Rhetorical modes are useful in both academic and non-academic writing, and can be subjects to be studied within linguistic research and computational modeling. Establishing a conceptual bridge among these domains could enable each to benefit from the others. This paper proposes duality-based mode operations (split-unite, forward-backward, expansion-reduction and orthogonal dualities) to expand the set of rhetorical modes, introducing generated modes like combination and generalization, thereby enhancing epistemic diversity across multiple applications. It further presents a pyramid multilayer mapping framework (e.g., three layers from the rhetorical model layer, to cognitive layer, and to epistemic layers) that reduces the resulting cognitive complexity. The degrees of expressive diversity and complexity reduction are quantified through binomial combinatorics and Shannon entropy analysis. A Marginal Rhetorical Bit (MRB) is identified, permitting the definition of a rhetorical-scalable parameter that measures expressive growth speed in bits per stage. A direct entropy measure shows that hierarchical selection over smaller subsets markedly reduces choice uncertainty compared with flat selection across all modes. These considerations appear to transform static and non-measurable rhetorical taxonomies into more dynamic and more measurable systems for discourse design. From this work, it would be possible to identify a pathway for future AI systems to operate not only on language tokens but on layered rhetorical reasoning structures, bridging linguistic, pedagogical, academic, and computational research

翻译：修辞模式在学术与非学术写作中均具有重要价值，并可作为语言学研究和计算建模的研究对象。在这些领域间建立概念桥梁可使各方相互受益。本文提出基于对偶性的模式操作（分裂-联合、前向-后向、扩展-缩减及正交对偶性），以扩展修辞模式集合，引入组合与泛化等生成模式，从而增强跨多应用的认知多样性。进一步提出金字塔多层映射框架（例如从修辞模型层到认知层再到认知层的三层结构），以降低由此产生的认知复杂度。通过二项式组合数学与香农熵分析，量化了表达多样性的程度与复杂性降低的幅度。识别出边际修辞比特（MRB），允许定义可衡量每阶段表达增长速率的修辞可扩展参数。直接熵度量表明，与在所有模式上进行扁平选择相比，在较小子集上的分层选择显著降低了选择不确定性。这些考量似乎将静态且不可度量的修辞分类体系转化为更具动态性和可测量性的话语设计系统。基于此项工作，未来人工智能系统不仅可在语言符号上操作，还能在分层修辞推理结构上运行，从而架起语言学、教育学、学术研究与计算研究之间的桥梁。