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Innovating evaluation system for sci-tech talent

LIU YUN | 2021-06-24 | Hits:
(Chinese Social Sciences Today)

A recruitment fair, combining online recruitment and on-site negotiation, held on April 13, for doctoral research talent and urgently needed talent in Guangzhou, Guangdong Province Photo: CFP

The Fifth Plenary Session of the 19th CPC Central Committee highlighted that “innovation remains at the heart of China’s modernization drive. We will strengthen our science and technology to provide strategic support for China’s development.” Chinese President Xi Jinping stressed the key role of talent in innovation-driven development.

How do we effectively bring the role of sci-tech talent into greater strength? By respecting sci-tech innovation rules and talent development rules, establishing reasonable and effective evaluation and reward mechanisms for sci-tech talent, constantly improving the developmental environment for talent, spurring the innovative vitality of talent, and adapting fully to the country’s strategic needs for development in the new era.
In practice, sci-tech evaluation systems significantly influence how talent performs. As early as the beginning of 2000, the sci-tech evaluation system had yet to be improved. In 2003, the issuance of “Decision on Improvement in the work of Sci-tech Evaluation” highlighted the implementation of classification and putting quality first. “Measures for Science and Technology Evaluation (Trial)” offered a detailed guide for the sci-tech evaluation process, the selection of experts, and sci-tech planning, which includes assessment of projects, institutions, personnel, and achievements. These two documents signified the preliminary establishment of China’s sci-tech evaluation system in line with international standards. The following interventions are suggested to orient sci-tech evaluation systems towards innovation, quality, effectiveness, and contribution.
Mechanism reform
It is advisable to establish sci-tech talent evaluation concepts led by an overarching understanding of “talent cultivation at a macro scale” “comprehensive development” and “dynamic development.”
Regarding the concept of “talent cultivation at a macro scale” we should create an ecosystem suitable for the growth of innovative talent, allowing  everyone to develop their skills and display their abilities, as this is the foundation for cultivating and promoting the growth of talent.
The concept of “comprehensive development” not only emphasizes the instillation of knowledge, but also highlights the cultivation of innovative thinking, qualities, capabilities, as well as the cultivation of political awareness, cultural literacy, social responsibility, and a patriotic spirit.
“Dynamic development” brings attention to the dynamic evolution of talent’s development potential and ability to innovate. Instead of treating talent statically, permanently labeling people with a talent title, or artificially labeling talent, employers should strive to create an ecosystem for growth where people make the best use of their talents to stand out. In the sci-tech field, we need an ecosystem where people can dare to be the first, to create, to take risks, to doubt and criticize, where failures are tolerated, free explorations are encouraged, academic democracy is developed, and academic contention is supported.
It is advisable to abandon the  “paper-, title-, diploma-, and award-centric” (four-centric) approach  to talent evaluation. Even though a series of related policies have been set up by the central government, the approach still exists in several local areas and employment units. Therefore, in the spirit of CPC Central Committee policies, relevant departments should actively promote the existing management methods in scientific projects, talent projects, title-appraisal systems, the use of funds, and institutional evaluations in local and higher education institutions.   
These improvements would disrupt the four-centric phenomenon, which should be fundamentally addressed from the root of mechanism design. To deepen reform of sci-tech talent, the utilitarianism of talent projects should be restricted. Sci-tech talent programs are funding programs for young talent of a specific age, with limited periods for project implementation. The talent funded by those programs should not be permanently labeled. Also, talent award program winners should not receive excessive packages.
Based on the observation of sci-tech innovation laws, it is important to establish the sci-tech talent evaluation standard system through classification. In accordance with the nature of sci-tech talent’s work and the characteristics of sci-tech activities, talent in this field can be classified into different types including: basic research, applied research and technological development, research of social welfare, experimental technologies, sci-tech management and services.
On the basis of this classification, talent evaluation systems highlight medium- and long-term goals, emphasizing the evaluation of representative achievements, and focusing on evaluations of performance and potential. As evaluations for processes and results combine, mechanisms are improved for fault tolerance and liability exemptions, creating a sound ecosystem that encourages innovation, tolerates failures, and is committed to research.
Meanwhile, a dynamic adjustment mechanism should be established, to encourage sci-tech talent to contribute in different fields and in different positions. We should improve, in accordance to the classification, talent evaluation standards which assess morality, ability, performance and other factors, highlighting innovation quality, coordinating capability and performance, incorporating team contributions, and implementing differentiated evaluation, avoiding the one-size-fits-all approach of sci-tech talent evaluation in varied disciplines and fields at different development stages.
Multi-subject evaluation
It is advisable to establish an evaluation governance system based on peer review, actively inviting multiple evaluation actors such as market evaluations and social evaluations.
As talent comes from different employment units and departments, with varied academic levels and types, differentiated evaluation subjects should be incorporated in the process.
Meanwhile, evaluation methods are in need of constant enrichment, as the nation adopts more specific and accurate evaluation methods for different occupations and positions by applying examinations, reviews, combinations of exams and evaluation, assessment, personal work reports, interviews, practical operations, performance presentations and other methods.
Channels for sci-tech associations and enterprises should be broadened, allowing the public to participate in the evaluation. It is also important to actively develop third-party evaluation institutions for sci-tech talent, and encourage academic groups and professional institutions to carry out independent evaluations. 
It is important to underline work capabilities of different types of sci-tech talent while employment units play a dominant role. The research abilities, academic impact, and contributions of basic research talent must be highlighted, with a focus on evaluating their abilities to grasp innovation trends in the field of basic sciences, and their abilities to propose, analyze, and solve major scientific problems, to motivate research team development, and promote the development of disciplines. It is vital to emphasize technological innovation, achievement transformation, and industrial development contributions of applied R&D talent, with a focus on evaluating their abilities to grasp cutting-edge technology developments within their professional fields, to innovate and integrate common core technologies, to commercialize and industrialize achievements in innovation, and to drive industrial transformation and upgrading.
The evaluation system needs to highlight the abilities, quality, and effects of social services, technological support, and the scientific management of talent in the field of  social welfare, experimental technology development and sci-tech management. For social welfare talent, evaluations should emphasize research on social, civil, and industrial development hotspots, the ability to consult and propose development suggestions, and provide advice on decision making. As for the evaluation of experimental technological talent, the evaluation focus needs to be centered on their experimental skills, operational capabilities and work efficiency. When evaluating scientific management talent, the importance should be on their abilities to formulate scientific development plans, to organize and implement scientific projects, as well as coordinate and manage major scientific events.
In accordance with their own functional positioning and development directions, employment units should also refine their evaluation criteria. A reasonable evaluation cycle for differentiated types of sci-tech talent must be set. Evaluation cycles for basic research personnel and young sci-tech talent need extension. It is advisable to conduct tenure review. Green channels should be created for urgently needed and high-level sci-tech talent. The evaluation results must be employed correctly, to promote the integration of talent evaluation, cultivation, utilization, and motivation.
Supportive measures
The supporting measures for the evaluation of sci-tech talent also need improvement. It is advisable to further strengthen systematic, holistic, and collaborative evaluation reform, and its full implementation.
As China increases policy advocacy efforts, we must also simplify evaluation procedures.  It is important to gradually establish standardized and professional evaluation management systems, and optimize evaluation processes, while avoiding multiple, frequent, and repeated talent assessments, so as to effectively alleviate talent’s burden.
It is vital to smooth channels for evaluation. We need to improve the channels for application and evaluation of sci-tech talent in non-public economic organizations, social organizations, and emerging occupations. As the evaluation ecosystem is optimized, the construction of study styles is strengthened. It is necessary to develop the responsibility and credit system for evaluation experts, rating scientific researchers, and monitoring research institutions and other evaluators. It is also important to strengthen investigations into and punishments for misconduct in scientific research.
The country is working to improve the credibility of evaluation, establish and improve systems for information disclosure, feedback, appeals, supervision, and backtracking. By implementing trace management for the whole evaluation process, and accepting supervision of society, China will make the evaluation of sci-tech talent truly fair, just, and open.
Liu Yun is a professor from the School of Public Policy and Management at University of Chinese Academy of Sciences.
Edited by ZHAO YUAN