用符号学理论分析模型如何表达意义，揭示建模选择的深层影响。
The Differential Meaning of Models: A Framework for Analyzing the Structural Consequences of Semantic Modeling Decisions
- 基于皮尔斯符号学，将模型视为符号，分析其语义结构。
- 模型本质是关于符号系统背后意义机制的假设，而非单纯性能工具。
- 适合研究意义建模、符号系统分析的学者，尤其关注模型解释性者。
人类意义生成的建模方法日益丰富，成为分析复杂符号系统的有力工具。然而，当前领域缺乏一个通用理论框架，无法在不同模型类型间进行可比分析。本文提出基于查尔斯·桑德斯·皮尔斯符号学理论的框架，认为这些模型实际上测量的是潜在的符号几何结构，即对符号数据集背后复杂符号能动性的假设。当模型价值无法通过性能指标直接衡量时，可从关系视角理解：模型的独特解释视角可通过与其他模型的对比显现。由此构建了模型语义理论，将模型及其建模决策本身视为符号。除提出框架外，还通过简例展示其应用，并探讨由此开启的基础问题与未来方向。
原文摘要 · Abstract (English)
The proliferation of methods for modeling of human meaning-making constitutes a powerful class of instruments for the analysis of complex semiotic systems. However, the field lacks a general theoretical framework for describing these modeling practices across various model types in an apples-to-apples way. In this paper, we propose such a framework grounded in the semiotic theory of C. S. Peirce. We argue that such models measure latent symbol geometries, which can be understood as hypotheses about the complex of semiotic agencies underlying a symbolic dataset. Further, we argue that in contexts where a model's value cannot be straightforwardly captured by proxy measures of performance, models can instead be understood relationally, so that the particular interpretive lens of a model becomes visible through its contrast with other models. This forms the basis of a theory of model semantics in which models, and the modeling decisions that constitute them, are themselves treated as signs. In addition to proposing the framework, we illustrate its empirical use with a few brief examples and consider foundational questions and future directions enabled by the framework.
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