| 马海群,张涛.数据生产力的理据阐释与“新质”力量[J].中国图书馆学报,2025,51(3):50~64 |
| 数据生产力的理据阐释与“新质”力量 |
| The Explanation of Data Productivity and “New Quality” Forces |
| 投稿时间：2024-10-09 修订日期：2024-11-11 |
| DOI： |
| 中文关键词: 新质生产力 数据生产力 数据要素 “新质”力量 |
| 英文关键词: New quality productivity Data productivity Data elements “New quality” forces |
| 基金项目: |
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| 摘要点击次数: 237 |
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| 中文摘要: |
自2023年新质生产力概念提出以来,因其具有向“高”而行的特征,推动了数字经济的高质量发展。数据与新质生产力具有深度耦合与相互塑造的关联,数据要素乘数倍增推动了数据要素价值的创造,并作用于生产、分配、流通、消费环节,催生新质劳动资料、孕育新质劳动对象、培育新质劳动力。本文通过对数据双重属性的揭示,重点从核心要素和转化过程两个方面对数据生产力进行理据阐释,旨在论证从数据赋能生产力所产生的量变到数据作为生产力所带来的质变过程。以此为基础,从新质生产力具有的高科技、高效能和高价值特征挖掘数据生产力所特有的“新质”力量,即覆盖数据流转全生命周期的技术突破实现、多层级数据市场涌现数据创新应用、数实融合创造彰显乘数效应的数据场景。图 2。参考文献46。
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| 英文摘要: |
Since the concept of “new quality productivity” was first put forward,its characteristic of moving towards “high” has enhanced the high quality development of the digital economy. Data and new quality productivity share a tightly coupled and mutually shaping relationship. Data elements multipliers promote the creation of value from data,influencing production,distribution,circulation,and consumption levels. This process generates new quality means of labor,subjects of labor and labor forces. In this process,data itself obtains substantive content,and then becomes a productivity entity. It no longer remains merely an accumulation of external quantity,thus achieving the qualitative leap of the data itself.
Based on the dual nature of production factors and the productivity of data itself,this study aims to provide a theoretical interpretation of data productivity through the three core elements of laborers,means of labor,subjects of labor,and the process of production,distribution,circulation,and consumption conversion. It aims to demonstrate the process of the quantitative change from data enabled productivity to the qualitative change of data as productivityBased on this,it explores the new quality productivity that characterizes data productivity in terms of its high tech,high performance and high value features. Firstly,the realization of technological breakthroughs covers the full life cycle of data flow. This “chokehold technique” breakthrough spanning the full life cycle of data flow has accelerated the integration and innovation of blockchain,artificial intelligence,quantum computing and other emerging technologies,which is an important manifestation of the new quality productivity. Taking smart city construction as an example,this study analyzes the data productivity change in the context of technological innovation which spanns the stages of “collection and storage,management and processing,product creation,sharing and transmission,circulation and transaction,security and compliance”. Secondly,innovative applications of data are emerging within multi tiered data markets,and both data productivity and new quality productivity contribute to the efficient development of the market. The accelerated construction of a multi tiered data market system and the development of data innovation applications from “point” to “chain” to “cluster” are the key driving forces in this process. Thirdly,digital-physical integration creates data scenarios that showcase a multiplier effect. Currently,data processing methods at human disposal have greatly unleashed the power of data. Taking metaverse applications as an example,this study creates data scenarios that demonstrate multiplier effects through digital-physical integration and analyzes the production,distribution,circulation and consumption of data. 2 figs. 46 refs.
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