Canali Stefano
Institute for Philosophy, Leibniz Universität Hannover, Lange Laube 32, 30159, Hannover, Germany.
Stud Hist Philos Biol Biomed Sci. 2020 Aug;82:101248. doi: 10.1016/j.shpsc.2019.101248. Epub 2020 Apr 16.
How is scientific data used to represent phenomena and as evidence for claims about phenomena? In this paper, I propose that a specific type of claims - evidential claims - is involved in data practices to define and restrict the representational and evidential content of a dataset. I present an account of data practices in the epidemiology of the exposome based on the notion of evidential claims, which helps unpack the approaches, assumptions and warrants that connect different stages of research. I identify three different strategies to generate different types of evidential claims in this case. The macro strategy, which individuates the dataset that serves as the initial evidential space for research. The micro strategy, which is used to generate evidential claims about the microscopic and individual component of target phenomena. The association strategy, that uses evidence from the other strategies to identify a dataset as representation of the different levels and relations of exposure and disease. Differentiating between these strategies sheds light on the multi-faceted landscape of biomedical research on environment and health; and the roles of data and evidence in the process of inquiry.
科学数据是如何被用来表征现象并作为有关现象的主张的证据的?在本文中,我提出,在数据实践中涉及一种特定类型的主张——证据性主张——以定义和限制数据集的表征内容和证据内容。我基于证据性主张的概念,对暴露组流行病学中的数据实践进行了阐述,这有助于剖析连接研究不同阶段的方法、假设和依据。在这种情况下,我确定了三种不同的策略来生成不同类型的证据性主张。宏观策略,它确定作为研究初始证据空间的数据集。微观策略,用于生成关于目标现象的微观和个体组成部分的证据性主张。关联策略,它利用其他策略的证据将一个数据集确定为暴露与疾病不同层次和关系的表征。区分这些策略有助于揭示环境与健康生物医学研究的多面图景;以及数据和证据在探究过程中的作用。