Denmark

**Author(s):** Miton, H; Morin, O. &lt;br&gt;&lt;br&gt;Cattle brands (ownership marks left on animals) may be subject to forces influencing other graphic codes: the copying of constituent parts, pressure for distinctiveness (e.g. to distinguish a mark from its nearest neighbors), and pressure for complexity (e.g. to be harder to fake). The historical record of cattle brands in some US states is complete due to legal registration, providing a unique opportunity to assess how sampling processes leading to time- and space-averaging influence our ability to make inferences from limited datasets in fields like archaeology. In this preregistered study, we used a dataset of ~81,000 Kansas cattle brands (1990-2016) to explore two questions: (1) the relative influence of copying, distinctiveness, and complexity, and (2) the effects of time- and space- averaging on statistical signals. By conducting generative inference with an agent-based model, we found that the patterns in our data are consistent with random copying and pressure for intermediate complexity. In addition, by comparing mixed and structured datasets, we found that these statistical signals of random copying are robust to, and possibly boosted by, time- and space-averaging.

Cultural Evolution Society 2022

Distinctiveness, copying, and complexity in the cultural evolution of cattle brands

generative inference

random copying

graphic codes

archaeology

agent-based modeling

Computational creativity is the art, science, philosophy and engineering of computational systems which, by taking on particular responsibilities, exhibit behaviours that unbiased observers would deem to be creative. As a field of research, this area is thriving, with progress in formalising what it means for software to be creative, along with many exciting and valuable applications of creative software in the sciences, the arts, literature, gaming and elsewhere.

The ICCC conference series organized by the Association for Computational Creativity since 2010 is the only scientific conference that focuses on computational creativity alone and also covers all aspects of it.


ICCC'20

The ICCC conference series organized by the Association for Computational Creativity since 2010 is the only scientific conference that focuses on computational creativity alone and also covers all aspects of it.
Computational creativity is the art, science, philosophy and engineering of computational systems which, by taking on particular responsibilities, exhibit behaviors that unbiased observers would deem to be creative. As a field of research, this area is thriving, with progress in formalizing what it means for software to be creative, along with many exciting and valuable applications of creative software in the sciences, the arts, literature, gaming and elsewhere.



**Author(s):** Miton, H; Morin, O. Cattle brands (ownership marks left on animals) may be subject to forces influencing other graphic codes: the copying of constituent parts, pressure for distinctiveness (e.g. to distinguish a mark from its nearest neighbors), and pressure for complexity (e.g. to be harder to fake). The historical record of cattle brands in some US states is complete due to legal registration, providing a unique opportunity to assess how sampling processes leading to time- and space-averaging influence our ability to make inferences from limited datasets in fields like archaeology. In this preregistered study, we used a dataset of ~81,000 Kansas cattle brands (1990-2016) to explore two questions: (1) the relative influence of copying, distinctiveness, and complexity, and (2) the effects of time- and space- averaging on statistical signals. By conducting generative inference with an agent-based model, we found that the patterns in our data are consistent with random copying and pressure for intermediate complexity. In addition, by comparing mixed and structured datasets, we found that these statistical signals of random copying are robust to, and possibly boosted by, time- and space-averaging.

technical paper

### Welcome to the fourth Cultural Evolution Society Conference, CES2022! 

As last year, Underline will support the online component of the conference. The ongoing COVID-19 pandemic is causing a great deal of uncertainty for all of us. Therefore, we seek to offer a hybrid format that will hopefully allow some folks to travel to Aarhus, others to meet up locally or regionally in CES hub-lets, and other yet to participate online. The field of cultural evolution is growing in size and scope; its theories, methods and applications - both academic and applied - are getting ever more robust. Do join us in what promises to be an exciting exchange of ideas and a celebration of our field.

##### ***For SoMe interaction and live tweeting please tag @CulturalEvolSoc and use #CESconf2022***


#### The CES 2022 local organising committee
* Luseadra Joy McKerracher
* Jesper Sørensen 
* Niels Nørkjær Johannsen 
* Benjamin Grant Purzycki 
* Mette Løvschal 
* Felix Riede
* Iza Romanowska 
* Karsten Olsen

Please click on the button bellow if you want to watch the videos

The field of cultural evolution is growing in size and scope; its theories, methods and applications - both academic and applied - are getting ever more robust. Do join us in what promises to be an exciting exchange of ideas and a celebration of our field.

**Author(s):** Krajinovic, A; Rodrigues, X **Author(s):** No **Author(s):** No Linguistics has shown that the evolution of grammar follows a pattern known as grammaticalization, where structures evolve from more lexical and iconic meanings to more grammatical and abstract meanings. Lack of precise data on language transmission patterns presents an obstacle in understanding the factors that drive this grammaticalization process. In this talk, we argue that multimodal constructions such as internet memes follow a similar evolution pattern, and can thus provide a wealth of data on this phenomenon. We analyze twenty different memes, each consisting of an image macro with or without text. We use the number of browser searches, provided by Google Analytics, as a proxy for the time-dependent transmission rate of each meme. We then collect information on the date, format and semantic change over time of a sample of meme instances shared on Twitter and Reddit. We show that statistically, wider transmission leads to a higher rate of semantic change in the direction of higher abstraction. We also show that the memes go through stages parallel to grammaticalization, such as use in new contexts, semantic bleaching, erosion, and decategorialization, and that these stages follow the same temporal ordering across memes (see our example at https://bit.ly/3a4JFbk). Social networks can therefore provide a valuable lab for the study of communication patterns and language evolution.

From iconic pictures to “grammatical” templates: Modeling the evolution of internet memes

**Author(s):** Sebire, I; Camargo, C; Introduction: Popular media plays a significant role in shaping and reflecting culture and society. In this paper, we investigate patterns in the use of recurring storytelling devices, i.e. common tropes, in popular media. Examples of tropes include the "mad scientist", "villain wearing a dark palette", or even "melancholic song playing during sad moment". Using a database of media tropes, we compare clusters of tropes with actual genre classifications, and study the differences in media through geography and time. Methods: This study uses a dataset collected from TVTropes, a wiki-format crowdsourced website describing tropes in popular media. We apply approaches from cultural evolution along with data science methods such as topic modelling, sentence embedding, and stochastic block models, to simultaneously cluster tropes and the works they feature in. # Results & Discussion: We show the applicability of the nonparametric stochastic block model-based topic model topSBM to identify a hierarchy of genres and subgenres, as well a hierarchy of storytelling tropes present in the data over time. We end by discussing the strengths and limitations of machine learning in cultural evolution.

Genres, subgenres, and storytelling tropes: a data science approach

**Author(s):** Erben Johansson, Niklas; Cronhamn, Sandra Intuitive, iconic associations between sound and meaning in grammaticalized linguistic units are poorly understood. Relatedly, the grammatical classification of nouns cross-linguistically involves semantic categories, e.g. sex, animacy and physical properties, which are usually iconic. This study investigates vocal iconicity in nominal classification systems in half of the world’s language families, consisting of 210 non-agreeing (e.g. classifier) and 151 agreeing (e.g. grammatical gender) systems. By analyzing the semantic scopes of the nominal classes and contained speech sounds through Bayesian mixed models, we assessed which sounds were overrepresented in which class meanings. The strongest overrepresentations were found in shape and size categories, but iconic effects were restricted to non-agreeing systems. Consequently, vocal iconicity is present on a grammatical level cross-linguistically, but only in semantically transparent nominal classes. These results indicate that the fundamental semantic properties of nouns can iconically influence how linguistic structure develops over time and help explain how language users categorize and conceptualize the world.

Vocal iconicity in nominal classification: How semantic properties can influence linguistic structure

**Author(s):** Sheard, C; Bowern, C; Jordan, F M Introduction: Human kinship systems, or how different cultural groups use language to classify family members, show remarkable global diversity, but they also seem to be constrained by social and cognitive limits. It is common within anthropology, for example, for kinship systems to be categorised into a mere six typologies, based on a few axes of variation in cousin terms. Despite the importance of kinship in structuring human society, however, there has been little work examining the cross-cultural drivers of, and constraints on, this diversity, and most of this scholarship has been limited to a handful of well-documented language families. Materials and Methods: Here, we present a survey of kinship systems in 71 Pama-Nyungan languages, representing all major branches of the largest Australian language family. We first describe the macroevolutionary dynamics of Pama-Nyungan kinship and test for evidence of stable kinship typologies. We then test hypotheses related to how social practice and spatial variables shape kinship systems. Results: We find only weak support for any clustering of languages by kinship system or for specific holes within the observed volume of kinship space, instead demonstrating that these ethnolinguistic groups’ kinship systems have evolved steadily over the past ~ 6,000 years. We find that community marriage norms, but not post-marital residency, correlate with kinship system. Furthermore, though we find evidence of spatial autocorrelation in the data above and beyond the effect of shared phylogenetic history, we find that spatial similarity in kinship systems is better explained by a correlation between kinship and the physical environment. Conclusions: By applying modern phylogenetic comparative methods to the study of language-culture coevolution, we thus demonstrate the importance of moving beyond traditional typological comparisons in the study of kinship, as well as caution against assuming the universal applicability of cultural evolution trends across all geographic and linguistic contexts.

Social practice and physical environment shape Pama-Nyungan kinship macroevolution, but not into stable typologies

**Author(s):** Deffner, D; Mezey, D; Wu, C; Schakowski, A; Kahl, B; Romanczuk, P; Kurvers, R Introduction: A fundamental challenge in collective problem solving is the dynamic integration of individual and social information. Previous theory has shown that social learning needs to be selective in order to be adaptive, yet it is still largely unknown how agents collectively negotiate this balance. Methods: We investigate these trade-offs in the context of collective foraging (collecting spatially distributed resources) and present novel agent-based simulations and human foraging experiments in a virtual world. This immersive environment creates a natural trade-off between individual search and social learning and provides spatial trajectories as well as visual field data that we analyze through Bayesian computational modeling. Results: Simulation results show how different amounts of social learning maximize collective returns depending on the structure of the environment and visual constraints. Experiments revealed that people copy selectively and can adapt social learning to the demands of the physical and social environment. Discussion: Our results shed new light on how groups collectively adapt to the demands of the environment through exploration and selective imitation.

Selective social learning in collective foraging

 Transient diversity in a cooperative group involves the maintenance of diverse solutions while the group attempts to reach a consensus. I argue that any mechanism that slows diffusion and delays consensus will increase the quality of solution at the cost of increased time to reach it. I further argue that this is a general principle analogous to the role of positive assortment in the evolution of cooperation. Several processes facilitate the evolution of cooperation—kin selection, direct reciprocity, indirect reciprocity, group structure, partner choice—but all these do so by directing the benefits of cooperation toward cooperative individuals. I review specific mechanisms that facilitate transient diversity, synthesizing evidence from both empirical studies and diverse formal models—multi-armed bandits, NK landscapes, cultural attractors, cumulative innovation models, and evolutionary transmission models—to support my argument. Apparent exceptions this principle occur only when problems are sufficiently simple that they can be solved by mere trial and error. This work has implications for the cultural evolution of teams, population structures, and the accumulation of innovations.

Maintaining transient diversity is a general principle for improving collective problem solving

**Author(s):** Lightner, AD; Heckelsmiller, C; Hagen, EH Religious specialists invoke the supernatural while healing illnesses. We investigated such specialists in two studies. Study 1 analyzed medicinal specialists in 47 cultures in the Human Relations Area Files. We found specialists with supernatural theories in 74% of texts, often fulfilling practical, transactional roles for a clientele whose patronage hinges on expectations of efficacious treatment. Study 2 interviewed Tanzanian Maasai medicinal specialists and their clientele (N=84). We found that in the event of illness clients mainly selected specialists based on efficacy and religious identity. Participants also explained how medicinal plants work with highly abstract concepts that were not conspicuously supernatural. We review these findings and propose that, in many cases, (1) supernatural theories of disease are useful, abstract falsehoods that help explain complex and uncertain processes, such as illness; (2) specialists use these falsehoods to assist their clientele in a mutually beneficial exchange of services for resources; and (3) “religious” clients defer to specialists in a market, where patronage is conditional on effective solutions to uncertain and serious problems.

Supernatural theories of disease: Useful falsehoods in a market for specialists

Introduction: Cultural evolution of norm psychology holds that groups first evolved norms regulating interpersonal behaviors. Second, individuals in groups with stable prosocial norms evolved norm psychology helping with internalization of such norms. I argue that perception of moral norms as absolute and universal is internal part of norm psychology and test three hypotheses derived from such reasoning. Methods: I utilized data from Pew, FBI crime records, WVS, and NSYR (National Study of Youth and Religion) and hierarchical regression framework. The Pew and FBI data served to test the association between % of moral absolutists in the US state and crime rates per 100K (H1 group benefits). WVS data were used to test whether moral absolutists justify norm transgressions less than relativists (H2 norm compliance). NSYR data allowed me to test relationship between moral relativism and likelihood of being jailed, arrested, and found guilty (H3 individual benefits). Results and conclusion: I found mixed support for the hypotheses which is in conflict with clear results from controlled experiments highlighting the importance of observational data in the study of norm psychology evolution.

Moral absolutism as a component of norm psychology: The relationship between moral perception and compliance with norms

**Author(s):** Jansson F; Aguilar E; Acerbi A; Buskell A; Enquist M Introduction: Cultural traits are embedded in webs of relations and sequentially acquired and evaluated – filtered – in light of previously acquired traits. Incorporating multiple traits and their relations is needed to understand the organisation, dynamics, and emergent products of cultural evolution. Approach: We introduce a modelling framework of individual filtering of interdependent traits and explore the effects on cultural transmission and emergent phenomena, through mathematical treatment and simulations. Findings: Sequential acquisition of compatible traits leads to culturally evolved filters. These organise culture into mostly consistent and stable systems. Depending on the structure of trait relations, they modulate rates of cultural change, exhibit path dependence and punctuated equilibria, and can generate convergent transmission, clustering and polarisation. Discussion: A systems view of culture can give a fuller understanding of the source and character of emergent phenomena. It increases the scope of cultural evolution, whereby faithful transmission, self-organisation and filters can be accounted for by systems dynamics without strong assumptions on innate machinery.

Modelling Cultural Systems and Selective Filters

Demonstrating how individual-level cultural transmission scales up to produce population-level social norms is one of cultural evolution’s evergreen challenges. Spoiler: This talk does not solve that challenge. Happily, even small steps towards understanding the interplay between micro and macro scales are useful. I focus my discussion on kinship terminologies, which are the patterns of words that languages have for denoting and referring to family members. Our systems of reckoning relatives vary cross-culturally, and the structural features of these norms persist and recur across the globe. In some languages, siblings are distinguished by age; in others by gender; by both aspects; or not at all. The women I call my ‘aunty’ in one society might be called ‘mother’ in another. I present collaborative work from a team project that explores terminologies as a product of cultural evolutionary processes shaped by cognitive and interactional constraints. Observations from Datooga-speaking children and their families demonstrates the contexts of individual transmission and learning of kinship terms, while phylogenetic analyses explore functional explanations for the persistence of patterned structural systems across languages. Reconciling these scales might be too grandiose an aim, but the effort helps us consider the relationship between language and culture, as well as the status of “shared ancestry” as an explanation.

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From iconic pictures to “grammatical” templates: Modeling the evolution of internet memes

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Utilizing Agent-Based Modeling to Quantify Robustness in Design Teams With Respect to Cognitive Style

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