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Charlemagne’s Legacy
(2023)
We investigate between- and within-country consensus about affective meanings of social identities along the evaluation, potency, and activity dimensions from the affect control theory research tradition. Ratings for 387 (194 male and 193 female) identities were collected from two samples representative of the French (N = 700) and German (N = 700) populations for age, gender, and region. Guided by two preregistered hypotheses based on previous cross-cultural research, our analysis points to considerable cultural consensus between French and Germans who seem to share a common “Carolingian” affective culture; yet some culture-specific patterns concerning the evaluation dimension and evaluation-potency interactions were found to be statistically significant. We interpret these results in terms of known cross-cultural features such as power distance and conceptions of power.
Understanding how individual or group behaviour are influenced by the presence of others is something both social psychology and agent-based social simulation are concerned with. However, there is only limited overlap between these two research communities, which becomes clear when terms such as “variable”, “prediction”, or “model” come into play, and we build on their different meanings. This situation challenges us when working together, since it complicates the uptake of relevant work from each community and thus hampers the potential impact that we could have when joining forces.
Bayesian affect control theory is a model of affect-driven social interaction underconditions of uncertainty. In this paper, we investigate how the operationalization of uncertainty in the model can be related to the disruption of social orders—societal pressures to adapt to ongoing environmental and technological change. First, we study the theoretical tradeoffs between three kinds of uncertainty as groups navigate external problems: validity (the predictability of the environment, including of other agents), coherence (the predictability of interpersonal affective dynamics), and dependence (the predictability of affective meanings). Second, we discuss how these uncertainty tradeoffs are related to contemporary political conflict and polarization in the context of societal transitions. To illustrate the potential of our model to analyze the socio-emotional consequences of uncertainty, we present a simulation of diverging individual affective meanings of occupational identities under uncertainty in a climate change mitigation scenario based on events in Germany. Finally, we sketch a possible research agenda to substantiate the novel, but yet mostly conjectural, ideas put forward in this paper.
Coaching can be understood as a process of creating meaning through linguistic interaction. Meanings are coherent networks of concepts, which are on the one hand socially shared and on the other hand based on the emotional experience of individuals. We present the relevant current state of research in cognitive science and social psychology and explain the significance of this research for coaching practice using the example of a coaching model established on the market (“contextual coaching”).
We compared event-related potentials during sentence reading, using impression formation equations of a model of affective coherence, to investigate the role of affective content processing during meaning making. The model of Affect Control Theory (ACT; Heise, 1979, 2007) predicts and quantifies the degree to which social interactions deflect from prevailing social norms and values - based on the affective meanings of involved concepts. We tested whether this model can predict the amplitude of brain waves traditionally associated with semantic processing. To this end, we visually presented sentences describing basic subject-verb-object social interactions and measured event-related potentials for final words of sentences from three different conditions of affective deflection (low, medium, high) as computed by a variant of the ACT model (Schröder, 2011). Sentence stimuli were closely controlled across conditions for alternate semantic dimensions such as contextual constraints, cloze probabilities, co-occurrences of subject-object and verb-object relations. Personality characteristics (schizotypy, Big Five) were assessed to account for individual differences, assumed to influence emotion-language interactions in information processing. Affective deflection provoked increased negativity of ERP waves during the P2/N2 and N400 components. Our data suggest that affective incoherence is perceived as conflicting information interfering with early semantic processing and that increased respective processing demands – in particular in the case of medium violations of social norms - linger on until the N400 time window classically associated with the integration of concepts into embedding context. We conclude from these results that affective meanings influence basic stages of meaning making.
The idea that a simple execution of an innovation invented by actors other than those who are expected to apply it is not likely to take place is a truism. We assume, however, in this paper the idea of a discursive production of knowledge on the application of an innovation across different levels of the education system. We aim to shed light on an innovation’s ‘journey’ from educational policy over training providers to teams of professionals in early childhood education and care (ECEC). By investigating knowledge and emotions associated with the introduction of an intended innovation using the example of “stimulation interactions” in day care-centers, the paper contributes to research on the transfer of innovations in education. To better understand challenges occurring during the transfer of innovations, we triangulate methods from discourse theory (coding techniques based on GTM) and cognitive science, namely cognitive-affective mapping (according to the scholarly conventions). The data corpus includes educational plans (N = 2), in-service training programs (N = 123) and group discussions of pedagogical teams (N = 6) who participated in an in-service training on the subject, stimulating interaction. Findings underline that similar messages from the inventors on the educational policy level are received and processed heterogeneously by the teams of pedagogues as a result of their preexisting views, routine practices and experiences with intended innovations through in-service trainings. Besides, a diffuse mixture of competing and contradictory information is communicated to the professionals and, hence, collides with the in-service training providers’ and educational policy actors’ expectations on the processing of the intended innovation. Specific knowledge elements and their valences are diametrically opposed to each other. Dissonances like these are considered as obstacles to social innovation. The obstacles are caused by the lack of a ‘common language’ beyond all levels. Hence, policy-makers and in-service-training providers should anticipate the supportive as well as competing knowledge-emotional complexes of professionals and take these into account when communicating an intended innovation.
This paper studies the dynamics of identity and status management within groups in collaborative settings. We present an agent-based simulation model for group interaction rooted in social psychological theory. The model integrates affect control theory with networked interaction structures and sequential behavior protocols as they are often encountered in task groups. By expressing status hierarchy through network structure, we build a bridge between expectation states theory and affect control theory, and are able to reproduce central results from the expectation states research program in sociological social psychology. Furthermore, we demonstrate how the model can be applied to analyze specialized task groups or sub-cultural domains by combining it with empirical data sources. As an example, we simulate groups of open-source software developers and analyze how cultural expectations influence the occupancy of high status positions in these groups.
The interplay between intuitive and deliberative processing is known to be important for human decision making. As independent modes, intuitive processes can take on many forms from associative to constructive, while deliberative processes often rely on some notion of decision theoretic rationality or pattern matching. Dual process models attempt to unify these two modes based on parallel constraint networks or on socially or emotionally oriented adjustments to utility functions. This paper presents a new kind of dual process model that unifies decision theoretic deliberative reasoning with intuitive reasoning based on shared cultural affective meanings in a single Bayesian sequential model. Agents constructed according to this unified model are motivated by a combination of affective alignment (intuitive) and decision theoretic reasoning (deliberative), trading the two off as a function of the uncertainty or unpredictability of the situation. The model also provides a theoretical bridge between decision-making research and sociological symbolic interactionism. Starting with a high-level view of existing models, we advance Bayesian Affect Control Theory (BayesACT) as a promising new type of dual process model that explicitly and optimally (in the Bayesian sense) trades off motivation, action, beliefs and utility. We demonstrate a key component of the model as being sufficient to account for some aspects of classic cognitive biases about fairness and dissonance, and outline how this new theory relates to parallel constraint satisfaction models.
This paper describes a novel emotionally intelligent cognitive assistant to engage and help older adults with Alzheimer’s disease (AD) to complete activities of daily living (ADL) more independently. Our new system combines two research streams. First, the development of cognitive assistants with artificially intelligent controllers using partially observable Markov decision processes (POMDPs). Second, a model of the dynamics of emotion and identity called Affect Control Theory that arises from the sociological literature on culturally shared sentiments. We present background material on both of these research streams, and then demonstrate a prototype assistive technology that combines the two. We discuss the affective reasoning, the probabilistic and decision-theoretic reasoning, the computer-vision based activity monitoring, the embodied prompting, and we show results in proof-of-concept tests.
Emotion theory needs to explain the relationship of language and emotions, and the embodiment of emotions, by specifying the computational mechanisms underlying emotion generation in the brain. We used Chris Eliasmith’s Semantic Pointer Architecture to develop POEM, a computational model that explains numerous important phenomena concerning emotions, including how some stimuli generate immediate emotional reactions, how some emotional reactions depend on cognitive evaluations, how bodily states influence the generation of emotions, how some emotions depend on interactions between physiological inputs and cognitive appraisals, and how some emotional reactions concern syntactically complex representations. We contrast our theory with current alternatives, and discuss some possible applications to individual and social emotions.
Belief systems matter for all kinds of human social interaction. People have individual cognitions and feelings concerning processes in their environment, which is why they may evaluate them differently. Belief systems can be visualized with cognitive-affective maps (CAMs; as reported by Thagard (in: McGregor (ed) EMPATHICA: A computer support system with visual representations for cognitive-affective mapping, AAAI Press, CA, 2010)). However, it is unclear whether CAMs can be constructed in an intersubjective way by different researchers attempting to map the beliefs of a third party based on qualitative text data. To scrutinize this question, we combined qualitative strategies and quantitative methods of text and network analysis in a case study examining belief networks about participation. Our data set consists of 10 sets of two empirical CAMs: the first CAM was created based on participants’ freely associating concepts related to participation in education (N = 10), the second one was created based on given text data which the participants represented as a CAM following a standardized instruction manual (N = 10). Both CAM-types were compared along three dimensions of similarity (network similarity, concept association similarity, affective similarity). On all dimensions of similarity, there was substantially higher intersubjective agreement in the text-based CAMs than in the free CAMs, supporting the viability of cognitive affective mapping as an intersubjective research method for studying the emotional coherence of belief systems and discursive knowledge. In addition, this study highlights the potential for identifying group-level differences based on how participants associate concepts.
Coaching lässt sich als ein Prozess der Bedeutungsschaffung durch sprachliche Interaktion verstehen. Bedeutungen sind kohärente Begriffsnetzwerke, die zum einen sozial geteilt, zum anderen im emotionalen Erleben von Personen fundiert sind. Wir stellen den aktuellen Forschungsstand in der Kognitionswissenschaft und Sozialpsychologie dar und erläutern am Beispiel eines am Markt etablierten Coaching-Modells („Contextuelles Coaching“) die Bedeutung dieser Forschung für die Coaching-Praxis.