과학후속세대를 위한 한국 과학기술의 글로벌 소프트파워 제고 방안 - 스타과학자를 중심으로

다국어 초록 (Multilingual Abstract)

The enhancement way of the global soft power of Korean science and technology for the follow-up generation: focusing on star scientists

ㆍProject Leader: Hyonik Lee
ㆍParticipants: Hyunchae Yang·Sungjoo Hong·Seunghwa Jin·Yeonglin Kim

For centuries, the world, conditioned by Malthus's population theory (Malthus, T. R., 1986), has relied solely on imagination premised on expansion. This is because the history of the world has been dominated by growth for the past century or so. The expanding world seemed to be eternal. The industrial and information revolutions, which were based on technological progress, have taken root in human history as a result of globalization and have borne the fruit of economic development. And this phenomenon has changed the global population structure. For humans, the problem has always been that there are too many people. Economic development brought about by industrialization has reduced the infant mortality rate and increased the average life expectancy of humanity. Urbanization has accelerated this phenomenon.
The industrial revolution and information revolution, which were based on technological progress, have taken root in human history as a result of globalization and have borne the fruit of economic development. And this phenomenon has changed the population structure of the world. Population has always been a problem for humanity. Economic development through industrialization has reduced the infant mortality rate and increased the average life expectancy of humanity. As industrialization began, women's fertility rates declined, but the expanding world did not take this as a major problem. Rather, it seemed to be finding its own natural balance, where it could achieve sustainable growth by maintaining an appropriate population size. The theory of economic growth proposed by some rational economists (Solow, 1956) was even used as a rationale for encouraging birth control in countries in the early stages of economic development. In the meantime, the world naturally aged and slowed down.
The national strategy of a shrinking world cannot be the same as that of an expanding world. According to the United Nations World Population Prospects (2022), the population of major countries, except for the United States and the United Kingdom, will decrease significantly by 2055. Japan's population will decrease from 125 million (2020) to a level that barely maintains 100 million (-19.95%), and South Korea's population will decrease by 16.14% to 43 million. The population of 50 million will collapse. Germany will also see a population decline of nearly 7% as the population falls below 80 million. China will lose nearly 200 million people. Japan's population will drop from 125 million (2020) to a level that barely maintains 100 million (-19.95%), and South Korea's population will drop by 16.14% to 43 million. This means that the population of 50 million will collapse. Germany will also lose nearly 7% of its population, falling below the 80 million mark. In the next 30 years, two countries the size of Japan will disappear. This is the result of looking at the mid-level (med) of the forecast scenario. A more dire scenario (high) predicts even greater population declines in more countries. The population size forecast for 2100 is even more bleak. China will shrink to 770 million people, well below the one billion mark. South Korea will not exceed 25 million people.
This is the result of the mid-level (med) of the forecast scenario. The more pessimistic scenario (high) predicts even greater population declines in more countries. The population size forecast for 2100 is even more bleak.
China will fall below 770 million, a long way from the 1 billion population mark. Major countries such as Germany (69 million), Japan (74 million), France (61 million), and the UK (70 million) are expected to maintain their population at 60 to 70 million, while only the US (390 million) and the UK are expected to see an increase. From a global perspective, South Korea is a country that is in the midst of concerns about population extinction.
This project is a study that looks at the level of the science and technology innovation environment, which has been mainly measured and managed from the perspective of suppliers, from the perspective of attractiveness from the perspective of researchers. By deriving the need for policy formulation and the details of the policy to create an innovative environment that scientists and researchers, the ultimate beneficiaries of science and technology innovation policies, want (and find attractive), we will propose new indicators for managing the goals of national projects and provide a clue for enhancing the attractiveness of the innovative environment.
The research question that runs through the core of this project is,
“Is the innovation environment in Korea attractive to researchers and scientists?”
The table of contents of this project consists of three major parts as follows.
First, we will discuss the importance of enhancing the ease of doing research. Starting with a discussion on the shrinking world and demographics, we will look at the impact of the decline in research personnel on productivity, and give meaning to the role of researchers who have secured the ease of knowledge production. Through this, we hope to raise awareness of the need to restructure our innovation policies as a whole through research to increase the attractiveness of the National Innovation System (NIS). In addition, we will present indicators for effective management of national tasks to ensure the effectiveness of government policies and enhance the clarity of policy goals.
Second, we will analyze and diagnose the current situation using various previous studies and indicators to see if there are any ways to make researchers and researchers with excellent productivity choose our innovation environment.
Through this, we will raise awareness of the need for a structural transformation of our overall innovation policy through research to increase the attractiveness of the National Innovation System (NIS).
In addition, we will present indicators for effective management of national projects to ensure the effectiveness of government policies and enhance the clarity of policy goals.
The second is to analyze and diagnose Based on this, we will try to derive policy implications through interviews with relevant researchers.
Second, we will analyze and diagnose the current situation using various previous studies and indicators to see if there are any ways to make researchers and researchers with excellent performance choose our innovation environment.
Based on this, we will try to derive policy implications through interviews with relevant researchers. In particular, by setting the interview targets in a future-oriented manner, we will try to present novel, specific, and realistic policy alternatives for the next generation of scientists who will lead our innovation ecosystem.
According to the production function based on the growth accounting model, long-term growth can be decomposed into the product of two variables: the number of researchers and research productivity. Analysis suggests that a certain level of economic growth is maintained due to a decrease in research productivity despite an increase in the effort put into research, and we have discussed the extensive empirical evidence that suggests this. In other words, a certain level of long-term economic growth is observed as the opposing trends of the two variables presented cancel each other out. The study by Bloom et al. (2020), which is an economic answer to the question “Are ideas getting harder to find?”, can be summarized as follows: a certain level of long-term (economic) growth is observed through the input of research personnel that offsets the declining research productivity.
The study by Bloom et al. (2020), which is an economic answer to the question “Are ideas getting harder to find?”, can be summarized as follows: a certain level of long-term (economic) growth is observed through the input of research personnel to offset the declining research productivity. It shows that the US growth rate of 2% per year from the 1930s to the present has been achieved by increasing the number of researchers to offset the falling research productivity. Even without going through any special logical thinking, it is obvious that the falling number of researchers will inevitably lead to a mechanism (TO-BE) that will cause the economy to grow at a slower rate.
The number of researchers is expected to decrease in most major countries, with some countries showing a maintenance level of increase, while relatively large increases are expected in the US and the UK. If the number of researchers in the eight major countries, which include the United States, China, the United Kingdom, Germany, France, Italy, Japan, and South Korea, is set at 100, China ranks first at 36.86% as of 2022, followed by the United States (25.12%), Japan (10.81%), South Korea (7.49%), Germany (7.43%), France (5.30%), the United Kingdom (4.53%), and Italy (2.46%). By 2055, the proportion will be as follows: China (34.83%), the United States (29.71%), Japan (8.93%), Germany (6.85%), South Korea (6.52%), France (5.61%), the United Kingdom (5.43%), and Italy (2. 12%) with Germany and South Korea overtaking Germany and South Korea, and by 2100, the ranking changes to the United States (40.95%), China (23.19%), Japan (8.31%), Germany (7.78%), France (7.12%), the United Kingdom (6.71%), South Korea (4.08%), and Italy (1.85%). The prediction of the number of researchers by country based on statistics and logic is simple, but the ripple effect that will occur as the composition of human resources by country that embody global innovation changes completely will be much more complex.
In summary, most countries will soon face a population cliff, and this phenomenon will gradually intensify, eventually leading to the year when the number of births will be less than the number of deaths (2064), and the world will shrink. This demographic change will not only reduce the number of workers, but also affect researchers who are at the forefront of innovation. When workers and researchers disappear, the ideas that have driven sustainable economic growth disappear.
In summary, most countries will soon face a population cliff, and this phenomenon will gradually intensify, eventually leading to a year (2064) when the number of births is less than the number of deaths, and the world will shrink. This is the conclusion of the predetermined future.
This population change will not only reduce the number of workers, but also affect researchers who are at the forefront of innovation. Economic growth will stagnate and eventually go into reverse. Many economists who have published the research results discussed above are concerned about the bleak future of economic growth dominated by demographics, and they argue that new ideas must be constantly generated for sustainable growth. The reason why the influx of a young population with guaranteed productivity is important to maintain a country's innovation capacity is also rooted in the economic perspective that many ideas from researchers can improve productivity, thereby achieving sustainable economic growth and raising the standard of living we are leading.
We can identify them as researchers, a group of people with the imagination to influence the world of tomorrow, and a world where they are becoming increasingly scarce has already become a foregone future. And this fact means that the fundamental perspective on innovation policies for researchers must change.
A catalyst is any substance that participates in a chemical reaction process and changes the reaction speed without being consumed. In an innovation system, star scientists play a role in strengthening the innovation achievements within their network without consuming their own capabilities, just like a catalyst in a chemical reaction. A star scientist can be defined as a scientist who is affiliated with an institution, including universities, research institutes, and companies, who has outstanding achievements as a researcher and is involved in the transfer of knowledge in any form, either formal or informal. They differ from ordinary scientists in the following three aspects: (1) outstanding research productivity, (2) the motivation and incentive system they respond to, and (3) high mobility.
In previous studies on measuring and comparing the research productivity of scientists (researchers), the common outputs used are papers and patents.
Star scientists can be defined as scientists who belong to institutions, including universities, research institutes, and companies, who have outstanding achievements as researchers and are involved in knowledge transfer in any form, either formal or informal. Therefore, this study attempts to measure the productivity of (star) scientists by limiting it to papers and patents.
This represents the productivity of 4,954,238 researchers who published 16,888,165 papers in seven major countries over 11 years from 2013 to 2023. The seven countries with the highest R&D spending were selected as the countries to be analyzed, including South Korea, the United States, China, the United Kingdom, Germany, France, and Japan.
In South Korea, 230,000 researchers (4.6% of the total 4,954,238 researchers) published 790,000 papers (4.7%). The average number of papers by a highly cited researcher (HCR) was 139.65, which is about 25 times higher than the average of 5.52 for other researchers. In terms of times cited, the average number of citations for star scientists was 9,958.47, which is more than 157 times higher than the average number of citations for other researchers (63.39). In terms of the normalized citation impact by field, star scientists have a level of 5.23, which is 7.16 times higher than that of general scientists (0.73), and in terms of the H-index, the level is 15.23 (star scientists 39.3, general scientists 2.58), the number of citations of patents is 165.55 (star scientists 51.32, general scientists 0.31), and the number of international joint papers is 67. 1 times (star scientist 67.1, general scientist 1.00), number of joint papers with companies 30.75 times (star scientist 6.15, general scientist 0.20), citation impact 13.71 times (star scientist 135.3, general scientist 9.87), it was analyzed that star scientists show superior productivity compared to general researchers. In particular, they surpassed the productivity of ordinary researchers in terms of the number of citations of papers in patents, the total number of citations, and the number of international joint papers, which can be interpreted as remarkable results in that the ripple effect of research results is leading to practical applications (patents) and international cooperation.
The analysis target for measuring patent productivity was limited to 1,667,137 registered patents in the United States from 2018 to 2022.
The top 1% of quantitative patent productivity in each indicator is not much different from the 99%, and in most countries, inventors in the 99% group are producing more quantitatively. However, it was analyzed that there is a difference in productivity of tens to thousands of times for qualitative productivity indicators (per capita) such as the number of citations, CPP, PII, TS, and highly cited patent index.
We analyzed information on the execution status and performance of national research and development projects for each year from 2012 to 2020 for 86 researchers who had been selected for the HCR from 2014 to 2020 and the remaining researchers. Of the 86 star researchers, 81 were men and 5 were women, and of the 106,243 general researchers analyzed, 90,316 were men and 15,927 were women.
The average number of projects per year was 13.2 per star scientist, 3.1 times higher than the 4.3 projects per general researcher, and the average project amount was 95.2 (star scientist) and 12.7 (general researcher), showing a difference of 7.5 times. As for the results of the investment, in the case of SCIE papers, star scientists published an average of 71.3 papers per person per year, while ordinary researchers published 2.9 papers, showing that star scientists are 24.2 times more productive. Even taking into account the difference in input, it can be seen that scientists with a history of HCR selection show significantly higher productivity. They also showed a significant difference in patents from general researchers, with a larger difference in overseas applications (2.3 for star scientists, 0.4 for general researchers) than in domestic applications (17.0 for star scientists, 6.8 for general researchers).
Based on the analysis of the productivity of star scientists based on the data of papers and patents, star scientists boast superior productivity in all indicators, ranging from tens to thousands of times that of ordinary researchers. This pattern is also seen in the performance of the Korean government's support, and the productivity of the group of star scientists in the performance of the national research and development project is generally analyzed to be overwhelming that of the group of ordinary researchers. Even after taking into account the difference in input per person and the difference in scale between the groups, it is true that the policies in our innovation environment have been implemented with a distance from the researcher excellence, while scientists with a history of HCR selection have shown much higher productivity.
The analysis of the productivity of star scientists based on papers and patent data shows that star scientists boast superior productivity by tens to thousands of times compared to ordinary researchers in all indicators.
This is the same pattern in the performance of government support in Korea, and the productivity of the star scientist The 3 Books and 5 Parks system has provided an environment where a specific researcher cannot monopolize a large number of projects, and the policy has been arranged so that the research funds per project are continuously reduced so that more researchers can be given equal opportunities. There is no denying that this series of policies, which were promoted to expand the base of research, have brought diversity to the barren academic soil of Korea.
It is true that the policies that have been implemented to expand the base of research have brought diversity to the barren academic soil of Korea. However, at the same time, it is also true that the government's policy signals have been distorted as it has exhausted the capacity of policy incentives to enhance the excellence of researchers. In other words, it can be said that the government has not sufficiently motivated researchers to improve their excellence by focusing too much on the fairness of researchers.
The government has provided an environment in which a specific researcher cannot monopolize a large number of projects through the Three Books and Five-Sphere System, and has made policy arrangements to ensure that more researchers have equal opportunities by continuously reducing the research funds per project.
However, at the same time, it is also true that the government's policy signals have been distorted as it has exhausted the capacity of policy incentives to enhance the excellence of researchers.
Over the past decade, our overall talent competitiveness has risen from the top 27% (in 2013) to 18% (in 2023), but the trend in terms of competition for human resources has been the opposite.
In other words, the government's policy signals have been distorted as it has exhausted the capacity for policy incentives to improve the excellence of researchers. In other words, the government's policy signals have been distorted as it has exhausted the capacity for policy incentives to improve the excellence of researchers. The brain gain, an indicator of the inflow of excellent human resources, has dropped significantly from 15th place in 2013 to 59th place in 2023, while the level of talent retention has remained unchanged at 24th place. If we apply this phenomenon to the “brain game” of the competition for human resources in terms of the net total of brain drain and brain gain, we come to the conclusion that we are clearly playing a losing game. We can think that the root of this trend is that our innovation environment is not attractive enough to researchers and scientists. Therefore, if we are to gain a positive advantage in the brain game, we will need to entice researchers (scientists) to choose our innovation environment because it is attractive.
Is our innovation environment attractive enough? If not, what can be improved?
We can think that the reason for this trend is that our innovation environment is not attractive enough to researchers and scientists.
Therefore, if we want to gain a positive advantage in the brain game, we will need to attract researchers (scientists) to choose our innovation environment because it is attractive.
Is our innovation environment attractive enough? If not, what can be improved?
The answer to the above question seems to have already been concluded by the researchers themselves. Therefore, this study was meaningful in that it attempted to identify policy needs to improve researcher productivity by conducting in-depth interviews with researchers to enhance the attractiveness of the National Innovation System (NIS) for the next generation of scientists.
“Research environment that allows for the pursuit of original research topics”
One keyword that ran through the in-depth interviews conducted for this study was “originality.” For the interviewees, a star scientist was synonymous with a researcher who wrestled with an original topic. In the end, the various improvement plans for the government innovation system that they ordered were nothing more than a request to lower the threshold they had to overcome in order to conduct a lot of original research.
At first glance, this may sound like a natural and vague story, but we need to reflect on whether our innovation environment has failed to build a system that is so natural that many people have left and has prevented the necessary people from entering. In the end, the free research environment that researchers wanted was not an abstract idea, but an environment where researchers could work with researchers who are good at the research they want to do, and where there are no major obstacles to this.
As I conducted the interviews, I realized that there was no research innovation policy to improve the ease of researchers, and that the government's role as a signal to encourage researchers to pursue ease was important. The paradigm shift in innovation policy should start with a change in the government's signals. The government has made efforts to enhance the attractiveness of our innovation environment from the perspective of suppliers by providing quantitative support for R&D and improving various systems. Nevertheless, it is necessary to reflect on whether the government has conducted a sober assessment of the extent to which the efforts have had a tangible effect from the perspective of consumers (researchers) and whether they have indeed led their research activities in a desirable direction.
As the amount of research funding per task for researchers has decreased, the government has encouraged researchers to take on as many research tasks as possible to maximize their chances of winning the 3-book, 5-publication system, and to be recognized as “scientists who do good research.” Rather than pioneering the world's first research field through international collaboration, did the government not force collaboration between researchers who were optimized for the domestic government research funding support system? Was it not the case that the researchers themselves were discouraged from conducting challenging and innovative research because of the overly short-sighted logic that they could only pursue performance-based research because it was funded by the people's taxes? And above all, while having a vague understanding of all these situations, were the policymakers and related parties not just doing their best to manage the situation so that it would not get worse, using the excuse that it was an “unavoidable choice”? They should take a good look at this at least once.

국문 초록 (Abstract)

[연구목적]
○ 국가 혁신시스템(NIS)의 매력도 증진을 위한 한국 과학기술의 글로벌 소프트 파워 제고 방안에 관한 연구를 통해 우리의 혁신 정책 전반의 구조 전환 필요성 환기
○ 특히, 앞으로 우리의 혁신 생태계를 이끌어나갈 과학후속세대를 위하여 참신하면서도, 구체적이고 현실적인 정책 대안 제시

[주요내용]
○ 스타과학자의 정의 및 국정과제(76) 관리지표 제시
※ 윤석열 정부 120대 국정과제(76): 기초연구분야 세계 최고 수준의 선도 연구자(HCR 등) 2배 확대의 정량적 목표달성을 위한 선도 연구자 정의 및 관련 신규 지표 개발
○ 우리나라 R&D 혁신시스템 내에서의 스타과학자 역할과 성과에 대한 정량 및 정성적 분석을 통한 정책적 시사점 도출
○ 스타과학자 지원 관점에서 한국 과학기술의 소프트파워 제고를 위한 정책 제언
※ (가칭) Scientific Soft power 복합지수 개발 및 관리를 통한 정책 목표와 효과에 관한 질적 지표 제시

[정책대안]
○ 거대 패권 경쟁에 대응하는 한국의 ‘페이퍼클립’ 정책 방향성 설계 및 구체화
○ 한국의 ‘제이슨 그룹’* 활약을 위한 수월성, 개방성 중심의 정부 R&D 지원시스템 구조개선
* 1960년 결성된 미 국방부 산하의 과학 자문 집단으로 그리스 신화의 제이슨(Jason)과 아르고노트(Argonaut) 원정대로부터 착안하여 명명
○ 혁신환경의 매력도 제고를 위한 국가전략 수립
- 언어장벽 해소, 높은 경쟁력을 가진 연구 기관 육성, 다양한 펀딩 기회 제공 등 혁신환경의 매력도 증진을 위한 국가 차원의 통합된 전략 수립이 요구

목차 (Table of Contents)

• 국문 요약 i
• 영문 요약 I
• 제1장 연구인력 감소 시대: 지식의 생산과 연구자원 투입 관계 1
• 제1절 축소하는 세계와 인구학 1
• 제2절 연구 생산성과 경제성장 13
• 제3절 연구인력 감소가 지식 생산에 미치는 영향 25
• 제2장 스타과학자의 생산성은 왜 중요한가 35
• 제1절 스타과학자와 연구 생산성 35
• 제2절 연구 생산성 측정의 프레임워크 52
• 제3절 논문 및 특허 생산성 비교 분석: 스타과학자의 중요성 66
• 1. 논문 생산성 비교 분석 66
• 2. 특허 생산성 비교 분석 74
• 제3장 정부R&D 성과와 연구자 수월성 85
• 제1절 우리나라 스타과학자 현황 85
• 제2절 스타과학자의 정부R&D 투자 성과 88
• 제3절 연구자 수월성 확보의 중요성 94
• 제4장 연구자의 이동에 관하여 97
• 제1절 연구자의 이동성 분석 97
• 제2절 이동의 요인 및 시사점 104
• 제5장 과학후속세대가 원하는 매력적인 혁신환경 112
• 제1절 과학후속세대 중심의 인터뷰 추진 및 수요 유형화 112
• 제2절 추진 결과 및 시사점 116
• 1. 추진 내용 116
• 2. 시사점 141
• 제6장 요약 및 정책적 시사점 145
• 제1절 축소하는 세계와 혁신정책 패러다임의 전환 145
• 제2절 정책적 시사점 150
• 참고문헌 159