摘要
通过梳理大数据主义的概念由来和观点,以及经验主义思潮的由来与历史演变,论证了齐磊磊建立在南茜·卡特莱特(Nancy Cartwright)为代表的新经验主义哲学基础之上的"大数据经验主义"新概念不能客观、全面地概括大数据科学哲学特征,也不具备表征大数据时代人文社会现象的现实需要,因此不能实现对大数据主义概念的超越。受技术限制,人类传统思维只能观察和收集有限的数据,然后运用理性思维建立理论模型,最后在实践中利用理论模型的演绎来把握和预测规律性,因此理论模型的建立强调的是一种知识驱动的经验主义。但大数据技术的发展使得数据采集突破了地域性、时间性和规模限制的瓶颈,科学的发现不再依赖于理论模型,分析数据间的相关性即可实现知识的获取,因此大数据主义是一种数据驱动的经验主义认识论,是传统经验主义的继承和发扬。
By combing the concept and perspective of big data-ism, and the origin and historical evolution of empiricism, it is demonstrated that Qi Leilei's new concept of "big data-empiricism" based on the philosophy of new empiricism represented by Nancy Cartwright cannot objectively and comprehensively summarize the philosophical characteristics of big data science, nor does it have the realistic need to represent the humanistic social phenomenon in the era of big data. Therefore, it cannot achieve the transcendence of the concept of big data-ism. In traditional thinking, limited by technology, humans can only observe and collect limited data, then use rational thinking to establish theoretical models, and finally use the deduction of theoretical models to grasp and predict regularity in practice. Therefore, the establishment of theoretical model emphasizes a knowledge-driven empiricism, and the development of big data technology has made data collection break through the bottleneck of regional, temporal and scale constraints. Scientific discovery no longer relies on theoretical models, and the correlation between data can be used to achieve knowledge acquisition. Therefore, big data-ism is a data-driven empirical epistemology, which is the inheritance and development of traditional empiricism.
作者
彭理强
PENG Liqiang(School of Public Management, Hunan Normal University, Changsha Hunan 410081, China)
出处
《长沙大学学报》
2019年第3期82-85,共4页
Journal of Changsha University
