Lessons for Theory from Scientific Domains Where Evidence is Sparse or Indirect.

Computational brain & behavior Pub Date : 2024-01-01 Epub Date: 2024-12-03 DOI:10.1007/s42113-024-00214-8
Marieke Woensdregt, Riccardo Fusaroli, Patricia Rich, Martin Modrák, Antonina Kolokolova, Cory Wright, Anne S Warlaumont
{"title":"Lessons for Theory from Scientific Domains Where Evidence is Sparse or Indirect.","authors":"Marieke Woensdregt, Riccardo Fusaroli, Patricia Rich, Martin Modrák, Antonina Kolokolova, Cory Wright, Anne S Warlaumont","doi":"10.1007/s42113-024-00214-8","DOIUrl":null,"url":null,"abstract":"<p><p>In many scientific fields, sparseness and indirectness of empirical evidence pose fundamental challenges to theory development. Theories of the evolution of human cognition provide a guiding example, where the targets of study are evolutionary processes that occurred in the ancestors of present-day humans. In many cases, the evidence is both very sparse and very indirect (e.g., archaeological findings regarding anatomical changes that might be related to the evolution of language capabilities); in other cases, the evidence is less sparse but still very indirect (e.g., data on cultural transmission in groups of contemporary humans and non-human primates). From examples of theoretical and empirical work in this domain, we distill five virtuous practices that scientists could aim to satisfy when evidence is sparse or indirect: (i) making assumptions explicit, (ii) making alternative theories explicit, (iii) pursuing computational and formal modelling, (iv) seeking external consistency with theories of related phenomena, and (v) triangulating across different forms and sources of evidence. Thus, rather than inhibiting theory development, sparseness or indirectness of evidence can catalyze it. To the extent that there are continua of sparseness and indirectness that vary across domains and that the principles identified here always apply to some degree, the solutions and advantages proposed here may generalise to other scientific domains.</p>","PeriodicalId":72660,"journal":{"name":"Computational brain & behavior","volume":"7 4","pages":"588-607"},"PeriodicalIF":0.0000,"publicationDate":"2024-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11666647/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Computational brain & behavior","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1007/s42113-024-00214-8","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2024/12/3 0:00:00","PubModel":"Epub","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

Abstract

In many scientific fields, sparseness and indirectness of empirical evidence pose fundamental challenges to theory development. Theories of the evolution of human cognition provide a guiding example, where the targets of study are evolutionary processes that occurred in the ancestors of present-day humans. In many cases, the evidence is both very sparse and very indirect (e.g., archaeological findings regarding anatomical changes that might be related to the evolution of language capabilities); in other cases, the evidence is less sparse but still very indirect (e.g., data on cultural transmission in groups of contemporary humans and non-human primates). From examples of theoretical and empirical work in this domain, we distill five virtuous practices that scientists could aim to satisfy when evidence is sparse or indirect: (i) making assumptions explicit, (ii) making alternative theories explicit, (iii) pursuing computational and formal modelling, (iv) seeking external consistency with theories of related phenomena, and (v) triangulating across different forms and sources of evidence. Thus, rather than inhibiting theory development, sparseness or indirectness of evidence can catalyze it. To the extent that there are continua of sparseness and indirectness that vary across domains and that the principles identified here always apply to some degree, the solutions and advantages proposed here may generalise to other scientific domains.

证据稀少或间接的科学领域给理论的教训。
在许多科学领域,经验证据的稀疏性和间接性对理论发展提出了根本性的挑战。人类认知进化理论提供了一个指导性的例子,其研究目标是发生在现代人类祖先身上的进化过程。在许多情况下,证据既稀少又间接(例如,关于可能与语言能力进化有关的解剖学变化的考古发现);在其他情况下,证据较少,但仍然非常间接(例如,关于当代人类和非人类灵长类动物群体的文化传播的数据)。从这一领域的理论和实证工作的例子中,我们提炼出科学家在证据稀疏或间接时可以致力于满足的五种良性实践:(i)明确假设,(ii)明确替代理论,(iii)追求计算和形式化建模,(iv)寻求与相关现象理论的外部一致性,以及(v)跨不同形式和来源的三角测量证据。因此,证据的稀疏性或间接性不仅不会抑制理论的发展,反而会促进理论的发展。在某种程度上,不同领域的稀疏性和间接性是连续的,这里确定的原则在某种程度上总是适用的,这里提出的解决方案和优势可以推广到其他科学领域。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
CiteScore
4.30
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信