Causal approaches to investigating language evolution

研究语言演化的因果方法

• 批准号: AH/T006927/1
• 负责人: Sean Roberts
• 金额: $ 25.54万
• 依托单位: CARDIFF UNIVERSITY
• 依托单位国家: 英国
• 项目类别: Research Grant
• 财政年份: 2021
• 资助国家: 英国
• 起止时间: 2021 至 无数据
• 项目状态: 未结题
• 来源: https://gtr.ukri.org/projects?ref=AH%2FT006927%2F1
• 关键词: Causal; approaches; investigating; language; evolution

Research contextHuman language is the most complex communication system on earth. Why did it evolve only in humans? Other animals share some of our capacities: birdsong has complex syntax, vervet monkeys have 'semantic' alarm calls, and bees communicate the location of nectar, but none come close to human language. While genetics and cognition are part of the story, perspectives from anthropology and archaeology make it increasingly clear that our ancestors found themselves in critical social, economic and ecological situations which provided the selective pressures for the evolution of complex language. Some primates can learn symbolic communication systems via intense training in captivity, but their natural habitats do not provide the right selective pressures for these latent abilities to develop. Theories explaining language evolution are scattered across biology, linguistics, psychology, anthropology and archaeology. What is missing is an attempt to pull these theories together and test them systematically against each other.Solving the mystery of language evolution is important. It changes the way we see ourselves as a species: not as a predestined pinnacle of creation, but as evolved animals shaped by our history and environment, and on a continuum with other species. Now more than ever it is important to demonstrate that researchers can work together across fields to resolve debates and tell meaningful stories that capture people's imaginations.Aims and objectivesThis project aims to develop the Causal Hypotheses in Evolutionary Linguistics Database (CHIELD, https://chield.excd.org). This uses formal tools from the field of Causal Inference to represent hypotheses as a series of causal connections (a causal graph). This clarifies theories and allows researchers to spot connections between them. Causal inference has revolutionised fields like epidemiology, and the time is ripe for its application to language evolution and the social sciences more generally. The aim is to provide a model for scientific theory building that can be applied to many other questions.The second aim is to develop and use a "common task framework" to test competing theories of language evolution. In a pilot study, the project team tested the proposal that the use of symbolic signals emerged to help early humans build structures together (Irvine & Roberts, 2016). We ran an experiment where human participants had to build a shelter together in a virtual world (Minecraft) without using natural language. Unexpectedly, participants chose to rely on simple pointing rather than innovate a symbolic communication system. We concluded that collaborative construction would not provide a selective pressure strong enough for symbolic communication to emerge. Several theories suggest alternative scenarios such as the division of labour or collaborative hunting. A common task framework would allow us to manipulate the number of participants or the resources available while keeping everything else constant.Objective 1: Collect and formally describe theories of how a particular linguistic ability evolved as a response to particular social, economic or ecological factors. The CHIELD database will be public and open access.Objective 2: Develop open-source tools for a common task framework.Objective 3: Test three case-studies from the set of identified theories through experiments using the common task framework.Objective 4: Communicate the results to researchers.Objective 5: Communicate the results to the general public.Applications and benefits:This project will provide a new way of solving one of humanity's greatest mysteries: why we evolved a capacity for language. It will create impact by engaging science fiction authors. More generally, this project will provide a model for how to develop theory in interdisciplinary research. Source code will be freely available for other fields to utilise.

人类语言是地球上最复杂的交流系统。为什么它只在人类中进化？其他动物也有我们的一些能力：鸟鸣有复杂的语法，长尾猴有“语义”警报，蜜蜂交流花蜜的位置，但没有一种能接近人类的语言。虽然遗传学和认知是故事的一部分，但人类学和考古学的观点越来越清楚地表明，我们的祖先发现自己处于关键的社会、经济和生态环境中，这些环境为复杂语言的进化提供了选择压力。一些灵长类动物可以通过圈养的高强度训练学习符号交流系统，但它们的自然栖息地没有为这些潜在能力的发展提供合适的选择压力。解释语言进化的理论散布在生物学、语言学、心理学、人类学和考古学中。我们缺少的是将这些理论整合在一起，并系统地相互检验它们的尝试。解开语言进化之谜是很重要的。它改变了我们看待自己作为一个物种的方式：不是被注定的创造的顶峰，而是被我们的历史和环境塑造的进化动物，与其他物种在一个统一体上。现在比以往任何时候都更重要的是，要证明研究人员可以跨领域合作，解决争论，讲述有意义的故事，吸引人们的想象力。目的与目标本项目旨在开发进化语言学数据库（cheld, https://chield.excd.org）中的因果假设。它使用因果推理领域的形式化工具将假设表示为一系列因果关系（因果图）。这澄清了理论，并使研究人员能够发现它们之间的联系。因果推理已经彻底改变了流行病学等领域，将其应用于语言进化和更广泛的社会科学的时机已经成熟。其目的是为科学理论的建立提供一个可以应用于许多其他问题的模型。第二个目标是开发和使用一个“共同任务框架”来测试语言进化的竞争理论。在一项试点研究中，项目团队测试了使用符号信号来帮助早期人类共同建造结构的提议（Irvine & Roberts, 2016）。我们进行了一个实验，让人类参与者在虚拟世界（Minecraft）中一起建造一个庇护所，而不使用自然语言。出乎意料的是，参与者选择依靠简单的指向，而不是创新的符号交流系统。我们得出的结论是，协作建设不会提供足够强大的选择压力，使符号交流得以出现。一些理论提出了其他的情景，如劳动分工或合作狩猎。一个通用的任务框架将允许我们在保持其他一切不变的情况下操纵参与者的数量或可用的资源。目标1：收集并正式描述一种特定语言能力是如何作为对特定社会、经济或生态因素的反应而进化的理论。cheld数据库将向公众开放。目标2：为公共任务框架开发开源工具。目标3：通过使用共同任务框架的实验，从已确定的理论中测试三个案例研究。目标4：将结果传达给研究人员。目标5：将结果传达给公众。应用和好处：这个项目将提供一种新的方法来解决人类最大的谜团之一：为什么我们进化出了语言能力。它将通过吸引科幻作家来产生影响。更一般地说，这个项目将为如何在跨学科研究中发展理论提供一个模型。源代码将免费提供给其他领域使用。

项目成果

Investigating environmental effects on phonology using diachronic models

• DOI: 10.1017/ehs.2023.33
• 发表时间: 2024-01-03
• 期刊: EVOLUTIONARY HUMAN SCIENCES
• 影响因子: 2.6
• 作者: Hartmann，Frederik;Roberts，Sean G.;Grollemund，Rebecca
• 通讯作者: Grollemund，Rebecca

Language Evolves: Communicating theories of language evolution to science fiction authors

语言进化：向科幻小说作者传达语言进化理论

• 发表时间: 2022
• 作者: Litte H

Including Creoles and Pidgins in Analyses of Cultural Co-Evolution

将克里奥尔语和洋泾浜语纳入文化共同进化分析

• 发表时间: 2022
• 作者: Roberts SG

Distinguishing selection pressures in an evolving communication system: Evidence from color-naming in "cross signing"

区分不断发展的通信系统中的选择压力：来自“交叉签名”中颜色命名的证据

• DOI: 10.3389/fcomm.2022.1024340
• 发表时间: 2022
• 期刊: Frontiers in Communication
• 影响因子: 2.4
• 作者: Byun K

CHIELD: A database of causal hypotheses for unifying theories of cultural evolution

CHIELD：统一文化进化理论的因果假设数据库

• 发表时间: 2022
• 作者: Roberts S