解释了语言形态为何自发稳定，源于类别的排斥力机制。
The natural stability of autonomous morphology
- 通过模拟词形填充过程，发现理性推理中的区分性证据产生类别排斥。
- 排斥力阻止词形类别完全融合，避免系统整体扁平化。
- 适合对语言演化、认知建模感兴趣的读者。
自主形态（如屈折类系统和范式分布模式）在自然语言中普遍存在且具有历时稳定性。尽管其学习成本高、无明显优势，且易受类比力重塑，但为何能长期存在仍不明确。本文提出一种解释：基于词形类别间的吸引与排斥动态，该动态源自简单的范式单元填充过程。通过计算进化模型，关键创新在于揭示‘分离性证据’的作用——即理性推理者在类比过程中可获取的屈折差异证据。此类证据引发排斥力，防止词形类别的完全融合（即彻底均质化）。对比其他模型时，我们发现条件熵作为可预测性度量在动态变化系统中存在局限。最终证明，自主形态并非‘反自然’（如 extcite{Aronoff1994} 所言），而是自然理性推理应用于屈折系统的必然涌现结果。
原文摘要 · Abstract (English)
Autonomous morphology, such as inflection class systems and paradigmatic distribution patterns, is widespread and diachronically resilient in natural language. Why this should be so has remained unclear given that autonomous morphology imposes learning costs, offers no clear benefit relative to its absence and could easily be removed by the analogical forces which are constantly reshaping it. Here we propose an explanation for the resilience of autonomous morphology, in terms of a diachronic dynamic of attraction and repulsion between morphomic categories, which emerges spontaneously from a simple paradigm cell filling process. Employing computational evolutionary models, our key innovation is to bring to light the role of `dissociative evidence', i.e., evidence for inflectional distinctiveness which a rational reasoner will have access to during analogical inference. Dissociative evidence creates a repulsion dynamic which prevents morphomic classes from collapsing together entirely, i.e., undergoing complete levelling. As we probe alternative models, we reveal the limits of conditional entropy as a measure for predictability in systems that are undergoing change. Finally, we demonstrate that autonomous morphology, far from being `unnatural' (e.g. \citealt{Aronoff1994}), is rather the natural (emergent) consequence of a natural (rational) process of inference applied to inflectional systems.
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