Words are the essence of communication: They are the building blocks of any language. Learning the meaning of words is thus one of the most important aspects of language acquisition: Children must first learn words before they can combine them into complex utterances. Many theories have been developed to explain the impressive efficiency of young children in acquiring the vocabulary of their language, as well as the developmental patterns observed in the course of lexical acquisition. A major source of disagreement (...) among the different theories is whether children are equipped with special mechanisms and biases for word learning, or their general cognitive abilities are adequate for the task. We present a novel computational model of early word learning to shed light on the mechanisms that might be at work in this process. The model learns word meanings as probabilistic associations between words and semantic elements, using an incremental and probabilistic learning mechanism, and drawing only on general cognitive abilities. The results presented here demonstrate that much about word meanings can be learned from naturally occurring child-directed utterances (paired with meaning representations), without using any special biases or constraints, and without any explicit developmental changes in the underlying learning mechanism. Furthermore, our model provides explanations for the occasionally contradictory child experimental data, and offers predictions for the behavior of young word learners in novel situations. (shrink)

While speakers have been shown to adapt to the knowledge state of their addressee in choosing referring expressions, they often also show some egocentric tendencies. The current paper aims to provide an explanation for this “mixed” behavior by presenting a model that derives such patterns from the probabilistic combination of both the speaker's and the addressee's perspectives. To test our model, we conducted a language production experiment, in which participants had to refer to objects in a context that also included (...) a visually misleading object whose function was either known to both partners, or known just to the speaker but not the addressee. Modeling results indicate that the experimental findings cannot be explained by assuming that speakers tailor a referring expression solely to their own perspective or to the perspective of their addressee. Instead, accounting for the behavioral pattern requires an approach where both perspectives influence the choice of referring expressions. Nevertheless, in our situation, speakers consider their partner's perspective more than their own. (shrink)

We explore the following two cognitive questions regarding crosslinguistic variation in lexical semantic systems: Why are some linguistic categories—that is, the associations between a term and a portion of the semantic space—harder to learn than others? How does learning a language‐specific set of lexical categories affect processing in that semantic domain? Using a computational word‐learner, and the domain of color as a testbed, we investigate these questions by modeling both child acquisition of color terms and adult behavior on a non‐verbal (...) color discrimination task. A further goal is to test an approach to lexical semantic representation based on the principle that the more languages label any two situations with the same word, the more conceptually similar those two situations are. We compare such a crosslinguistically based semantic space to one based on perceptual similarity. Our computational model suggests a mechanistic explanation for the interplay between term frequency and the semantic closeness of learned categories in developmental error patterns for color terms. Our model also indicates how linguistic relativity effects could arise from an acquisition mechanism that yields language‐specific topologies for the same semantic domain. Moreover, we find that the crosslinguistically inspired semantic space supports these results at least as well as—and in some aspects better than—the purely perceptual one, thus confirming our approach as a practical and principled method for lexical semantic representation in cognitive modeling. (shrink)

How children go about learning the general regularities that govern language, as well as keeping track of the exceptions to them, remains one of the challenging open questions in the cognitive science of language. Computational modeling is an important methodology in research aimed at addressing this issue. We must determine appropriate learning mechanisms that can grasp generalizations from examples of specific usages, and that exhibit patterns of behavior over the course of learning similar to those in children. Early learning of (...) verb argument structure is an area of language acquisition that provides an interesting testbed for such approaches due to the complexity of verb usages. A range of linguistic factors interact in determining the felicitous use of a verb in various constructions—associations between syntactic forms and properties of meaning that form the basis for a number of linguistic and psycholinguistic theories of language. This article presents a computational model for the representation, acquisition, and use of verbs and constructions. The Bayesian framework is founded on a novel view of constructions as a probabilistic association between syntactic and semantic features. The computational experiments reported here demonstrate the feasibility of learning general constructions, and their exceptions, from individual usages of verbs. The behavior of the model over the timecourse of acquisition mimics, in relevant aspects, the stages of learning exhibited by children. Therefore, this proposal sheds light on the possible mechanisms at work in forming linguistic generalizations and maintaining knowledge of exceptions. (shrink)

Lexical ambiguity—the phenomenon of a single word having multiple, distinguishable senses—is pervasive in language. Both the degree of ambiguity of a word (roughly, its number of senses) and the relatedness of those senses have been found to have widespread effects on language acquisition and processing. Recently, distributional approaches to semantics, in which a word's meaning is determined by its contexts, have led to successful research quantifying the degree of ambiguity, but these measures have not distinguished between the ambiguity of words (...) with multiple related senses versus multiple unrelated meanings. In this work, we present the first assessment of whether distributional meaning representations can capture the ambiguity structure of a word, including both the number and relatedness of senses. On a very large sample of English words, we find that some, but not all, distributional semantic representations that we test exhibit detectable differences between sets of monosemes (unambiguous words; N = 964), polysemes (with multiple related senses; N = 4,096), and homonyms (with multiple unrelated senses; N = 355). Our findings begin to answer open questions from earlier work regarding whether distributional semantic representations of words, which successfully capture various semantic relationships, also reflect fine‐grained aspects of meaning structure that influence human behavior. Our findings emphasize the importance of measuring whether proposed lexical representations capture such distinctions: In addition to standard benchmarks that test the similarity structure of distributional semantic models, we need to also consider whether they have cognitively plausible ambiguity structure. (shrink)

Cognitive Science, Volume 46, Issue 6, June 2022.

Our contributors explore a rich variety of aesthetic problems that bring about the self-reflexive re-evaluation of ideas.

Person‐centred practice indubitably seems to be the antithesis of technology. The ostensible polarity of technology and person‐centred practice is an easy road to travel down and in their various forms has been probably travelled for decades if not centuries. By forging ahead or enduring these dualisms, we continue to approach and recede, but never encounter the elusive and the liminal space between technology and person‐centred practice. Inspired by Haraway's work, we argue that healthcare practitioners who critically consider their cyborg ontology (...) may begin the process to initiate and complicate the liminal and sought after space between technology and person‐centred practice. In this paper, we draw upon Haraway's idea that we are all materially and ontologically cyborgs. Cyborgs, the hybridity of machine and human, are part of our social reality and embedded in our everyday existence. By considering our cyborg ontology, we suggest that person‐centred practice can be actualized in the contextualized, embodied and relational spaces of technology. It is not a question of espousing technology or person‐centred practice. Such dualisms have been historically produced and reproduced over many decades and prevented us from recognizing our own cyborg ontology. Rather, it is salient that we take notice of our own cyborg ontology and how technological, habitual ways of being may prevent (and facilitate) us to recognize the embodied and contextualized experiences of patients. A disruption and engagement with the habitual can ensure we are not governed by technology in our logics and practices of care and can move us to a conscious and critical integration of person‐centred practice in the technologized care environments. By acknowledging ourselves as cyborgs, we can recapture and preserve our humanness as caregivers, as well as thrive as we proceed in our technological way of being. (shrink)

This Handbook addresses Chaucer's poetry in the context of several disciplines, including late medieval philosophy and science, Mediterranean culture, comparative European literature, vernacular theology, and popular devotion.

By examining the shared neuro-cognitive correlates of curiosity and creativity, we better understand the brain basis of creativity. However, by only examining shared components, important neuro-cognitive correlates are overlooked. Here, we argue that any comprehensive brain model of creativity should consider multiple cognitive processes and, alongside the interplay between brain networks, also the neurochemistry and neural oscillations that underly creativity.

The insights described by Nevin & Grace may be summarized without reference to the Newtonian concepts they suggest. The metaphor to Newtonian mechanics seems dubious in three ways: (1) extensions seem to lead to paradoxes; (2) many well-known phenomena are ignored; (3) the Newtonian concepts seem difficult to reconcile with the larger framework of evolutionary theory.

A wider social stage -- Girls will be boys : gender, envy, and the Freudian social contract -- Anna-Antigone : experiments in group upbringing -- The defense of psychoanalysis/the anxiety of politics -- Conclusion : ego politics.

It is widely held that for a life to be conferred meaning it requires the appropriate type of agency. Call this the agency requirement. The agency requirement is primarily motivated in the philosophical literature by the assumption that there is a widespread pre-theoretical intuition that humans have the capacity for meaning whereas animals do not; and that difference must come down to their agency or lack thereof. This paper aims to undercut the motivation for the agency requirement by arguing our (...) pre-theoretical intuitions actually run opposite; that animals, and even objects, can have meaningful lives/existences. The argument is twofold. First, I extend an existing argument for animals as having a capacity for meaning to objects. Second, I argue maintaining that only humans have the capacity for meaning results in the more counterintuitive upshot that all animals and objects have, by definition, meaningless existences. Since we pre-theoretically believe that anything can be meaningful—even things which by definition lack agency—then we have strong reason for being sceptical about an agency requirement for meaning in life. (shrink)

In the VIBeS study, Pierson et al. (2024) observe that the views of U.S. bioethicists do not align with views of clinicians or with broader U.S. public opinion. They also note that the bioethics co...

In this book, Suzanne Kirschner traces the origins of contemporary psychoanalysis back to the foundations of Judaeo-Christian culture, and challenges the prevailing view that modern theories of the self mark a radical break with religious and cultural tradition. Instead, she argues, they offer an account of human development which has its beginnings in biblical theology and neoplatonic mysticism. Drawing on a wide range of religious, literary, philosophical and anthropological sources, Dr Kirschner demonstrates that current Anglo-American psychoanalytic theories are but (...) the latest version of a narrative that has been progressively secularized over the course of nearly two millennia. She displays a deep understanding of psychoanalytic theories, while at the same time raising provocative questions about their status as knowledge and as science. (shrink)

Examination of recent debates about belief shows the need to distinguish: (a) non-linguistic informational states in animal perception; (b) the uncritical use of language, e.g. by children; (c) adult humans' reasoned judgments. If we also distinguish between mind-directed and object-directed mental states, we have: Perceptual 'beliefs' of animals and infants about their material environment. 'Beliefs' of animals and infants about the mental states of others. Linguistically-expressible beliefs about the world, resulting from e.g. the uncritical tendency to believe what we are (...) told. Uncritically-formed beliefs about the mental states. Beliefs about the material world arrived at by the weighing of evidence. Beliefs about mental states formed by critical assessment. (shrink)

Scientists and decision makers rely on climate models for predictions concerning future climate change. Traditionally, physical processes that are key to predicting extreme events are either directly represented or indirectly represented. Scientists are now replacing physically based parameterizations with neural networks that do not represent physical processes directly or indirectly. I analyze the epistemic implications of this method and argue that it undermines the reliability of model predictions. I attribute the widespread failure in neural network generalizability to the lack of (...) process representation. The representation of climate processes adds significant and irreducible value to the reliability of climate model predictions. (shrink)

Contemporary literature on consciousness, with some exceptions, rarely considers the olfactory system. In this article the characteristics of olfactory consciousness, viewed from the standpoint of the phenomenal /access distinction, are examined relative to the major senses. The review details several qualitative differences in both olfactory P consciousness and A consciousness . The basis for these differences is argued to arise from the functions that the olfactory system performs and from the unique neural architecture needed to instantiate them. These data suggest, (...) at a minimum, that P and A consciousness are uniquely configured in olfaction and an argument can be made that the P and A distinction may not hold for this sensory system. (shrink)

The indiscernibility of identicals is incompatible with geach's theory of 'relative' identity, But consistent with the view that x is identical with y iff x is the same a as y, For some count-Noun 'a'. 'x is the same a as y' expresses identity only if x is an a, Otherwise it is merely an equivalence relation.