Inequality in Global Scientific Research: Implications for Novelty and Innovation

研究人员跨国界合作，科学家出国发展他们的职业生涯，新发现通过范围和地点日益国际化的期刊和会议广泛传播。决策者和科学家的假设是，全球化有利于研究，促进知识生产，特别是对资源较少国家的研究人员而言。有广泛的研究表明，科学家的经验和观点的多样性，特别是在多学科合作中，往往会在公开合作解决问题的企业中产生更好的解决方案。然而，研究人员可能会过早地结合现成的，但也许是次优的，解决方案，他们的工作，作为科学知识，无论是体现在同行评议的期刊或全球人际网络，更容易获得大量和需求。只有少数国家能够获得维持尖端科学研究所需的资源，这扩大了现有知识的影响。那些这样做的国家可能会越来越多地影响重要的话题，并隐含地设定科学领域的议程，可能会阻碍科学话语并扼杀创新。该项目旨在通过开发方法，指标和分析方法来提高对社会有益的科学发现的速度，这些方法，指标和分析方法可以识别由于同质化而随着时间的推移可能不那么新颖的领域，以及落后于同行的国家。 该项目将使用集成自然语言处理和社交网络分析的创新分析工具，在全球范围内对科学影响力和新奇进行建模。自然语言处理揭示了大规模科学媒介中包含的影响和知识（即，学术出版物中的文本），而社会网络分析则从结构上追踪了国家之间和时间上的这种影响。该项目有五个主要目标：1）使用科学出版物的摘要创建跨不同领域的国际影响力网络，2）将基于网络的不平等措施应用于这些网络，以展示不同领域和国家随时间的趋势，3）将新奇得分应用于这些领域中的每个国家，4）将国际影响力网络中日益增长的不平等措施与新奇得分联系起来，（5）确定在哪些领域和国家，这种影响力的不平等以及新奇事物的兴起或衰落最严重和最不严重。该项目的指导假设是，在一系列科学领域，影响力越来越多地来自高度发达国家的一小部分。他们对其他国家的科学研究的影响不平等，导致世界各地在许多领域的研究同质化。随着一个领域的影响力日益集中，研究课题在各国之间变得越来越相似，全球性的新奇想法减少了。该奖项反映了NSF的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

Researchers collaborate across national borders, scientists move abroad to further their careers, and new discoveries are widely disseminated via journals and conferences that are increasingly international in scope and locale. The presumption held by policy makers and scientists is that globalization benefits research and enhances knowledge production, especially for researchers in countries with fewer resources. There is extensive research to suggest that diversity of experiences and perspectives in scientists, specifically in multidisciplinary collaborations, tends to yield better solutions in openly collaborative problem-solving ventures. However, researchers may prematurely coalesce on readily available, but perhaps suboptimal, solutions to their work, as scientific knowledge—whether embodied by peer-reviewed journals or global interpersonal networks—is more readily accessible in high volume and on demand. Amplifying the influence of readily available knowledge is that only a few countries are able to garner the resources needed to sustain cutting-edge scientific research. Those countries that do may increasingly influence what is topically important and implicitly set the agenda for scientific fields, potentially homogenizing scientific discourse and stifling innovation. This project aims to improve the rate of socially beneficial scientific discovery by developing methods, indicators, and analytic approaches that identify fields that may be less novel over time due to homogenization, as well as countries that lag behind their peers. This project will model scientific influence and novelty on a global level using innovative analysis tools that integrate natural language processing and social network analysis. Natural language processing uncovers influence and knowledge contained in the medium of science at scale (i.e., the text found in academic publications), while social network analysis structurally traces this influence between countries and over time. The project has five key objectives: to 1) create international networks of influence across diverse fields using the abstracts of scientific publications, 2) apply network-based measures of inequality to these networks to demonstrate trends over time in different fields and countries, 3) apply novelty scores to countries in each of these fields, 4) relate measures of growing inequality in international influence networks to novelty scores, and 5) identify the fields and countries where this inequality in influence and the rising or waning novelty is the most and least severe. The project’s guiding hypothesis is that across a range of scientific fields, influence increasingly originates from a smaller sect of highly developed countries. Their unequal influence on science performed in other countries results in a homogenization of what is researched around the world in many fields. As influence in a field is increasingly concentrated and research topics become increasingly similar across borders, the global novelty of ideas declines.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.