目前为止,对于说谎者悖论的解答,我们可以找到大量的方案。为了理清这些方案的关系,本文提出一种合理有效的说谎者悖论解悖方案的分类标准。以往典型的分类标准有三种,第一种是源自塔斯基的二分分类标准;第二种是由二分分类标准发展的...目前为止,对于说谎者悖论的解答,我们可以找到大量的方案。为了理清这些方案的关系,本文提出一种合理有效的说谎者悖论解悖方案的分类标准。以往典型的分类标准有三种,第一种是源自塔斯基的二分分类标准;第二种是由二分分类标准发展的三分分类标准;第三种是Koons提出的分类标准。三种分类标准均是使用特殊概念作为分类依据,因此三种分类方案均存在时效性问题和特设性问题。这些问题使得已有的分类标准具有滞后性,无法有效对未来可能出现的解悖方案进行分类。本文提出的分类方式将以说谎者悖论本身为依据,而不是以特殊概念作为分类依据。因此新分类方式将避免在以往分类标准中由特殊概念作为分类依据而引起的问题。To date, we can identify a multitude of solutions to the liar paradox. To clarify the relationships among these approaches, this article proposes a reasonable and effective classification standard for liar paradox resolution schemes. Historically, there have been three typical classification standards: The first is the binary classification standard derived from Tarski, the second is the ternary classification standard developed from the binary classification standard, the third is the binary classification standard derived from Koons. All standards rely on specific concepts as the basis for classification, resulting in issues of time-sensitive and ad hoc nature. These issues cause existing classification standards to lag behind and fail to effectively categorize potential future solutions to the paradox. The classification method proposed in this article will be based on the liar paradox itself, rather than on specific concepts. Consequently, the new classification method will circumvent the problems associated with using specific concepts as the classification criteria in previous standards.展开更多
文摘目前为止,对于说谎者悖论的解答,我们可以找到大量的方案。为了理清这些方案的关系,本文提出一种合理有效的说谎者悖论解悖方案的分类标准。以往典型的分类标准有三种,第一种是源自塔斯基的二分分类标准;第二种是由二分分类标准发展的三分分类标准;第三种是Koons提出的分类标准。三种分类标准均是使用特殊概念作为分类依据,因此三种分类方案均存在时效性问题和特设性问题。这些问题使得已有的分类标准具有滞后性,无法有效对未来可能出现的解悖方案进行分类。本文提出的分类方式将以说谎者悖论本身为依据,而不是以特殊概念作为分类依据。因此新分类方式将避免在以往分类标准中由特殊概念作为分类依据而引起的问题。To date, we can identify a multitude of solutions to the liar paradox. To clarify the relationships among these approaches, this article proposes a reasonable and effective classification standard for liar paradox resolution schemes. Historically, there have been three typical classification standards: The first is the binary classification standard derived from Tarski, the second is the ternary classification standard developed from the binary classification standard, the third is the binary classification standard derived from Koons. All standards rely on specific concepts as the basis for classification, resulting in issues of time-sensitive and ad hoc nature. These issues cause existing classification standards to lag behind and fail to effectively categorize potential future solutions to the paradox. The classification method proposed in this article will be based on the liar paradox itself, rather than on specific concepts. Consequently, the new classification method will circumvent the problems associated with using specific concepts as the classification criteria in previous standards.
