the collaborative efforts of the Ontogenetics Process Group (OPG) – an interdisciplinary, multi-institutional, multi-national research group that began meeting in 2017 to explore new and innovative ways of thinking the problem of complexity in living, physical, and social systems outside the algorithmic models that have dominated paradigms of complexity to date. This kind of interdisciplinary theoretical endeavor has a long history, of course, one that, in recent decades, has been largely occluded by the rise of Big Data, the neoDarwinian paradigm and its obsession with the genome as an engineerable “book of life,” and the assumption that “hard” scientific knowledge is fundamentally quantitative in nature. It’s entirely possible, however, that that hegemony will, in the longer view, prove to be misguided or, at the very least, oversold (as even prominent proponents such as Craig Ventner have recently admitted). For all the descriptive and predictive power that the complexity sciences offer (the ability to compute feedback systems, recursive networks, emergent dynamics, etc.), they also presume that the living world in all of its modalities (biological, semiotic, economic, affective, social) can be reduced to finite schema of description that delimits in advance all possible outcomes. The mathematics of complexity function like a “grid of intelligibility” for physicists, biologists, economists, information scientists, sociologists, and now, many humanists; they permit the sciences of the living and nonliving to speak the same language. What distinguishes this group of researchers, and this special issue of Angelaki in particular, is the breadth of disciplinary and methodological frameworks brought to bear on the possibilities and limitations of this proposition. More than this, what is proposed

中文翻译：

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超越复杂性的个体发育

Ontogenetics Process Group (OPG)——一个跨学科、多机构、跨国研究小组的合作努力，于 2017 年开始召开会议，探索新的和创新的思考外部生活、物理和社会系统复杂性问题的方法迄今为止主导复杂性范式的算法模型。这种跨学科的理论努力有着悠久的历史，当然，近几十年来，随着大数据的兴起、新达尔文范式及其对基因组作为可设计的“生命之书”的痴迷，这种努力在很大程度上被封闭了。以及“硬”科学知识本质上是定量的假设。然而，从长远来看，这种霸权完全有可能被证明是被误导的，或者至少，超卖（正如克雷格·文特纳（Craig Ventner）等著名支持者最近也承认的那样）。对于复杂性科学提供的所有描述和预测能力（计算反馈系统、递归网络、涌现动力学等的能力），他们还假设生活世界的所有形式（生物、符号学、经济、情感，社会）可以简化为有限的描述模式，它预先界定了所有可能的结果。对于物理学家、生物学家、经济学家、信息科学家、社会学家以及现在的许多人文主义者来说，复杂性数学就像一个“可理解性网格”；它们允许生命科学和非生命科学使用同一种语言。这组研究人员的与众不同之处，尤其是Angelaki的这一特刊，是对这一命题的可能性和局限性产生影响的学科和方法论框架的广度。不仅如此，还有什么建议