@article{HildebrandtGlauerKachel, author = {Hildebrandt, Frauke and Glauer, Ramiro and Kachel, Gregor}, title = {Coming from a world without objects}, series = {Mind \& Language}, volume = {37}, journal = {Mind \& Language}, number = {2}, publisher = {Wiley Blackwell Publishing Ltd}, address = {Oxford, UK}, doi = {10.1111/mila.12313}, url = {http://nbn-resolving.de/urn:nbn:de:kobv:525-25000}, pages = {159 -- 176}, abstract = {While research on object individuation assumes that even very young children are able to perceive objects as particulars, we argue that the results of relevant studies can be explained in terms of feature discrimination. We propose that children start out navigating the world with a feature-based ontology and only later become able to individuate objects spatiotemporally. Furthermore, object individuation is a cognitively demanding achievement resting on a uniquely human form of enculturation, namely the acquisition of deictic demonstratives. We conclude by outlining empirical expectations for operationalizations of our proposal.}, language = {en} } @article{HildebrandtGlauerMoore, author = {Hildebrandt, Frauke and Glauer, Ramiro and Moore, Richard}, title = {Rethinking how children individuate objects}, series = {Synthese}, volume = {202}, journal = {Synthese}, number = {3}, publisher = {Springer Nature}, address = {Berlin}, issn = {0039-7857}, doi = {10.1007/s11229-023-04300-5}, pages = {1 -- 25}, abstract = {The current understanding of cognitive development rests on the premise that infants can individuate objects early on. However, the so-called object-first account faces severe difficulties explaining extant empirical findings in object individuation tasks while alternative, more parsimonious explanations are available. In this paper, we assume that children start as feature-thinkers without being able to individuate objects and show how this ability can be learned by thinkers who do not already implicitly possess the notion of an object. Based on Tugendhat's ideas on the relation between singular terms and object reference, we argue that spatial indexicals comprise the fundamental means of object individuation and describe how feature thinkers might acquire the complex substitutional system of spatial indexicals. In closing, two accounts of object cognition that do not rely on symbolic capacities, namely Pylyshyn's FINST indexes and Burge's perceptual objectivity, are critically discussed.}, subject = {Kind}, language = {en} } @article{HildebrandtLonnemannGlauer, author = {Hildebrandt, Frauke and Lonnemann, Jan and Glauer, Ramiro}, title = {Why Not Just Features? Reconsidering Infants' Behavior in Individuation Tasks}, series = {Frontiers in Psychology}, volume = {11}, journal = {Frontiers in Psychology}, number = {Okt.}, publisher = {Frontiers Media S.A.}, address = {Lausanne}, issn = {1664-1078}, doi = {10.3389/fpsyg.2020.564807}, url = {http://nbn-resolving.de/urn:nbn:de:kobv:525-24896}, pages = {9}, abstract = {It counts as empirically proven that infants can individuate objects. Object individuation is assumed to be fundamental in the development of infants' ontology within the object-first account. It crucially relies on an object-file (OF) system, representing both spatiotemporal ("where") and categorical ("what") information about objects as solid, cohesive bodies moving continuously in space and time. However, infants' performance in tasks requiring them to use featural information to detect individuation violations appears to be at odds with the object-first account. In such cases, infants do not appear to be able to develop correct expectations about the numerosity of objects. Recently, proponents of the object-first account proposed that these individuation failures result from integration errors between the OF system and an additional physical reasoning system. We are going to argue that the predictions of a feature-based physical-reasoning (PR) system are sufficient for explaining infants' behavior. The striking predictive power of the PR system calls into question the relevance of the OF system and, thereby, challenges the assumption that infants can individuate objects early on.}, subject = {Individuation}, language = {en} } @article{HildebrandtMusholt, author = {Hildebrandt, Frauke and Musholt, Kristina}, title = {Teaching rationality : sustained shared thinking as a means for learning to navigate the space of reasons}, series = {Journal of Philosophy of Education}, volume = {54}, journal = {Journal of Philosophy of Education}, number = {3}, publisher = {Wiley-Blackwell}, address = {Malden, Mass.}, issn = {1467-9752}, doi = {10.1111/1467-9752.12407}, pages = {582 -- 599}, abstract = {Human thought can be characterised as being situated in the 'space of reasons'. That is to say that human thought is guided by the norms of theoretical and practical rationality which, in turn, enable autonomous thinking. But how do children learn to navigate the space of reasons? Building on the work of Tugendhat and Bakhurst, among others, we argue, first, that this process involves the acquisition of propositional thought and that it is an essentially social one in which both children and adults take an active role. Second, and more specifically, by drawing on Brandom's theory of meaning, we provide a philosophical analysis of empirical findings with respect to the efficacy of 'Sustained Shared Thinking' (SST) in early educational settings. We argue that the efficacy of SST is based on its emphasising, modelling and practising those elements of communication that are essential for gaining proficiency in 'playing the game of giving and asking for reasons', namely drawing inferences between propositions and concepts and providing justifications for one's assertions. This is achieved by making explicit the inferential relationships between concepts and propositions and by the use of modal and doxastic markers that function as an invitation to a joint search for reasons.}, subject = {Denken}, language = {en} } @article{HoeyMacKinnonSchroeder, author = {Hoey, Jesse and MacKinnon, Neil J. and Schr{\"o}der, Tobias}, title = {Denotative and connotative management of uncertainty}, series = {Judgment and Decision Making}, volume = {16}, journal = {Judgment and Decision Making}, number = {2}, publisher = {Society for Judgment and Decision Making}, issn = {1930-2975}, doi = {10.1017/S1930297500008652}, pages = {505 -- 550}, abstract = {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.}, subject = {Zwei-Prozess-Modell}, language = {en} } @techreport{HoeyNagappanRogersetal., author = {Hoey, Jesse and Nagappan, Meiyappan and Rogers, Kimberly B. and Schr{\"o}der, Tobias and Dametto, Diego and De Zoysa, Nalin and Iyer, Rahul and Morgan, Jonathan H. and Rishi, Deepak and Sirianni, Antonio D. and Yun, Seonghu and Zhao, Jun and Z{\"o}ller, Nikolas}, title = {Theoretical and Empirical Modeling of Identity and Sentiments in Collaborative Groups}, doi = {10.31235/osf.io/4hukx}, pages = {1 -- 36}, abstract = {Theoretical and Empirical Modeling of Identity and Sentiments in Collaborative Groups (THEMIS.COG) was an interdisciplinary research collaboration of computer scientists and social scientists from the University of Waterloo (Canada), Potsdam University of Applied Sciences (Germany), and Dartmouth College (USA). This white paper summarizes the results of our research at the end of the grant term. Funded by the Trans-Atlantic Platform's Digging Into Data initiative, the project aimed at theoretical and empirical modeling of identity and sentiments in collaborative groups. Understanding the social forces behind self-organized collaboration is important because technological and social innovations are increasingly generated through informal, distributed processes of collaboration, rather than in formal organizational hierarchies or through market forces. Our work used a data-driven approach to explore the social psychological mechanisms that motivate such collaborations and determine their success or failure. We focused on the example of GitHub, the world's current largest digital platform for open, collaborative software development. In contrast to most, purely inductive contemporary approaches leveraging computational techniques for social science, THEMIS.COG followed a deductive, theory-driven approach. We capitalized on affect control theory, a mathematically formalized theory of symbolic interaction originated by sociologist David R. Heise and further advanced in previous work by some of the THEMIS.COG collaborators, among others. Affect control theory states that people control their social behaviours by intuitively attempting to verify culturally shared feelings about identities, social roles, and behaviour settings. From this principle, implemented in computational simulation models, precise predictions about group dynamics can be derived. It was the goal of THEMIS.COG to adapt and apply this approach to study the GitHub collaboration ecosystem through a symbolic interactionist lens. The project contributed substantially to the novel endeavor of theory development in social science based on large amounts of naturally occurring digital data.}, subject = {Computational social science}, language = {en} } @article{HoeySchroeder, author = {Hoey, Jesse and Schr{\"o}der, Tobias}, title = {Disruption of Social Orders in Societal Transitions as Affective Control of Uncertainty}, series = {American behavioral scientist}, volume = {67}, journal = {American behavioral scientist}, number = {2}, publisher = {Sage Publ.}, address = {Thousand Oaks}, issn = {1552-3381}, doi = {10.1177/00027642211066055}, pages = {311 -- 331}, abstract = {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.}, language = {en} } @article{HoeySchroederMorganetal., author = {Hoey, Jesse and Schr{\"o}der, Tobias and Morgan, Jonathan Howard and Rogers, Kimberly B. and Rishi, Deepak and Nagappan, Meiyappan}, title = {Artificial Intelligence and Social Simulation}, series = {Small Group Research}, volume = {49}, journal = {Small Group Research}, number = {6}, publisher = {Sage Publications}, address = {London}, issn = {1552-8278}, doi = {10.1177/1046496418802362}, pages = {647 -- 683}, abstract = {Recent advances in artificial intelligence and computer science can be used by social scientists in their study of groups and teams. Here, we explain how developments in machine learning and simulations with artificially intelligent agents can help group and team scholars to overcome two major problems they face when studying group dynamics. First, because empirical research on groups relies on manual coding, it is hard to study groups in large numbers (the scaling problem). Second, conventional statistical methods in behavioral science often fail to capture the nonlinear interaction dynamics occurring in small groups (the dynamics problem). Machine learning helps to address the scaling problem, as massive computing power can be harnessed to multiply manual codings of group interactions. Computer simulations with artificially intelligent agents help to address the dynamics problem by implementing social psychological theory in data-generating algorithms that allow for sophisticated statements and tests of theory. We describe an ongoing research project aimed at computational analysis of virtual software development teams.}, subject = {K{\"u}nstliche Intelligenz}, language = {en} } @inproceedings{ImaiSajiGrosseetal., author = {Imai, Mutsumi and Saji, Noburo and Große, Gerlind and Schulze, Cornelia and Asano, Michiko and Saalbach, Henrik}, title = {General mechanisms of color lexicon acquisition : insights from comparison of German and Japanese speaking children}, series = {Proceedings of the 42nd Annual Conference of the Cognitive Science Society}, booktitle = {Proceedings of the 42nd Annual Conference of the Cognitive Science Society}, organization = {Cognitive Science Society}, pages = {3315 -- 3320}, abstract = {This research investigated how German-speaking children learn color words, both in terms of centroid mappings and boundary delineation, and how they construct the color lexicon as a connected system. The results were compared to those of Japanese children to draw insights on general mechanisms that underlie the acquisition of words in the color lexicon. For both languages, input frequency and category size contributed to the ease of learning. In contrast, in both language groups, naming (in)consistency in adults predicted the adult-like boundary delineation.}, subject = {Kindersprache}, language = {en} } @article{KachelMooreTomasello, author = {Kachel, Gregor and Moore, Richard and Tomasello, Michael}, title = {Two-year-olds use adults' but not peers' points}, series = {Developmental Science}, volume = {21}, journal = {Developmental Science}, number = {5}, publisher = {Wiley-Blackwell}, address = {Oxford}, issn = {1467-7687}, doi = {10.1111/desc.12660}, abstract = {In the current study, 24- to 27-month-old children (N = 37) used pointing gestures in a cooperative object choice task with either peer or adult partners. When indicating the location of a hidden toy, children pointed equally accurately for adult and peer partners but more often for adult partners. When choosing from one of three hiding places, children used adults' pointing to find a hidden toy significantly more often than they used peers'. In interaction with peers, children's choice behavior was at chance level. These results suggest that toddlers ascribe informative value to adults' but not peers' pointing gestures, and highlight the role of children's social expectations in their communicative development.}, subject = {Kleinkind}, language = {en} }