一、评价依据
Talent competitiveness is hard to characterize with a single indicator. This index synthesizes the four dimensions of "Scale, Quality, Innovation and Contribution", covering the complete chain of talent from cultivation and agglomeration to output:
人才竞争力难以用单一指标刻画。本指数综合"规模、质量、创新、贡献"四个维度,覆盖人才从培养、集聚到产出的完整链条:
- 规模:人才队伍的"家底"——高等教育人口(存量)与研发人员总数(活跃科研力量),衡量人才资源的绝对体量。
- 质量:人才队伍的"含金量"——顶尖科学家/高被引学者(头部科研精英)与研发人员密度(人均科研强度),衡量人才的高度与密集度。
- 创新:人才转化为生产力的"产出"——研发投入(创新资源强度)与发明专利(PCT 国际专利)产出,衡量人才驱动的创新成果。
- 贡献(CPPPS 特色):人才培养输出与"人才红利"——STEM 毕业生规模(每年新增工程师供给)与高校在校生规模(人才后备军),衡量其为全球产业链持续输送高素质人才的贡献能力。
By employing all four dimensions together, it avoids "scale-centrism" (where populous countries necessarily rank first) and also avoids "per-capita-centrism" (where small countries necessarily rank first), and further restores, through the "Contribution" dimension, the "engineer dividend" of populous countries—a competitiveness ignored by most international rankings.
四维并举,既避免"唯规模论"(人口大国必然居前),也避免"唯人均论"(小国必然居前),更通过"贡献"维度还原人口大国"工程师红利"这一被多数国际榜单忽视的竞争力。
二、数学模型
Each indicator is first range-standardized to [0,1]; large-span scale indicators (higher-education population, R&D personnel, R&D expenditure, patents, STEM graduates, enrolled students, highly cited scholars) first take the logarithm and are then standardized to avoid monopoly by head economies; R&D personnel density is a ratio indicator and is directly linearly standardized. After weighted summation, the result is converted into a percentage score:
各指标先做极差标准化至 [0,1],规模类大跨度指标(高等教育人口、研发人员、研发经费、专利、STEM 毕业生、在校生、高被引学者)先取对数再标准化,避免头部经济体垄断;研发人员密度为比率指标,直接线性标准化。加权求和后换算为百分制:
x′ = (x − x_min) / (x_max − x_min),规模类先取 log₁₀(1+x)
指数 = 100 × ( 0.10·高等教育人口′ + 0.10·研发人员′ + 0.18·高被引学者′ + 0.12·研发密度′ + 0.15·研发经费′ + 0.15·专利′ + 0.12·STEM毕业生′ + 0.08·在校生′ )
Each of the four sub-scores (Scale/Quality/Innovation/Contribution) is 100 times the weighted sum of its constituent indicators, for ease of horizontal comparison.
四项分项得分(规模/质量/创新/贡献)各自为所含指标加权和的 100 倍,便于横向比较。
三、指标与权重依据
| 维度 | 指标 | 方向 | 权重 | 处理 | 依据 |
| 规模 0.20 | 高等教育人口 | 正向 | 0.10 | 对数 | 人才存量 |
| 研发人员总数 | 正向 | 0.10 | 对数 | 活跃科研力量 |
| 质量 0.30 | 高被引学者 | 正向 | 0.18 | 对数 | 头部科研精英 |
| 研发人员密度 | 正向 | 0.12 | 线性 | 人均科研强度 |
| 创新 0.30 | 研发经费 | 正向 | 0.15 | 对数 | 创新资源投入 |
| PCT 专利 | 正向 | 0.15 | 对数 | 创新成果产出 |
| 贡献 0.20 | STEM 毕业生 | 正向 | 0.12 | 对数 | 人才培养输出 |
| 高校在校生 | 正向 | 0.08 | 对数 | 人才后备军/红利 |
Weight-design logic: Quality and Innovation each account for 30%, highlighting that the essence of "talent competitiveness" is "a high level of research and innovation capability" rather than mere population size; Scale accounts for 20%, retaining the basic stock of talent; Contribution accounts for 20% and is a distinctive CPPPS dimension that specifically supplements the "talent-cultivation output and engineer dividend" perspective generally missing from international rankings.
权重设计逻辑:质量与创新各占 30%,突出"人才竞争力"的本质是"高水平的科研与创新能力",而非单纯的人口规模;规模占 20%,保留人才家底的基本盘;贡献占 20%,为 CPPPS 特色维度,专门补足国际榜单普遍缺失的"人才培养输出与工程师红利"视角。
四、数据来源与局限性
The higher-education population, R&D personnel, R&D expenditure and patents are approximate values from the public data of the UNESCO Institute for Statistics, the World Intellectual Property Organization (WIPO) and national statistical departments; highly cited scholars are approximate values from Clarivate's annual "Highly Cited Researchers" list; STEM graduates and enrolled university students are approximate values from public statistics of national ministries of education. All of the above data are publicly known approximate values, marked "subject to official figures". This model does not include hard-to-quantify soft factors such as talent mobility (immigration attractiveness), institutional environment and salary competitiveness, and the approximate values contain errors; the ranking is provided for research and reference only.
高等教育人口、研发人员、研发经费、专利等为联合国教科文组织(UNESCO)统计所、世界知识产权组织(WIPO)、各国统计部门公开数据的近似值;高被引学者为科睿唯安(Clarivate)"高被引科学家"年度榜单的近似值;STEM 毕业生与高校在校生为各国教育部公开统计的近似值。上述数据均为公开常识近似值,标注"以官方为准"。本模型不包含人才流动(移民吸引力)、制度环境、薪酬竞争力等难以量化的软性因素,且近似值存在误差,排名仅供研究与参考。
五、参考文献
- UNESCO Institute for Statistics (UIS):研究与开发(R&D)统计数据。
- 世界知识产权组织(WIPO):PCT 国际专利申请年度统计。
- 科睿唯安(Clarivate):高被引科学家(Highly Cited Researchers)年度榜单。
- OECD:《Main Science and Technology Indicators(MSTI)》。
- 各国统计部门:高等教育、在校生、毕业生年度统计。
- CPPPS《自有评价算法规范》:规模 + 质量 + 创新 + 贡献 四维框架。