기초학문연구의 제도와 정책(2): 대학 연구 인센티브 변화 및 효과 (Changes and Effects of University Research Incentives)
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Korean Abstract: 대학의 연구환경은 큰 변화를 겪고 있다. 대학은, 전통적인 교육․훈련 기능과, 자율과 창의에 기초한 자유로운 연구 또는 공공재로서 연구성과를 창출하는 지금까지의 역할에 추가하여 국민․지역 경제의 성장이나 사회경제적 당면 문제 해결에 보다 직접적으로 기여해야 한다는 요구가 커지고 있다. 이러한 요구에 부응하여, 대학이 지식재산권을 소유하고 이를 사업화하여 수익을 창출하도록 허용하는 제도의 도입, 이른바 바이-돌 체제로의 전환이 미국을 필두로 많은 나라에서 이루어졌다. 바이-돌 법 제정의 기본 취지는 소유권을 대학 및 민간기업에 허용함으로써 공적자금을 투입한 연구의 활용을 촉진하는 데 있다. 그러나 기본 취지와 성과에도 불구하고 새로운 체제에 대한 비판 또한 계속 제기되고 있다. 가장 근본적인 것은, 공공연구 성과의 사유화는 공공연구에 대한 정부지원의 논리적 근거에 배치되며 공공재 또는 과학적 공유재로서 지식 창출을 통한 사회에의 기여라는 대학의 가장 근원적인 미션을 수행하는 데도 배치된다는 비판이다. 또한 미국에 이어 유럽과 일본도 유사한 제도를 도입하였음에도 왜 미국에 버금가는 성과를 내지 못하는가라는 문제도 제기되고 있다.(이하 생략) English Abstract: In addition to conventional missions of education and research, universities are facing new demands to make more direct contribution to economic growth. Commercializing university research is a response to this new requirement. The US Bayh-Dole Act in 1980 is considered one of the key institutional arrangements which were intended to promote this trend. Despite the debate over the contributions and the seamy effects of the new institutional framework, the overall results of Bayh-Dole act are considered rather positively. After the US, many other countries have introduced similar laws at Bayh-Dole act. However, the outcomes are variously different; most of countries have not been successful in producing similar results as in the US.Korea had introduced similar laws in the last decade. On the one hand, despite very late start, compared to other countries, such as US, Canada, Japan, and some European countries like Spain, Korea is showing very rapid, positive changes in university commercialization activities. On the other hand, however, there are many rooms for further improvement for university’s research commercialization activities in Korea. Based on the lessons derived from other countries’ experiences, the following points are worth mention: (1) University-industry collaboration attracts more attention than before, since the linkage with public research system is increasingly important in technological innovation of the industry and business enterprises. There are various channels for universities to cooperate with industry: patenting and licensing are among those. Therefore, commercialization of university research should be viewed from a wider context of university-industry collaboration. (2) The promotion of commercializing activities should not harm the core missions of university, namely education and research. It is generally argued that Bayh-Dole Act did not constrict a basic research activity of university but this argument is still being questioned. In case of Korean universities, licensing comprises only tiny share of incomes for various university-industry collaboration activities. Upgrading research capabilities is the most important, urgent task for university policies. (3) The Industry-University collaboration system in Korea concentrates on quantitative performance indicators. Royalty income in Korean universities is significantly low in terms of the number of patents in comparison with other countries. It is due to the fact that universities count the number of patents for the performance evaluation of faculty so that patent applications are over issued despite no or little business value. It is necessary to modify the current evaluation and reward systems to reflect substantive outcomes including patent values.(4) Experiences from UK offer a valuable lesson for Korea: government initiatives focusing on the ‘blind spot’ are effective in fostering commercialization activities. Successful commercialization does require coping with risks in the market; academic research usually is poor at dealing with. Government’s ‘additional’ support can make the outcome far more successful.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.006 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.000 | 0.007 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it