Denmark

**Author(s):** Nilo M. Recalde, Ben C. Sheldon &lt;br&gt;&lt;br&gt;Population processes like dispersal, immigration and turnover play an essential role in evolution: they determine which individuals meet and reproduce and, as a result, shape the distribution of genetic diversity over space and time. By influencing when and which individuals interact, these processes also have the potential to affect traits that are culturally, rather than genetically, inherited, such as bird song. 


Teasing apart the relative contributions of population processes to the evolution of cultural traits is difficult, however, because it requires dense trait sampling and detailed individual life-history data—both notoriously hard to acquire in wild populations. To this end, we have built a multi-generational dataset containing the full song repertoires of hundreds of individuals in a population of great tits (Parus major) monitored extensively at Wytham Woods, UK. 


While simple at first impression, great tit songs are surprisingly diverse, and they give rise to a population-level cultural landscape that shifts continuously. Here, we take advantage of our long-term individual data and, using newly developed computational tools for studying large bird song datasets, show how demographic factors contribute to shaping local song diversity and complexity over multiple spatial and temporal scales.

Cultural Evolution Society 2022

Demography and cultural evolution in the wild: the landscape of diversity in bird song

bird song; non-human culture; cultural diversity; demography; bioacoustics

### Looking for Cogsci 2023? Please [click here](https://underline.io/events/405/reception) to switch to 2023 edition.


**Dear Colleagues,**

Welcome to the 43rd Annual Conference of the Cognitive Science Society! 

This year’s conference brings together the latest research from all Cognitive Science and also highlights this year’s theme **Comparative Cognition: Animal Minds.** 

The program features four plenary speakers: Friederike Range (University of Veterinary Medicine, Vienna), Onur Güntürkün (Ruhr University Bochum), Julia Fischer (University of Göttingen), and Erich Jarvis (The Rockefeller University). The keynotes and invited symposia showcase the broad spectrum of ideas that encompass the conference theme of comparative cognition. 

Further, the program includes the Rumelhart Prize keynote presentation by Susan Goldin-Meadow (University of Chicago), and symposia to celebrate the winner of the Elman Prize: Wei Ji Ma (New York University), the Heineken Award winner Robert Zatorre (McGill University), and the Robert J. Glushko Dissertation Prizes session.

The program committee for CogSci 2021 received 1,025 submissions, including 710 full papers, 275 member abstracts, 8 publication-based talks, as well as 15 proposals for symposia, and 17 for workshops and tutorials. After a rigorous review process, the committee selected 152 papers for oral presentation and inclusion in the conference proceedings (14.8%), 332 papers for poster presentation and inclusion in the proceedings (32.4%), and 175 papers for poster presentation with inclusion of abstracts in the proceedings (17.1%) We also selected 275 submitted member abstracts. In addition, we accepted 6 publication-based talks, 12 symposia, and 9 workshops and tutorials to make for an exciting and inclusive program.

We hope that you enjoy the conference this year! 

**Your Program Chairs,**
![](https://assets.underline.io/uploads/markdown_image/1/image/99984908caba5e6453e5fc5ba34f3507.jpg)

**Learn more about the Vienna Cognitive Science Hub at the University of Vienna, hosts of CogSci 2021**

<iframe width="560" height="315" src="https://www.youtube.com/embed/464h1m3iU68" title="YouTube video player" frameborder="0" allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture" allowfullscreen></iframe>

To review the proceedings for the conference or review the searchable program, please visit the [website](https://cognitivesciencesociety.org/program/).

CogSci 2021

The Cognitive Science Society brings together researchers from around the world who hold a common goal: understanding the nature of the human mind. The mission of the Society is to promote Cognitive Science as a discipline, and to foster scientific interchange among researchers in various areas of study, including Artificial Intelligence, Linguistics, Anthropology, Psychology, Neuroscience, Philosophy, and Education. The Society is a non-profit professional organization and its activities include sponsoring an annual conference and publishing the journals Cognitive Science and TopiCS.

**Author(s):** Nilo M. Recalde, Ben C. Sheldon Population processes like dispersal, immigration and turnover play an essential role in evolution: they determine which individuals meet and reproduce and, as a result, shape the distribution of genetic diversity over space and time. By influencing when and which individuals interact, these processes also have the potential to affect traits that are culturally, rather than genetically, inherited, such as bird song. 


Teasing apart the relative contributions of population processes to the evolution of cultural traits is difficult, however, because it requires dense trait sampling and detailed individual life-history data—both notoriously hard to acquire in wild populations. To this end, we have built a multi-generational dataset containing the full song repertoires of hundreds of individuals in a population of great tits (Parus major) monitored extensively at Wytham Woods, UK. 


While simple at first impression, great tit songs are surprisingly diverse, and they give rise to a population-level cultural landscape that shifts continuously. Here, we take advantage of our long-term individual data and, using newly developed computational tools for studying large bird song datasets, show how demographic factors contribute to shaping local song diversity and complexity over multiple spatial and temporal scales.

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.

 Introduction. The evolution of cooperation is a long-standing problem in evolutionary theory. However, cooperation is usually assumed to be genetically transmitted, despite evidence the prosocial behaviors are socially learned in humans as well as non-human animals (e.g., killer whales).

Cultural evolution of cooperation with non-vertical transmission

**Author(s):** Ammar, M; Fogarty, L; Kandler, A The ability to remember many cultural traits, and the context in which it is best to use them, is a clear feature of human cognition. However, this is rarely considered in models of the evolution of social learning. Without memory such models found that the benefit of innovation increases with environmental variability and social learning is most useful in stable environments. In our agent-based model, we investigate the interaction between memory and social learning and its implication for adaptation. With memory, agents can store information about traits they have learned and recall this later. The environment can change between time steps and agents use stored information to assess their traits in the current environment. Here ‘forgetting’ is a probabilistic process where rarely used traits are more easily forgotten than those frequently used. We consider how the rates of forgetting and social learning co-evolve. Large memories limit the need for innovation in rapidly changing environments by increasing the probability that individuals have adaptive information after an environmental change. This is driven by the presence of reservoirs of unexpressed persistent cultural variation. We explore the structure of ‘ideal’ cultural repertoires, balancing the probability of using the wrong cultural trait with retaining beneficial traits. This balance in turn affects the amount of social learning in stable environments. This approach to memory in cultural evolution changes our understanding of the evolution of social learning in fluctuating environments.

Memory and Social Learning

Many artificial intelligence systems are developed which interact with human beings and other such systems, sometimes embodied as robots. Their behaviour is driven by the knowledge they have on their environment. This knowledge may be learnt from experience. This is actually what advertised machine learning systems do. However, such systems will only behave properly if this knowledge, or culture, is shared with others. This raises the question: can they socially evolve their knowledge as assumed in cultural evolution?
Answering this question calls for developments in computational cultural (knowledge) evolution. It is at a crossroad between two threads:
- Cultural knowledge evolution in which cultural evolution is applied to the knowledge and beliefs of organisms.
- Computational cultural evolution in which computer capabilities are used to synthetise and analyse cultural evolution. It may be both experimental in which short-term small experiments are performed, or observational, in which observations can be made in the long run on large populations.

Computational cultural knowledge evolution may actually cover two types of activities: Agent-based simulation of cultural evolution in which agents are a model that can predict how a modelled system works or Artificial cultural evolution in which programs or agents are new `organisms' exhibiting cultural evolution.
Both activities are worth pursuing to study the principles of cultural (knowledge) evolution. For instance, the discussion about other species failing to develop cumulative culture supports the conclusion that the human species has a unique feature: cumulativity. However, it may be more simply related to the capability to deal with complex cultural items which support cumulativity better or to rely on more elaborate adaptation mechanisms that provide this cumulativity. So far, it is not possible to decide. Similarly, it is difficult to provide direct evidence of the absence of replicator. Developing agents able to evolve cumulatively their culture could bring some insight in these debates.
We are experimenting with agents learning their knowledge from their environment and from other agents. They behave according to this knowledge and are able to adapt their knowledge in order to succeed in social games exploiting it. The advantage of using agents bearing an explicit representation of knowledge is that it is possible to assess the evolution of the properties of agents' knowledge. In particular, the accuracy, the consistency, or the diversity of the knowledge can be directly measured.

Can AI systems culturally evolve their knowledge?

**Author(s):** Tyndel, S; Carlos, J; Aplin, LM; McElreath, MB Language is a hallmark of human evolution, and probably one of the main catalysts for cumulative cultural evolution in our species. While it is hard to study early language evolution directly, animal models can be useful to understand evolutionary drivers of communication. Parrots are similar to primates in social and cognitive complexity, but unlike primates, are known for their life-long flexible vocal learning across multiple contexts. Parrots use social contact calls that enabling other individuals to stay in touch even in dense vegetation. Multiple studies have found group or location specific dialects in contact calls, suggesting social learning. It has also been suggested that these calls are individually distinct and enable individual recognition. However, it is unclear whether, and how, social calls can be used for both functions within the same species. Here, we studied variation in monk parakeet (Myiopsitta monachus) calls at three levels using multilevel Bayesian models: individual, colony and population. We show that they have distinct dialects across cities, evidencing social learning. We further show that individuals have a distinctively recognisable ‘voice print’ across call types. This is the first evidence of such a voice print in a vocal learner outside of humans, and demonstrates how both dialects and individual recognition is possible in a flexible vocal learner.

Monk parakeets exhibit individual vocal signatures and population-level dialects in their vocalisations

**Author(s):** Mitchell, M; Hudson, E; Creanza, N Introduction 
In vocal-learning songbirds, song has been suggested to reinforce behavioral reproductive barriers between closely related species; this process may help facilitate speciation. Other explanations for song divergence are that songs would gradually accumulate random changes through drift, that morphological changes in birds would lead to changes in song features, or that sound-transmission properties of the local environment would lead to song differences between populations in different habitats.
 Approach
Here we test these competing hypotheses by analyzing 2726 community-science recordings of 42 species (21 sister species pairs) in the Passerellidae family of sparrows, using song-analysis software we developed. 
 Results
We found that geographic overlap was significantly associated with the degree to which sister species could be reliably distinguished by analyzing their song properties, and several song traits were found to evolve faster in sister species with range overlap than those without.
 Conclusions
Our results provide evidence that increased rates of cultural evolution could be a mechanism for population differentiation in songbirds.

Can cultural evolution facilitate speciation in songbirds?

A preference for having a particular number of children is a cultural trait expected to influence the fertility outcome of a woman. However, fertility preferences often do not match with the realised fertility of a woman. This pattern is probably because not much is known on how fertility desires actually vary, only that they are highly context-dependant. Furthermore, there is no clear understanding on how the social context shapes the fertility preferences of a woman. Here, we study how the social fertility context at the family, peer, and community level shapes the ideal family size of women from rural Poland. 
We build a Bayesian cross-classified multi-level model to account for the structure in the clustering at the family, peer, and community levels, and analyse how the average number of children ever born among clusters may shape the ideal number of children of Polish women (n=1,995). 
The results will show to what extent the ideal number of children is clustered at the family, peer, and community levels. Specifically, the results will show how the mean fertility of the different clusters predicts the direction of the fertility preferences of a woman. 
Knowing how the variability of fertility preferences is decomposed among the family, peers, and community levels can contribute to understand how the social context shapes culturally transmitted traits related to fertility.

How family, peers, and community matter in the differences of fertility preferences among women from rural Poland

**Author(s):** Kaaronen, R.O.; Manninen, M.A.; Eronen, J.T. Introduction
Measurement systems are key drivers of cultural evolution. Early standardized measurement systems evolved from body-based units of measure, such as the cubit. Previous research has implied that ‘advanced’ standardized units replaced ‘primitive’ body-based units. We argue that this is not the whole story, and that body-based measurement persisted up until recent times to serve specific cultural-technological functions. 
Materials/Methods
We collect ethnographic data from eHRAF and a literature review, documenting the use of body-based units. We develop a typology of body-based units and classify the cultural domains in which they are used. To study whether standardized systems replaced body-based systems, we collect data on the earliest evidence of standardization in each region.
 Results
We find body-based units in 186 cultures around the world. We find that body-based units persisted centuries after the emergence of standardization. We describe how body-based units afforded the elaborate ergonomic design of various key technologies (e.g., kayaks, bows) which facilitated human adaptation. 
Discussion
We discuss advantages of body-based units, including ergonomics, ease of use and availability. We discuss how standardization emerged rather as a tool for statecraft than for practical crafts, and how rules of thumb fell out of favor during industrial mass production.

Body-based units of measure in cultural evolution

**Author(s):** McCauley, B; Roberts, S; Xygalatas, D; Collard, M; Introduction: Permanent body modification (PBM) practices (e.g. tattooing, scarring, piercing) have been a global phenomenon for tens of thousands of years and continue to grow in popularity. However, their potential costs (e.g. infection, infertility, even death) are such that they represent an evolutionary puzzle. Why do people undertake them?
Approach: We reviewed etic explanations for PBM from anthropology, archaeology, psychology, the cognitive science of religion, clinical medicine, and gender studies. We then attempted to interpret each of them in an evolutionary framework.
Results: We identified 31 explanations from over 350 sources. Thirteen of them effectively posit that PBM practices indirectly increase inclusive fitness via their impact on the modified individual’s group, while 10 suggest they directly increase inclusive fitness. The remaining explanations could not be recast in evolutionary terms.
Discussion: Despite the diversity in explanations for PBM practices, evolutionary theory enables most of them to be transformed into a set of competing hypotheses. The next challenge is to generate a systematic cross-cultural dataset on PBM with which to test the hypotheses.

Why do people engage in permanent body modification? A multidisciplinary review

 Religious beliefs show profound cultural and historical diversity, and this diversity can yield insights into the ecological and cognitive foundations of religion. However, most studies of religious belief use participants from large industrialized nations who belong to major world religions. Here we describe an initiative to extract qualitative descriptions and quantitative codes for two major kinds of religious beliefs—characteristics of gods and spirits, and characteristics of supernatural explanations—using the ethnographic record. Our data cover 115 societies, 850 different supernatural agents, and thousands of different supernatural explanations. We also feature rich meta-data describing the ethnographic texts (e.g., source, field date) and societies. In this presentation, we will share early empirical insights from this database and a timeline for making the qualitative and quantitative data publicly accessible.

A new ethnographic database of religious beliefs

**Author(s):** Claessens, S; Atkinson, Q. D. INTRODUCTION: Cross-national analyses test hypotheses about drivers of global variation in national outcomes. However, since nations are connected via spatial proximity and cultural ancestry, cross-national analyses often violate assumptions of non-independence, inflating false positive rates. Here, we test whether cross-national research in economics and psychology sufficiently accounts for non-independence. METHODS: We conducted a systematic literature review, a simulation study, and reanalyses of 12 previous studies to determine whether previous cross-national analyses sufficiently account for non-independence. RESULTS: Our literature review revealed that controls for non-independence are rare in economics and psychology. When studies do include controls for non-independence, our simulations suggest that commonly used methods continue to produce false positives. In addition, we show that half of our reanalyses are no longer significant after controlling for non-independence using global proximity matrices. DISCUSSION: Existing cross-national analyses must be treated with caution. We urge social scientists to sufficiently control for non-independence in cross-national research.

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