实践准则:递归性如何构成人类社会实践。

IF 2 4区 生物学 Q2 BIOLOGY
Rasmus Gahrn-Andersen
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引用次数: 0

摘要

本文解决了Kull(2020)对代码生物学提出的批评。库尔的批评针对代码生物学中关键的本体论和认识论假设,如果有效,可以有效地将其从属于皮尔森生物符号学。在考察了库尔论证的核心之后,这篇论文反驳了他的观点的一个重要方面:认知必然涉及解释驱动的决策,其中一个主体在对世界采取行动时总是面临至少两种选择。从激进的认知科学和一般的代码生物学中,论文认为基本的认知过程是缺乏心理内容的,因此,不应该用“决策”或“解释”等心理主义术语来描述。在这方面,来自技能习得现象学的见解表明,即使是复杂的人类认知形式也可以在没有明确的选择推理的情况下发生。在这种情况下,环境本身引发了熟练的反应。在此基础上,本文引入了行为学法则的概念——人类社会实践活动特征的法典化关系——这可以用来解释Maturana所认为的实践行为的“递归性”。在这方面,本文提供了人类社会实践行为的核心方面的帐户。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Codes of praxis: How recursivity constitutes human social practices
The paper addresses a criticism raised by Kull (2020) against Code Biology. Kull's critique targets key ontological and epistemological assumptions within Code Biology and, if valid, could effectively subordinate it to Peircean Biosemiotics. After examining the core of Kull's argument, the paper counters a significant aspect of his claim: that cognition necessarily involves interpretation-driven decision-making, wherein an agent is always faced with at least two alternatives when acting upon the world. Drawing from radical cognitive science and general Code Biology, the paper argues that basic cognitive processes are devoid of mental content and, therefore, should not be described in mentalist terms such as ‘decision-making’ or ‘interpretation.’ In this connection, insights from phenomenological accounts of skill acquisition demonstrate that even sophisticated forms of human cognition can occur without explicit reasoning about alternatives. In such cases, the environment itself elicits skillful responses. Building on this, the paper introduces the concept of praxeological codes—understood as codified relations characteristic of human socio-practical activity—which can be used to explain what Maturana identifies as the ‘recursivity’ of practical doings. In this connection, the paper provides an account of core aspects of human socio-practical behavior.
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来源期刊
Biosystems
Biosystems 生物-生物学
CiteScore
3.70
自引率
18.80%
发文量
129
审稿时长
34 days
期刊介绍: BioSystems encourages experimental, computational, and theoretical articles that link biology, evolutionary thinking, and the information processing sciences. The link areas form a circle that encompasses the fundamental nature of biological information processing, computational modeling of complex biological systems, evolutionary models of computation, the application of biological principles to the design of novel computing systems, and the use of biomolecular materials to synthesize artificial systems that capture essential principles of natural biological information processing.
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