Infrastructuring Educational Genomics: Associations, Architectures, and Apparatuses

Infrastructuring Educational Genomics: Associations, Architectures, and Apparatuses
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教育基因组学基础设施:关联、架构和设备

DOI:
10.1007/s42438-023-00451-3
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发表时间:
2024
期刊:
Postdigital Science and Education
影响因子:
--
通讯作者:
Williamson B
Williamson B
中科院分区:
--
文献类型:
--
作者:
Williamson B

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分子基因组学的技术科学变革已经开始影响教育中的知识生产。跨学科的科学联盟正在寻求确定“遗传影响”对“教育相关”的特征,行为和结果。本文探讨了新兴的“知识基础设施”的教育基因组学,参加大会和编排的组织协会,认知架构,并technoscientific仪器牵连的基因组的理解,从大量的生物信息的生成。作为数据化知识生产的基础设施,教育基因组学嵌入以数据为中心的认识论和实践中,这些认识论和实践从分子遗传关联的角度重塑了教育问题,这些认识论和实践被认为是从数字生物信息中获得的,并可能对政策和实践中的遗传干预开放。虽然科学家们声称要“打开基因组的黑匣子”及其与教育成果的关联,但我们打开了教育基因组学本身的黑匣子,作为新兴科学权威的来源。数据密集型的教育基因组学并没有直接“发现”教育相关行为和结果的生物学基础。相反,这种知识基础设施也是一种实验性的“本体论基础设施”,支持在教育中认识、理解、解释和干预的特定方式,并通过生物信息的算法处理将人类教育主体重新塑造为可调查和可预测的。
Technoscientific transformations in molecular genomics have begun to influence knowledge production in education. Interdisciplinary scientific consortia are seeking to identify ‘genetic influences’ on ‘educationally relevant’ traits, behaviors, and outcomes. This article examines the emerging ‘knowledge infrastructure’ of educational genomics, attending to the assembly and choreography of organizational associations, epistemic architecture, and technoscientific apparatuses implicated in the generation of genomic understandings from masses of bioinformation. As an infrastructure of datafied knowledge production, educational genomics is embedded in data-centered epistemologies and practices which recast educational problems in terms of molecular genetic associations—insights about which are deemed discoverable from digital bioinformation and potentially open to genetically informed interventions in policy and practice. While scientists claim to be ‘opening the black box of the genome’ and its association with educational outcomes, we open the black box of educational genomics itself as a source of emerging scientific authority. Data-intensive educational genomics does not straightforwardly ‘discover’ the biological bases of educationally relevant behaviors and outcomes. Rather, this knowledge infrastructure is also an experimental ‘ontological infrastructure’ supporting particular ways of knowing, understanding, explaining, and intervening in education, and recasting the human subjects of education as being surveyable and predictable through the algorithmic processing of bioinformation.
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