Japan

Previous work utilizing Seshat: Global History Databank, a major resource for studying patterns of sociocultural evolution in world history, has sought to explain how and why complex societies rose, spread, and, at times, collapsed. Utilizing a large empirical dataset, we have explored the factors that drive social complexity and a host of related social features, from agricultural productivity to ideological developments to governing institutions. 

Here, I will summarize these findings and highlight our recent work trying to uncover the main causal forces behind the evolution of military technologies, a key factor in and indicator of intense interstate competition. I will discuss how this helps us not only understand the evolution of technology generally but also carries far-reaching implications for social dynamics more broadly. I conclude by previewing current efforts within the Seshat project linking these insights on interstate conflict to an exploration of internal competition and how this research can help shed light on not only the rise and continued development of states, but their periodic declines and falls as well.

Cultural Evolution Society 2021

Uncovering the Impact of External and Internal Competition on Long-Run Social Dynamics

### Conference Welcome

Welcome to the third Cultural Evolution Society Conference, CES2021. In the conference, which will be held from June 9-11, 2021, about 180 researchers from East Asia, Oceania, Middle East, Europe, North and South America give presentations on their latest research advancing the evolutionary understanding of human and nonhuman animal culture.

### Schedule and Program

[![](https://assets.underline.io/uploads/markdown_image/1/image/1ef06ffd05f80957b4a5b685f63ee3ba.png)](https://www.chain.hokudai.ac.jp/CES2020/wp-content/uploads/2021/06/fullprogram.pdf)
[![](https://assets.underline.io/uploads/markdown_image/1/image/12285eb22580949635121d15d5b46325.png)](https://www.chain.hokudai.ac.jp/CES2020/wp-content/uploads/2021/06/abstracts.pdf)

**Program-at-glance**

![](https://assets.underline.io/uploads/markdown_image/1/image/c0d0d4c8fcdad49d12631574fd966ae8.png)

### About the conference 
 
**Help-desk:** 
Please first visit [Help-desk](https://underline.io/events/120/help-desk) where you can find the instructions and manuals for exploring the conference site. 

**Plenary sessions:**
Five leading researchers give a live talk. It is like a TV show. The audience can submit a question from the chat window. Chat messages are immediately delivered to speakers and moderators.

**Q&A sessions (parallel):**
Each presenter first gives a 2-minute live lightning talk followed by an 8-minute live discussion with the audience. It uses Zoom.

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The audience can approach presenters and discuss their research. The sessions are held in a dedicated room in Gathertown.
 
**Gathertown:**
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You can meet and talk with anybody at a lounge or at a table in Gathertown.
Further Gather Town instruction and how to use short keys please find in our [Help desk page](https://underline.io/events/120/help-desk). 

**Videos and slides:**

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You can chat with any speaker in the Q&A and discussion sessions. A chat window is available on each speaker’s page, and you can leave your questions there. 

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If you want to make an announcement to the other participants (e.g., “Hey, let’s meet at the lounge in Gathertown from 9pm CEST!), please use twitter (#CESConf2021).



### Code of conduct

See the full details of [the code of conduct](https://www.chain.hokudai.ac.jp/CES2020/code-of-conduct/).
&nbsp; 
 CES is dedicated to providing a welcoming and harassment-free conference experience for everyone, regardless of gender, gender identity and expression, sexual orientation, disability, physical appearance, body size, race, age, religion, nationality, or the presence of or care for dependents. 
We do not tolerate harassment of conference participants in any form. Conference participants violating these rules may be sanctioned or expelled from the conference at the discretion of the conference organizers.

&nbsp;
**Harassment can occur in-person or virtually, and includes, but is not limited to:**
* Comments (verbal, text, etc.) that reinforce social structures of domination related to gender, gender identity and expression, sexual orientation, disability, physical appearance, body size, race, age, religion, nationality
* Sexual images in public spaces (physical or virtual)
* Deliberate intimidation, stalking, or following
* Harassing photography or recording (including sharing of presentation materials without consent)
* Sustained disruption of talks or other events (including “Zoombombing”)
* Inappropriate physical contact or unwelcome sexual attention
* Advocating for, or encouraging, any of the above behaviour 

&nbsp;
 **Inclusiveness Committee**:
&nbsp;
 To facilitate implementing the code of conduct and foster a climate of inclusion, we have developed an inclusiveness committee. Below is their contact information:
 **Hiromi Matsumae**:	matsumae.hiromi.g@tokai.ac.jp
 **Patrick Savage**:	psavage@sfc.keio.ac.jp
 **Sarah Mathew**:	Sarah.Mathew@asu.edu
 **Gmail:** inclusivenessCES2021@gmail.com
 See [more details about reporting the harassment.](https://www.chain.hokudai.ac.jp/CES2020/code-of-conduct/)

### Organizing committee

**Honorary Conference Organizer:** [Kenichi Aoki (Meiji University)](https://sites.google.com/site/kenichi1aoki/home) 

**Chair:** [Masanori Takezawa (Hokkaido University)](https://lalalarakko.github.io)

**Scientific Committee:** [Kenichi Aoki (Meiji University)](https://sites.google.com/site/kenichi1aoki/home), [Yasuo Ihara (the University of Tokyo)](https://researchmap.jp/read0209180?lang=en), [Hiromi Matsumae (Tokai University)](https://sites.google.com/site/hiromimatsumae/eng), [Naoko Matsumoto (Okayama University)](https://researchmap.jp/nmatsumoto_okayama-u), [Masako Myowa (Kyoto University)](https://myowa.educ.kyoto-u.ac.jp/en), [Hisashi Nakao (Nanzan University)](https://www.hisashinakao.com/), [Patrick E. Savage (Keio University)](https://sites.google.com/view/comp-music-lab/home)

**Local Organizing Committee:** [Yutaka Horita (Teikyo University)](https://sites.google.com/site/yhoritapage/), [Masanori Takezawa (Hokkaido University)](https://lalalarakko.github.io/), [Ayaka Takimoto (Hokkaido University)](https://lynx.let.hokudai.ac.jp/~takimoto/), [Kohei Tamura (Tohoku University)](https://researchmap.jp/7000017854)

**Inclusiveness Committee:** [Sarah Mathew (Arizona State University)](https://www.sarahmathew.net/), [Hiromi Matsumae (Tokai University)](https://sites.google.com/site/hiromimatsumae/eng), [Patrick E. Savage (Keio University)](https://sites.google.com/view/comp-music-lab/home)


![](https://assets.underline.io/uploads/markdown_image/1/image/967110a00d200a6b20d6f4fa6556ba13.png)

For attending the conference, you first need to register and pay fees from [the link here](https://www.chain.hokudai.ac.jp/CES2020/registration/). After the payment of the registration fees, you will receive a ticket, which is necessary for accessing the conference site. After the payment of the registration fees, you will receive a ticket, which is necessary for accessing the conference site

Registration fee

technical paper

It has become increasingly clear that culture and social learning play a vital role in species ecology. While much attention has been paid to its presence in vertebrates such as primates and cetaceans, which often have complex social structure, it also occurs in a broad and diverse variety of animal communities including reptiles, fishes, and insects. As we learn more about the breadth of species that utilise social learning, it has expanded the scope of what social learning and culture can tell us beyond a single species. This is particularly relevant as the conservation value of culture and social complexity becomes more established. Here I review social learning across species with varying community structures, providing an overview of how culture can manifest across animal societies and the different ecological roles it may play as a result. Such a review is critical to how studies across different species and community structures may inform one another. It further illustrates the intrinsic value of animal culture in practice as well as theory. When these separate pieces are brought together, they will provide the necessary infrastructure to move the field of animal culture forward in how it can be both understood and applied.

The diversity of animal culture across community structures

Envy-based magic beliefs, including witchcraft, are prevalent in societies around the world. These beliefs can create distrust due the belief that one’s misfortune can be magically caused by others in their community. We examined the relationship between witchcraft rituals, motivation, and distrust in a sample of 428 Hindus Mauritians. Despite these beliefs being largely taboo, Hindu Mauritians have a pervasive belief in witchcraft and evidence of the performance of witchcraft rituals is readily found throughout Mauritius. Participants were shown a picture of fruits claimed to be purchased for a religious or witchcraft ritual or to be eaten, and given one of three motivations for the purchaser (envy, selfishness, or neutral). Participants in the witchcraft and envy conditions rated the purchaser as less trustworthy and more harmful to the community than in the other conditions. Participants who were told the purchaser was envious or selfish were more likely to accuse the purchaser of witchcraft even when told he was buying fruit for a religious ritual or to eat. Free list questions confirmed that envy as a motivation increased participants willingness to see this person as less trustworthy and to claim his actions will have negative reputational impacts and cause harm. This work suggests that a belief that others are practicing magic decreases trust and is believed to cause harm across motivations. Further, the claim that a person is envious or selfish can increase the willingness to make a witchcraft accusation.

Witchcraft, Envy, and Trust among Hindu Mauritians

Magic is of longstanding interest to researchers studying the cultural evolution of religion, philosophy, and even science. Recent research supports that magical thinking tendencies affect individuals' susceptibility to modern day misinformation, which suggests insights on the cultural evolution of magic may have policy applications today. Using newly collected survey and comparative datasets, I test three leading hypotheses for the cultural evolution of magic, 1) unilineal replacement of magic first by religion and then by science, 2) magic functioning to provide market goods that are distinct from religion or science, and 3) magic arising from long-evolved cognitive tendencies that constrain human psychology. I find empirical support for all three hypotheses but in differing contexts. Thus, rather than evolving through any single process, magical beliefs and practices appear to be induced through multiple processes of cultural evolution. Greater awareness of the contexts in which magical thinking operates, and when it may be adaptively useful, may allow people to better guard against misfiring of magical thinking that can result in the spread of scientific and journalistic misinformation.

Multiple socio-cognitive processes lead to the cultural evolution of magic

We propose an evolutionary model of the origin of ritual behavior in the hominin lineage that treats collective ritual as a communication technology facilitating mutualistic cooperation. In our model, we first synthesize the literature dealing with hunter-gatherer ethnography and hominin archaeology and identify gradual coalescence of similarity signals, coalitionary signals, and signals of commitment to collective action as the main building blocks of human ritual behavior. Subsequently, we turn to primatology and paleoanthropology to trace the presence of these signals in both non-human primates and past hominins. Adding the proximate level to our analysis, we pinpoint distinctive neurocognitive mechanisms scaffolding the three types of ritual signals (overimitation, shared intentions, recursiveness, prospection, cross-domain association) and track down their presence in past hominins. Finally, we connect this evidence with the prevalent socio-ecological selective pressures for cooperative communication (environmental variability, interdependence, inter-group interactions) and offer estimates both for when the first of the ritual signals started to evolve as well as when ritual signals coalesced into an adaptation affording to overcome collective action problems.

Origin of human ritual behavior

Religious belief is declining in many regions of the world, but some societies have remained highly religious. What explains why people and countries abandon their beliefs while others stay faithful to their religion? We propose that the Moralization of Religiosity (MoR)—the belief that religion is necessary and essential for morality—is key to answering this question. MoR likely emerged as a by-product of the historical rise of prosocial religions, but we propose that it has an additional side-effect—it discourages deconversion due to perceived reputational costs. We further suggest that cultural differences in MoR foreshadow patterns of nation-level secularization and individual-level deconversion. Our model is supported by historical cross-cultural, retrospective longitudinal, survey, and experimental studies. Study 1 (N = 218,603) shows that cross-cultural differences in MoR in 44 nations predict why some countries secularized faster than others from 1995-2014. Study 2 (N = 701) shows that childhood exposure to MoR predicts a stronger likelihood to maintain religion across the lifespan, controlling for several other factors. In Studies 3a-3c (N3a = 299; N3b = 300; N3c = 325), present-day MoR negatively predicts participants’ likelihood of deconverting in the future. Study 4 (N = 513) showed that endorsement of MoR predicted prejudice towards deconverts and atheists, suggesting that MoR inhibits deconversion due to perceived reputational costs. Finally, Study 5 (N = 461) replicates our key findings with an experimental design.

Moralization of Religiosity Explains Worldwide Trends in Religious Belief

The present research investigates how psychological mechanisms and social network structures generate patterns of cultural change and diversity. The two psychological mechanisms studied here are cultural drift and indirect minority influence; the former is parameterized by an error rate and the latter by a leniency threshold. The patterns of cultural change are examined in terms of magnitude (small vs large), speed (gradual vs rapid), and frequency (frequent vs rare). Diversity and polarization in a society are examined in terms of global cultural variation (inverse Simpson index) and local neighborhood difference (Hamming distance). Key findings are that in networks with high connectivity or local community structures (complete, scale-free, random, and modular networks) cultural drift can produce a rapid, large, and rare pattern of cultural change (punctuated equilibrium), whereas in lattice or small world networks, it produces a more gradual change pattern. Indirect minority influence robustly produces a gradual, small, and frequent pattern of cultural change (gradualism) across various network structures. When cultural change occurs in social networks that have a modular community structure, indirect minority influence generates a regime of cultural diversity whereas cultural drift generates a polarized regime. Finally, cultural drift and indirect minority influence generate distinct tipping points for social change in different network structures, but prediction of whether and when cultural change emerges is difficult at tipping points in both cases.

Emergent Patterns of Cultural Change: Modeling Psychological Mechanisms and Social Network Structures

Population size has long been considered an important driver of cultural change. Results from population genetics, however, demonstrate that it is not the census population size, N, but the effective size of a population, N_e, that determines important evolutionary parameters. This effective population size governs the rate of change in a population due to drift and affects genetic variability both within and between populations. Here, we systematically examine effective population sizes for traits that evolve culturally, i.e. through processes of innovation and social learning, rather than genetically. We use different modeling approaches to investigate how cultural N_e and levels of diversity depend on the way traits are learned, population connectedness and social network structure. We show that one-to-many and frequency-dependent transmission can temporally or permanently lower effective population size compared to census numbers. Contrary to expectations in the literature, migration does not increase N_e and a process of cultural exchange among groups increases only the less meaningful inbreeding effective number but not the variance effective number. While network density in random networks leaves N_e unchanged, scale-free networks tend to decrease and small-world networks tend to increase N_e compared to census numbers. Finally, for one-to-many transmission and different network structures, effective size and cultural diversity are closely associated. For connectedness, however, small amounts of migration and cultural exchange result in highest diversity independently of N_e. Our results highlight the importance of effective population size for cultural evolution and show that inferring N_e requires detailed knowledge about underlying cultural and demographic processes.

Effective population size for culturally evolving traits

The use of two or more tools in combination - Associative tool use (ATU) – has played a crucial role in human cultural evolution and is also part of chimpanzee tool cultures. Research into the cognitive processes underlying ATU produced evidence for the spontaneous invention of some forms of ATU in some non-human primate and bird species. In contrast, developmental studies with children have been sparse. Whether young children are also able to spontaneously invent different types of ATU and at what age this ability emerges is still unknown. This study aimed to start filling this gap in the literature with two experiments with samples of European, predominantly White preschoolers (E1: N = 66, 3y 6m - 4y 9m; E2: N = 119, 3y 0m - 6y 10m) who were administered a series of novel, non-verbal tool-use tasks measuring three different types of ATU: Tool set, Metatool use, and Sequential tool use. Children had 3 min per task and did not receive any demonstrations. Results from both experiments showed that from 3 years of age, children were able to spontaneously invent the three types of investigated ATU behaviours, suggesting that no immediate social learning was needed for the emergence of these behaviours. E2 showed that performance significantly increased with age. However, success rates were low, demonstrating that the spontaneous invention of ATU in novel tasks with brief exposure is challenging for preschoolers. The tasks add to the pool of tests that can be used to study problem-solving in humans and non-humans.

Young children spontaneously invent different types of associative tool use behaviour

A species is deemed cultural when there exists behavioural variation across populations that can be at least partly attributed to social learning. Understood in this way, culture has been found in all species of great apes. However some ape behaviours have additionally been claimed to be culture-dependent, implying that copying social learning mechanisms underlie their acquisition (as it occurs in human culture). If that was the case, these ape behaviours should have become locally restricted as a consequence of the unavoidable copying errors accumulated during their transmission between connected individuals. Based on this logic we developed the "Method of Local Restriction" in order to identify potential cases of culture-dependent forms in great apes which distribution is compatible with acquisition via copying (i.e. these behaviours are restricted to a single ape population). After conducting an exhaustive literature search across ape species, populations and behavioural domains, we found that the vast majority of great ape behaviours re-appear in unconnected populations and therefore do not necessarily rely on copying to be acquired. However, we found 25 locally restricted behaviours, three of which were locally unique to a single population of a single great ape species. These behaviours represent the best available candidates of culture-dependent forms in great apes, which reliance on copying social learning should be tested in targeted experiments. Overall our results suggest that great ape cultures are sustained by different learning mechanisms from those at play in human cultures, namely by individual learning mediated by non-copying social learning mechanisms.

The Method of Local Restriction: In search of potential great ape culture-dependent forms

Many features of Human cultural evolution, such as technology (Kolodny et al., 2015), language (Carr et al., 2016), and scientific knowledge (Lehman, 1947) seem to exhibit unbounded evolutionary dynamics; growing in complexity, introducing new innovations, and having no obvious bounds. Evolutionary systems exhibiting unbounded evolutionary dynamics are commonly referred to as being open-ended (Bedau et al., 1998). The creation and analysis of systems that exhibit open-ended evolutionary dynamics is an open problem in the field of Artificial Life (Bedau et al., 2000). Motivated by the observations that nature exhibits unbounded evolution, with the ongoing generation of adaptive novelty and complexity, Artificial Life researchers want to create open-ended evolutionary systems in artificial media (e.g. computer simulations, robots, ... ). The goal of achieving open-endedness in artificial evolutionary systems has led to the formalisation of measurements for unbounded evolutionary dynamics - these measurements take the form of evolutionary activity statistics, and are often called the “ALife Test” for unbounded evolutionary dynamics (Bedau et al., 1998). This test has been applied to the fossil record (Bedau et al., 1998), the patent record (Bedau et al., 2019) and artificial evolutionary systems (Channon, 2003). The activity statistics enable researchers to take any evolving system over time and assess changes to diversity, alongside measuring the introduction and adaptive persistence of new components in the system. Despite having numerous datasets, models, and evaluation methods, the field of cultural evolution is yet to effectively determine whether any given component of a culturally evolving system is bounded or unbounded. Determining what species exhibit open-ended cultural evolution, and in which behavioural domains, should be a key focus of cultural evolution going forward, and the the ALife test provides us with a consistent approach for doing this.

Uncovering the Impact of External and Internal Competition on Long-Run Social Dynamics

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