It is well established that adults converge on common referring expressions in dialogue, and that such lexical alignment is important for successful and rewarding communication. The authors show that children with an autistic spectrum disorder (ASD) and chronological- and verbal-age-matched typically developing (TD) children also show spontaneous lexical alignment. In a card game, both groups tended to refer to an object using the same name as their partner had previously used for the same or a different token of the object. This tendency to align on a pragmatically conditioned aspect of language did not differ between ASD and TD groups, and was unaffected by verbal/chronological age, or (in the ASD group) Theory of Mind or social functioning. The authors suggest that lexical priming can lead to automatic lexical alignment in both ASD and TD children's dialogue. Their results further suggest that ASD children's conversational impairments do not involve an all-encompassing deficit in linguistic imitation. (PsycINFO Database Record

During dialogue, interlocutors align their situation models—cognitive representations of what they are currently discussing—and they do so by interacting. This chapter argues that alignment of situation models arises from interlocutors automatically aligning at other linguistic levels. It shows how this automatic alignment comes about from repeating each other’s choices of words, grammar, and meaning, and how alignment at one linguistic level percolates to alignment at other levels. After briefly reviewing the evidence for such alignment, the chapter considers how it relates to communicative success both cognitively and emotionally. Finally, it examines alternative social accounts of linguistic convergence processes (i.e. linguistic alignment) in relation to incidentally or strategically increasing social affiliation.

When speakers describe the world, they typically do so from their own perspective. However, they are able to adopt a different perspective, and sometimes do so even when they are not communicating with someone who has a different perspective from their own. In three experiments, we investigated the factors that might lead speakers to adopt a non-self perspective. Participants described how objects were located in scenes that contained no other entity, a person, or a symmetrical plant. They were more likely to adopt a non-self perspective (e.g., using to the left to refer to an object on their own right) if the scene contained a person facing them than a person facing away or a plant, and if it contained a person who could see (and potentially act on) the object than a person who could not, even when that person showed no intention to act. Our results suggest that speakers can put themselves in the shoes of another potential agent and use a simulation of that agent's perspective as the basis for formulating their descriptions.

In recent years behavioural science has quickly become embedded in national level governance. As the contributions of behavioural science to the UK's COVID-19 response policies in early 2020 became apparent, a debate emerged in the British media about its involvement. This served as a unique opportunity to capture public discourse and representation of behavioural science in a fast-track, high-stake context. We aimed at identifying elements which foster and detract from trust and credibility in emergent scientific contributions to policy making. With this in mind, in Study 1 we use corpus linguistics and network analysis to map the narrative around the key behavioural science actors and concepts which were discussed in the 647 news articles extracted from the 15 most read British newspapers over the 12-week period surrounding the first hard UK lockdown of 2020. We report and discuss (1) the salience of key concepts and actors as the debate unfolded, (2) quantified changes in the polarity of the sentiment expressed toward them and their policy application contexts, and (3) patterns of co-occurrence via network analyses. To establish public discourse surrounding identified themes, in Study 2 we investigate how salience and sentiment of key themes and relations to policy were discussed in original Twitter chatter (N = 2,187). In Study 3, we complement these findings with a qualitative analysis of the subset of news articles which contained the most extreme sentiments (N = 111), providing an in-depth perspective of sentiments and discourse developed around keywords, as either promoting or undermining their credibility in, and trust toward behaviourally informed policy. We discuss our findings in light of the integration of behavioural science in national policy making under emergency constraints.