数字人文研究 ›› 2026, Vol. 6 ›› Issue (2): 3-17.

• 理论探索 •    下一篇

数字人文中的形式化偏向:形成、影响及方法反思

赵皓玥,南京大学历史学院博士研究生   

  • 出版日期:2026-06-28 发布日期:2026-07-16

Formalization Bias in Digital Humanities: Formation,Effects,and Methodological Reflection

  • Online:2026-06-28 Published:2026-07-16

摘要:

文章聚焦数字人文中的数据结构化与算法分类方法,讨论“形式化偏向”如何形成、发挥作用及其后果。首先区分了形式化逻辑、形式化操作和形式化偏向三个层面,将形式化偏向界定为可编码、可比较和可计算的材料属性在研究设计、证据建构和解释判断中持续获得优先地位的倾向。继而从技术入口、方法适配和知识产出激励三个方面分析形式化偏向如何形成,并结合文本分析和空间分析案例,说明其如何作为一种结构性机制影响研究对象边界、证据权重和知识组织方式。研究认为,形式化偏向的讨论有助于揭示数字方法参与人文学知识生产时形成的选择机制和解释边界;对数字人文的方法反思,需要进一步通过容纳不确定性的数据库结构、反思性元数据和失败透明化等路径,说明数字成果的生成条件、适用范围与解释责任。

关键词: 数字人文 , 形式化偏向 , 数据结构化 , 算法分类 , 证据建构 , 方法反思

Abstract:

This article focuses on data structuring and algorithmic classification methods in digital humanities,examining how “formalization bias” is formed,how it operates,and what consequences it produces.It first distinguishes among three levels: formal logic,formal operations,and formalization bias.Formalization bias is defined as the tendency for material attributes that are codable,comparable,and visualizable to gain sustained priority in research design,evidence construction,and interpretive judgment. The article then analyzes the formation of formalization bias from three aspects: technical entry points,methodological compatibility,and incentives in knowledge production.Drawing on cases of text analysis and spatial analysis,it further explains how formalization bias functions as a structural mechanism that affects the boundaries of research objects,the weighting of evidence,and the organization of knowledge. The study argues that examining formalization bias helps reveal the selective mechanisms and interpretive boundaries through which digital methods participate in the production of humanistic knowledge.Methodological reflection in digital humanities should therefore further clarify the conditions of production,scope of applicability,and interpretive responsibility of digital outputs through approaches such as database structures that accommodate uncertainty,reflexive metadata,and transparency about failure.

Key words: digital humanities , formalizing tendency , data structuring , algorithmic classification , evidence construction , methodological reflection

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