from lower-level estimates. In contrast, higher-level (e.g. group-level) estimates may be more affected by modeling choices (e.g. prior distributions), population-level variances in effects, and inference methods, which may in turn affect false positive rates for group-level effects. Here we used simulation and computational modeling to systematically examine false positive rates and effects of specific modeling choices on inferences in a simple hierarchical Bayesian temporal discounting model. To this end, 600 data sets of a temporal discounting task with two conditions were simulated, drawing individual condition effect parameters from a null distribution with varying standard deviations. For each simulated data set, the group-level mean change in the discount rate was modeled with eight different prior variances of the condition effect. Results were subsequently evaluated using several commonly applied Bayesian inference methods: the Savage-Dickey Bayes factor (BF), the directional Bayes factor (dBF), P(effect > 0), and the highest density interval (HDI) against zero decision rule. Results confirm that inference methods that directly depend on the posterior distribution can be used regardless of prior variances, whereas the Savage-Dickey BF should only be used with sufficiently informative priors. Based on the simulation work, decision thresholds that ensure false positive rates below 5% are provided for each inference method. Results are discussed in the context of computational modeling approaches in cognitive (neuro-)science and psychology.

‘Intra-Israeli Conflict’ examines how the primary corpus represents conflict between different ethnic and political demographics among Jews in Israel. Using cognitive science, social psychology, and cognitive psychology, Cairns attempts to understand how and why conflict comes to be. The chapter takes an in-depth view at the immigrants who form the main constituents of Francophone communities in Israel, namely those of Moroccan, Tunisian, and Algerian descent, and highlights their intra-ethnic differences and the intense emotions felt between them.

This chapter outlines an approach to genre as the driving force behind language, cognition, and communication. Genre can and has been studied in the humanities as well as the cognitive and social sciences, but the present chapter presents a theoretical integration of these approaches and offers a model that can be empirically investigated by various methods across the board of these disciplines. The model itself is based in cognitive psychology, and a number of possibilities and implications for text analysis are illustrated. Both the role of language itself as well as the connection with literature are included in the discussion in order to suggest how a complete picture can be achieved of the bi-directional traffic between cognitive science and the humanities.

Cognitive Informatics (CI) is a transdisciplinary enquiry of the internal information processing mechanisms and processes of the brain and natural intelligence shared by almost all science and engineering disciplines. This article presents an intensive review of the new field of CI. The structure of the theoretical framework of CI is described encompassing the Layered Reference Model of the Brain (LRMB), the OAR model of information representation, Natural Intelligence (NI) vs. Artificial Intelligence (AI), Autonomic Computing (AC) vs. imperative computing, CI laws of software, the mechanism of human perception processes, the cognitive processes of formal inferences, and the formal knowledge system. Three types of new structures of mathematics, Concept Algebra (CA), Real-Time Process Algebra (RTPA), and System Algebra (SA), are created to enable rigorous treatment of cognitive processes of the brain as well as knowledge representation and manipulation in a formal and coherent framework. A wide range of applications of CI in cognitive psychology, computing, knowledge engineering, and software engineering has been identified and discussed.

Does the language you speak affect the way you think? According to the Principle of Linguistic Relativity, it does. Whether, however, the principle holds, has for several decades been one of the most controversial issues in cognitive science (for overviews, see Lucy, 1997; Wolff & Holmes, 2011). At the risk of oversimplifying its history, ideas linked to linguistic relativity can be traced back to philosophical writings in the German Romanticism of the 19th century (such as by Wilhelm von Humboldt) and became more widely known when ethno-linguists Edward Sapir and Benjamin Lee Whorf elaborated on them in their scientific work in the first half of the 20th century. While popular in the humanities, the proposition that speakers of different languages might perceive the world differently was untenable in early cognitive science. It was regarded as incommensurate with the assumption of a unified mind operating on a universal language of thought and hence simply inconceivable. When linguistic relativity eventually was put on the agenda in the 1990s (Gumperz & Levinson, 1991; Lucy, 1992), it was still met with substantial dissent (e.g., Pinker, 1994; overview in Gleitman & Papafragou, 2005); and although the antagonism of the early days has since given way to a more constructive exchange in which both opponents and supporters are increasingly seeking the middle ground and are even beginning to collaborate (e.g., Malt & Majid, 2013; Regier & Kay, 2009), the topic remains hotly debated. The current issue of Topics in Cognitive Science aims to make a productive contribution to this debate, both in format and content. In terms of format, this topic is one of only two that the journal has published featuring a target article, followed by a range of commentaries and a response to those commentaries by the author of the target article. This setup, known from Current Anthropology and Behavioral and Brain Sciences, is ideal for assembling multiple perspectives on controversial topics of broad interest across disciplines. The target article around which the current issue is structured (Kemmerer, 2023), is authored by linguist David Kemmerer (Purdue University, US). He develops a theoretical argument in support of linguistic relativity as deriving from the Grounded Cognition Model, a theory on conceptual knowledge that is highly influential within cognitive science. The argument entails a novel prediction that has the potential to inspire new experimental work across a range of academic communities that work on topics as diverse as perception, action, memory, emotion, language, culture, development, and evolution. For bringing together responses across such a wide field, Topics in Cognitive Science is the optimal forum. And, indeed, the eight commentaries accompanying this target article do reflect a wide variety of perspectives, authored by scholars who represent research communities on four continents and from across the social sciences, information sciences, and cognitive sciences, including linguistics, neuroscience, philosophy, and psychology. Credit for this topic goes to Asifa Majid (Oxford University, UK), a member of the Senior Editorial Board of Topics in Cognitive Science, who herself is a pioneer and leading figure in this subfield of cognitive science. She has been a strong voice for taking (linguistic) diversity and its consequences for cognition seriously (Majid, Bowerman, Kita, Haun, & Levinson, 2004), and yet she is also respected across camps for placing empirical evidence higher than theoretical ideology and for remaining open to a middle ground (e.g., Majid, 2021; Malt, Gennari, Imai, Ameel, Tsuda, & Majid, 2008). It was she who recruited the target article from David Kemmerer for Topics in Cognitive Science, suggested the format, handled the reviewing process, invited the commentaries with a clear objective for diversity, and monitored the compilation of the entire topic. topiCS encourages letters and commentaries on all topics, as well as proposals for new topics. Letters are not longer than two published pages (ca. 400–1000 words). Commentaries (between 1000 and 2000 words) are often solicited by Topic Editors prior to the publication of their topic, but they may also be considered after publication. Letters and commentaries typically come without abstract and with few references, if any. The Executive Editor and the Senior Editorial Board (SEB) are constantly searching for new and exciting topics for topiCS. Feel free to open communications with a short note to the Executive Editor ([email protected]) or a member of the SEB (for a list, see the publisher's homepage for topiCS: http://onlinelibrary.wiley.com/journal/10.1111/(ISSN)1756-8765/homepage/EditorialBoard.html).

abstractThis paper offers the first general introduction to CODA (Cognitive Discourse Analysis), a methodology for analyzing verbal protocols and other types of unconstrained language use, as a resource for researchers interested in mental representations and high-level cognitive processes. CODA can be used to investigate verbalizations of perceived scenes and events, spatio-temporal concepts, complex cognitive processes such as problem-solving and cognitive strategies and heuristics, and other concepts that are accessible for verbalization. CODA builds on and extends relevant established methodologies such as cognitive linguistic perspectives, verbal protocol analysis in cognitive psychology and interdisciplinary content analysis, linguistic discourse analysis, and psycholinguistic experimentation.