Are some cultures more mind-minded in their moral judgements than others?

Cross-cultural research on moral reasoning has brought to the fore the question of whether moral judgements always turn on inferences about the mental states of others. Formal legal systems for assigning blame and punishment typically make fine-grained distinctions about mental states, as illustrated by the concept of mens rea, and experimental studies in the USA and elsewhere suggest everyday moral judgements also make use of such distinctions. On the other hand, anthropologists have suggested that some societies have a morality that is disregarding of mental states, and have marshalled ethnographic and experimental evidence in support of this claim. Here, we argue against the claim that some societies are simply less ‘mind-minded’ than others about morality. In place of this cultural main effects hypothesis about the role of mindreading in morality, we propose a contextual variability view in which the role of mental states in moral judgement depends on the context and the reasons for judgement. On this view, which mental states are or are not relevant for a judgement is context-specific, and what appear to be cultural main effects are better explained by culture-by-context interactions.

Semantic diversity is best measured with unscaled vectors: Reply to Cevoli, Watkins and Rastle (2020)

Semantic diversity refers to the degree of semantic variability in the contexts in which a particular word is used. We have previously proposed a method for measuring semantic diversity based on latent semantic analysis (LSA). In a recent paper, Cevoli et al. (2020) attempted to replicate our method and obtained different semantic diversity values. They suggested that this discrepancy occurred because they scaled their LSA vectors by their singular values, while we did not. Using their new results, they argued that semantic diversity is not related to ambiguity in word meaning, as we originally proposed. In this reply, we demonstrate that the use of unscaled vectors provides better fits to human semantic judgements than scaled ones. Thus we argue that our original semantic diversity measure should be preferred over the Cevoli et al. version. We replicate Cevoli et al.’s analysis using the original semantic diversity measure and find (a) our original measure is a better predictor of word recognition latencies than the Cevoli et al. equivalent and (b) that, unlike Cevoli et al.’s measure, our semantic diversity is reliably associated with a measure of polysemy based on dictionary definitions. We conclude that the Hoffman et al. semantic diversity measure is better-suited to capturing the contextual variability among words and that words appearing in a more diverse set of contexts have more variable semantic representations. However, we found that homonyms did not have higher semantic diversity values than non-homonyms, suggesting that the measure does not capture this special case of ambiguity.

Collaborations and deceptions in strategic interactions revealed by hyperscanning fMRI

Despite its ubiquity, deceiving as a social phenomenon is scarcely addressed with fMRI, partly due to the spontaneity and individual differences in cheating, and the contextual variability that fosters lying. In this hyperscanning fMRI study, the participant pairs (n=33) from Taipei and Tainan joined an opening-treasure-chest (OTC) game, where the dyads took alternative turns as senders (to inform) and receivers (to decide) for guessing the right chest. The cooperation condition was achieved by, upon successful guessing, splitting the $200NTD trial reward, thereby promoting mutual trust. The competition condition, in contrast, was done by, also upon winning, the latter receivers taking all the $150NTD reward, thereby encouraging strategic interactions. One key fMRI finding was the negative correlations between the connectivity of the right temporo-parietal junction (rTPJ), known as the theory-of-mind function, and amygdala, parahippocampal gyrus, and rostral anterior cingulate (rACC), to senders' behavioral lying rates. Furthermore, the Multi-Voxel Pattern Analysis (MVPA) over multiple searchlight-identified Region-Of-Interests (ROIs), in classifying either the "truthful vs. lying in $150" or the "truthful in $200 vs. truthful in $150" conditions achieved 61% and 84.5% accuracy, respectively, reflecting the idiosyncratic brain networks involved in distinguishing the social trust vs. deceptions in the dyadic interactions.

Semantic diversity is best measured with unscaled vectors: Reply to Cevoli, Watkins and Rastle (2020)

Semantic diversity refers to the degree of semantic variability in the contexts in which a particular word is used. In 2013, we proposed a method for measuring semantic diversity based on latent semantic analysis (LSA) (Hoffman, Lambon Ralph, & Rogers, 2013). In a recent paper, Cevoli, Watkins and Rastle (2020) criticised our method, noting that we had failed to scale our LSA vectors by their singular values, which they considered to be a critical stage in the analysis. They presented new analyses using their own semantic diversity measure that included this step. In this reply, we demonstrate that the use of unscaled vectors provides better fits to human semantic judgements than scaled ones. Thus we argue that our original semantic diversity measure should be preferred over the Cevoli et al. version. We replicate Cevoli et al.’s analysis using the original semantic diversity measure and find (a) our original measure is a better predictor of word recognition latencies than the Cevoli et al. equivalent and (b) that, unlike Cevoli et al.’s measure, our semantic diversity is reliably associated with a measure of polysemy based on dictionary definitions. We conclude that the original Hoffman et al. semantic diversity measure is better-suited to capturing the contextual variability among words and that words appearing in a more diverse set of contexts have more variable semantic representations. However, we found that homonyms did not have higher semantic diversity values than non-homonyms, suggesting that the measure does not capture this special case of ambiguity.

CONCEPTUAL METAPHOR IN COGNITIVE-SEMIOTIC INTERPRETATION

The article presents an attempt to view the phenomenon of conceptual metaphor in the cognitive-semiotic aspect. The object of the study is the conceptual metaphor, the subject matter is its cognitive-semantic essence and the forms of its representation. The main thesis that forms the theoretical basis of the article is that the conceptual metaphor understood as the ability of our consciousness to think of one, more abstract entity in terms of another, more concrete, entity, presents a mental phenomenon that may have not only verbal, but other forms of its representation. The main objective of the article is to carry out the analysis of visual, artefact and ontological metaphors in the cognitive-semiotic aspect and the ways of their representation in the text. The main methods of analysis conditioned by the theoretical aspect chosen for analysis are introspection, or metacognition aimed at reconstructing the work of consciousness in the process of metaphorical thinking, and the inferential method aimed at reconstructing implicit metaphorical meanings. The analysis of visual (artistic), artifact and ontological metaphors reveals that they are characterized by the same qualities as verbal metaphors: dynamism, contextual variability and existence of two their varieties: trite metaphors which reflect ordinary thinking and original ones which are the product of artistic thinking. When ontological and artefact metaphors are presented in the text, their metaphorical meanings can be presented both explicitly and implicitly and, in the latter case, their metaphorical meanings must be inferred by the reader or the linguist. The participation of nonverbal codes in the expression of metaphorical meanings does not diminish the significance of the verbal code which is another proof of the leading role of language in conceptualization and interpretation of the world. The analysis undertaken enables to confirm the main thesis as well as to reveal the explanatory potential of the cognitive-semiotic approach to the study of metaphor and, most probably, other language phenomena.

Numerical Concepts in Context

Numerical concepts are an integral part of everyday conversation and communication. Expressions relating to numbers in natural language can have precise or imprecise interpretations. While the precise interpretation most prominently appears in mathematical contexts, the imprecise interpretation seems to arise when numbers (as quantities) are applied to real world contexts (e.g., the rope is 50 m long). Earlier literature shows that the (im)precise interpretation can depend on different factors, e.g., the kind of approximator a numeral appears with (precise vs. imprecise, e.g., exactly vs. roughly) or the kind of numeral itself (round vs. non-round, e.g., 50 vs. 47). We report on a corpus-linguistic study and a rating experiment of English numerical expressions. The results confirm the effects of both factors and additionally an effect of the kind of unit (discrete vs. continuous, e.g., people vs. meters). This shows the contextual variability in the interpretation of numerical concepts in natural language.

Analogizing

Multicontextual exampling implies a comparative perspective. Yet while comparativists conventionally emphasize cross-contextual variability, generic sociologists try to reveal cross-contextual commonality. Given its transcontextual agenda, it is the quest to uncover formal “parallels” between substantively disparate phenomena that characterizes generic sociology. In sharp contrast to sociologists’ conventional tendency to highlight differences between substantively disparate situations, it regards the latter as but various manifestations of the same transcontextual pattern. While diversifying the contexts in which they collect their data, generic sociologists thus try to identify common formal patterns across substantively diverse contexts. This chapter examines the mental process by which we uncover formal “parallels” across seemingly disparate contexts, namely analogizing. When analogizing, one disregards conventionally noted substantive differences in order to notice conventionally disregarded formal equivalences. The chapter features the four main types of cross-contextual analogies (cross-cultural, cross-historical, cross-domain, and cross-level) generic sociologists use in their analyses.

Classifying literary genres

Classifying literary genres has always been methodologically confined to philological methods and what is commonly known as Vector Space Clustering (VSC). The problem has been exasperated with the widening gap between computational theory and traditional analysis of literary texts. Towards finding a solution to this problem, the current study utilizes a synergetic approach that brings together two established methods. First, a computational model of genre classification is drawn upon for identifying concept-based, rather than word-bound, topics, where the representation of texts is secured via the ‘bag of concepts’ (BOC) model as well as the sense-restricted knowledge and meaningful links holding between and among concepts; relatedly, the two model strands of explicit semantic analysis (ESA) and ConceptNet have enacted text classification. Second, a contextual lexical semantic approach (CRUSE, 1986, 2000) is employed so that the contextual variability of word meanings and concepts can be tackled within the confines of the target literary genres classified. The findings of present study have shown that the current composite approach of computational and semantic models has resulted in improved performance in classifying literary genres, especially with respect to delineating the links between each cluster’s document-members and generalizing about their unifying genre. Further implications have emerged from the present study, namely, the benefits reserved for digital libraries and the process of archiving, where literary-text classification has proven problematic to both users and readers in many cases.

Impact of an Individualized Cognitive Training Intervention in Preschoolers from Poor Homes

Over the last few decades, different interventions were shown to be effective in changing cognitive performance in preschoolers from poor homes undertaking tasks with executive demands. However, this evidence also showed that not all children included in the intervention groups equally increased their performance levels, which could be related to individual and contextual variability. The present study aimed to explore the impact of a computerized cognitive training intervention with lab-based tasks in preschoolers from Unsatisfied Basic Needs (UBN) homes under the consideration of their baseline performance. In the context of a randomized controlled trial design, different interventions were administered to children according to their baseline performance in a variety of cognitive tasks (i.e., executive attention, inhibitory control, working memory, and planning demands). The results showed different patterns of impact on performance depending on the experimental group, supporting the importance of considering individual and contextual differences in the design of interventions aimed at optimizing executive functions in poverty-impacted sample populations in early stages of development.