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Canessa, E., & Chaigneau, S. (2014). The dynamics of social agreement according to Conceptual Agreement Theory. Qual. Quant., 48(6), 3289–3309.
Abstract: Many social phenomena can be viewed as processes in which individuals in social groups develop agreement (e.g., public opinion, the spreading of rumor, the formation of social and linguistic conventions). Conceptual Agreement Theory (CAT) models social agreement as a simplified communicational event in which an Observer and Actor exchange ideas about a concept , and where uses that information to infer whether 's conceptual state is the same as its own (i.e., to infer agreement). Agreement may be true (when infers that is thinking and this is in fact the case, event ) or illusory (when infers that is thinking and this is not the case, event ). In CAT, concepts that afford or become more salient in the minds of members of social groups. Results from an agent-based model (ABM) and probabilistic model that implement CAT show that, as our conceptual analyses suggested would be the case, the simulated social system selects concepts according to their usefulness to agents in promoting agreement among them (Experiment 1). Furthermore, the ABM exhibits more complex dynamics where similar minded agents cluster and are able to retain useful concepts even when a different group of agents discards them (Experiment 2). We discuss the relevance of CAT and the current findings for analyzing different social communication events, and suggest ways in which CAT could be put to empirical test.
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Canessa, E., Chaigneau, S. E., & Moreno, S. (2022). Using agreement probability to study differences in types of concepts and conceptualizers. Behav. Res. Methods, Early Access.
Abstract: Agreement probability p(a) is a homogeneity measure of lists of properties produced by participants in a Property Listing Task (PLT) for a concept. Agreement probability's mathematical properties allow a rich analysis of property-based descriptions. To illustrate, we use p(a) to delve into the differences between concrete and abstract concepts in sighted and blind populations. Results show that concrete concepts are more homogeneous within sighted and blind groups than abstract ones (i.e., exhibit a higher p(a) than abstract ones) and that concrete concepts in the blind group are less homogeneous than in the sighted sample. This supports the idea that listed properties for concrete concepts should be more similar across subjects due to the influence of visual/perceptual information on the learning process. In contrast, abstract concepts are learned based mainly on social and linguistic information, which exhibit more variability among people, thus, making the listed properties more dissimilar across subjects. Relative to abstract concepts, the difference in p(a) between sighted and blind is not statistically significant. Though this is a null result, and should be considered with care, it is expected because abstract concepts should be learned by paying attention to the same social and linguistic input in both, blind and sighted, and thus, there is no reason to expect that the respective lists of properties should differ. Finally, we used p(a) to classify concrete and abstract concepts with a good level of certainty. All these analyses suggest that p(a) can be fruitfully used to study data obtained in a PLT.
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Canessa, E. C., & Chaigneau, S. E. (2016). When are concepts comparable across minds? Qual. Quant., 50(3), 1367–1384.
Abstract: In communication, people cannot resort to direct reference (e.g., pointing) when using diffuse concepts like democracy. Given that concepts reside in individuals' minds, how can people share those concepts? We argue that concepts are comparable across a social group if they afford agreement for those who use it; and that agreement occurs whenever individuals receive evidence that others conceptualize a given situation similarly to them. Based on Conceptual Agreement Theory, we show how to compute an agreement probability based on the sets of properties belonging to concepts. If that probability is sufficiently high, this shows that concepts afford an adequate level of agreement, and one may say that concepts are comparable across individuals' minds. In contrast to other approaches, our method considers that inter-individual variability in naturally occurring conceptual content exists and is a fact that must be taken into account, whereas other theories treat variability as error that should be cancelled out. Given that conceptual variability will exist, our approach may establish whether concepts are comparable across individuals' minds more soundly than previous methods.
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Chaigneau, S. E., Canessa, E., Barra, C., & Lagos, R. (2018). The role of variability in the property listing task. Behav. Res. Methods, 50(3), 972–988.
Abstract: It is generally believed that concepts can be characterized by their properties (or features). When investigating concepts encoded in language, researchers often ask subjects to produce lists of properties that describe them (i.e., the Property Listing Task, PLT). These lists are accumulated to produce Conceptual Property Norms (CPNs). CPNs contain frequency distributions of properties for individual concepts. It is widely believed that these distributions represent the underlying semantic structure of those concepts. Here, instead of focusing on the underlying semantic structure, we aim at characterizing the PLT. An often disregarded aspect of the PLT is that individuals show intersubject variability (i.e., they produce only partially overlapping lists). In our study we use a mathematical analysis of this intersubject variability to guide our inquiry. To this end, we resort to a set of publicly available norms that contain information about the specific properties that were informed at the individual subject level. Our results suggest that when an individual is performing the PLT, he or she generates a list of properties that is a mixture of general and distinctive properties, such that there is a non-linear tendency to produce more general than distinctive properties. Furthermore, the low generality properties are precisely those that tend not to be repeated across lists, accounting in this manner for part of the intersubject variability. In consequence, any manipulation that may affect the mixture of general and distinctive properties in lists is bound to change intersubject variability. We discuss why these results are important for researchers using the PLT.
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Chaigneau, S. E., Canessa, E., & Gaete, J. (2012). Conceptual agreement theory. New Ideas Psychol., 30(2), 179–189.
Abstract: For some time now, psychological inquiry on reference has assumed that reference is achieved through causal links between words and entities (i.e., direct reference). In this view, meaning is not relevant for reference or co-reference. We argue that this view may be germane to concrete objects, but not to diffuse objects (that lack clear spatio-temporal limits, thus preventing the use of direct reference in interactions). Here, we propose that meaning is the relevant dimension when referring to diffuse entities, and introduce Conceptual Agreement Theory (CAT). CAT is a mathematized theory of meaning that specifies the conditions under which two individuals (or one individual at two points in time) will infer they share a diffuse referent. We present the theory, and use stereotype stability and public opinion as case studies to illustrate the theory's use and scope. (C) 2011 Elsevier Ltd. All rights reserved.
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Vera, J. (2018). An Agent-Based Model for the Role of Short-Term Memory Enhancement in the Emergence of Grammatical Agreement. Artif. Life, 24(2), 119–127.
Abstract: What is the influence of short-term memory enhancement on the emergence of grammatical agreement systems in multi-agent language games? Agreement systems suppose that at least two words share some features with each other, such as gender, number, or case. Previous work, within the multi-agent language-game framework, has recently proposed models stressing the hypothesis that the emergence of a grammatical agreement system arises from the minimization of semantic ambiguity. On the other hand, neurobiological evidence argues for the hypothesis that language evolution has mainly related to an increasing of short-term memory capacity, which has allowed the online manipulation of words and meanings participating particularly in grammatical agreement systems. Here, the main aim is to propose a multi-agent language game for the emergence of a grammatical agreement system, under measurable long-range relations depending on the short-term memory capacity. Computer simulations, based on a parameter that measures the amount of short-term memory capacity, suggest that agreement marker systems arise in a population of agents equipped at least with a critical short-term memory capacity.
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