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.

研究背景人类语言是地球上最复杂的交流系统。为什么它只在人类身上进化？其他动物也有一些与我们相同的能力：鸟鸣有复杂的句法，黑长尾猴有“语义”警报叫声，蜜蜂可以传达花蜜的位置，但没有一种动物的语言接近人类的语言。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，这为复杂语言的进化提供了选择性压力。一些灵长类动物可以通过圈养的强化训练来学习符号通信系统，但它们的自然栖息地并没有为这些潜在能力的发展提供适当的选择压力。解释语言进化的理论分散在生物学、语言学、心理学、人类学和考古学领域。缺少的是尝试将这些理论整合在一起并系统地相互检验它们。解决语言进化之谜非常重要。它改变了我们看待自己作为一个物种的方式：不是作为一个注定的造物顶峰，而是作为由我们的历史和环境塑造的进化动物，并与其他物种保持连续体。现在比以往任何时候都更重要的是证明研究人员可以跨领域合作来解决争论并讲述激发人们想象力的有意义的故事。目的和目标该项目旨在开发进化语言学数据库中的因果假设（CHIELD，https://chield） .excd.org）。它使用因果推理领域的正式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。目的是提供一个可应用于许多其他问题的科学理论构建模型。第二个目的是开发和使用“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）。我们进行了一项实验，人类参与者必须在虚拟世界（我的世界）中一起建造一个避难所，而无需使用自然语言。出乎意料的是，参与者选择依靠简单的指向而不是创新符号通信系统。我们得出的结论是，协作构建不会提供足够强大的选择性压力来促进符号交流的出现。一些理论提出了替代方案，例如劳动分工或协作狩猎。一个共同的任务框架将使我们能够控制参与者的数量或可用的资源，同时保持其他一切不变。目标 1：收集并正式描述特定语言能力如何随着特定社会、经济或生态因素而进化的理论。 CHIELD 数据库将是公共且开放访问的。目标 2：为通用任务框架开发开源工具。目标 3：使用通用任务框架通过实验来测试一组已确定理论中的三个案例研究。目标 4：沟通目标 5：向公众传达结果。应用和好处：该项目将提供一种新方法来解决人类最大的谜团之一：为什么我们进化出一种能力 语言。它将通过吸引科幻作家来产生影响。更一般地说，该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