Papers and patents are becoming less disruptive over time

引用 数据科学 比例(比率) 领域(数学) 技术变革 计算机科学 地理 数学 人工智能 地图学 图书馆学 纯数学
作者
Michael Park,Erin Leahey,Russell J. Funk
出处
期刊:Nature [Nature Portfolio]
卷期号:613 (7942): 138-144 被引量:518
标识
DOI:10.1038/s41586-022-05543-x
摘要

Theories of scientific and technological change view discovery and invention as endogenous processes1,2, wherein previous accumulated knowledge enables future progress by allowing researchers to, in Newton’s words, ‘stand on the shoulders of giants’3–7. Recent decades have witnessed exponential growth in the volume of new scientific and technological knowledge, thereby creating conditions that should be ripe for major advances8,9. Yet contrary to this view, studies suggest that progress is slowing in several major fields10,11. Here, we analyse these claims at scale across six decades, using data on 45 million papers and 3.9 million patents from six large-scale datasets, together with a new quantitative metric—the CD index12—that characterizes how papers and patents change networks of citations in science and technology. We find that papers and patents are increasingly less likely to break with the past in ways that push science and technology in new directions. This pattern holds universally across fields and is robust across multiple different citation- and text-based metrics1,13–17. Subsequently, we link this decline in disruptiveness to a narrowing in the use of previous knowledge, allowing us to reconcile the patterns we observe with the ‘shoulders of giants’ view. We find that the observed declines are unlikely to be driven by changes in the quality of published science, citation practices or field-specific factors. Overall, our results suggest that slowing rates of disruption may reflect a fundamental shift in the nature of science and technology. A decline in disruptive science and technology over time is reported, representing a substantive shift in science and technology, which is attributed in part to the reliance on a narrower set of existing knowledge.
最长约 10秒,即可获得该文献文件

科研通智能强力驱动
Strongly Powered by AbleSci AI
更新
PDF的下载单位、IP信息已删除 (2025-6-4)

科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
1秒前
wanci应助小包包采纳,获得10
1秒前
1秒前
DADing发布了新的文献求助20
1秒前
四叶草发布了新的文献求助50
2秒前
无花果应助ppppp采纳,获得10
3秒前
3秒前
刘运丽发布了新的文献求助10
3秒前
DX发布了新的文献求助10
3秒前
3秒前
小余同学发布了新的文献求助10
3秒前
4秒前
俭朴的三德完成签到,获得积分10
4秒前
可爱的函函应助虾仁采纳,获得10
5秒前
6秒前
6秒前
雄图完成签到,获得积分10
6秒前
CAOHOU举报小夫同学求助涉嫌违规
7秒前
7秒前
7秒前
852应助哈哈哈哈采纳,获得10
7秒前
xc41992发布了新的文献求助10
7秒前
研究生发布了新的文献求助10
7秒前
思源应助ccc采纳,获得20
7秒前
和谐续发布了新的文献求助10
8秒前
研友_851KE8发布了新的文献求助10
8秒前
superbanggg发布了新的文献求助30
8秒前
DX完成签到,获得积分10
8秒前
Jasper应助boyue采纳,获得10
9秒前
yookia应助小光采纳,获得10
9秒前
我是老大应助yangyangyang采纳,获得10
9秒前
思源应助微笑的傲安采纳,获得10
10秒前
zyx发布了新的文献求助10
11秒前
12秒前
13秒前
14秒前
15秒前
16秒前
YHT完成签到,获得积分10
16秒前
ppppp发布了新的文献求助10
16秒前
高分求助中
The Mother of All Tableaux Order, Equivalence, and Geometry in the Large-scale Structure of Optimality Theory 2400
Ophthalmic Equipment Market by Devices(surgical: vitreorentinal,IOLs,OVDs,contact lens,RGP lens,backflush,diagnostic&monitoring:OCT,actorefractor,keratometer,tonometer,ophthalmoscpe,OVD), End User,Buying Criteria-Global Forecast to2029 2000
Cognitive Neuroscience: The Biology of the Mind 1000
Cognitive Neuroscience: The Biology of the Mind (Sixth Edition) 1000
Optimal Transport: A Comprehensive Introduction to Modeling, Analysis, Simulation, Applications 800
Official Methods of Analysis of AOAC INTERNATIONAL 600
ACSM’s Guidelines for Exercise Testing and Prescription, 12th edition 588
热门求助领域 (近24小时)
化学 材料科学 医学 生物 工程类 有机化学 生物化学 物理 内科学 纳米技术 计算机科学 化学工程 复合材料 遗传学 基因 物理化学 催化作用 冶金 细胞生物学 免疫学
热门帖子
关注 科研通微信公众号,转发送积分 3958299
求助须知:如何正确求助?哪些是违规求助? 3504528
关于积分的说明 11118735
捐赠科研通 3235777
什么是DOI,文献DOI怎么找? 1788506
邀请新用户注册赠送积分活动 871225
科研通“疑难数据库(出版商)”最低求助积分说明 802600