The present study focuses on persistence in research productivity over the course of an individual's entire scientific career. We track 'late-career' scientists - scientists with at least 25 years of publishing experience (N=320,564) - in 16 STEMM (science, technology, engineering, mathematics, and medicine) and social science disciplines from 38 OECD countries for up to five decades. Our OECD sample includes 79.42% of late-career scientists globally. We examine the details of their mobility patterns as early-career, mid-career, and late-career scientists between decile-based productivity classes, from the bottom 10% to top 10% of the productivity distribution. Methodologically, we turn a large-scale bibliometric dataset (Scopus raw data) into a comprehensive, longitudinal data source for research on careers in science. The global science system is highly immobile: half of global top performers continue their careers as top performers and one-third of global bottom performers as bottom performers. Jumpers-Up and Droppers-Down are extremely rare in science. The chances of moving radically up or down in productivity classes are marginal (1% or less). Our regression analyses show that productivity classes are highly path dependent: there is a single most important predictor of being a top performer, which is being a top performer at an earlier career stage.

翻译：本研究聚焦于科学家整个学术生涯中研究生产力的持续性。我们追踪了来自38个OECD国家、在STEMM（科学、技术、工程、数学、医学）及社会科学16个学科领域拥有至少25年发表经验的"职业生涯晚期"科学家（N=320,564），追踪跨度长达五十年。该OECD样本覆盖全球79.42%的职业生涯晚期科学家。我们详细分析了这些科学家在职业生涯早期、中期和晚期阶段，在不同十分位生产力等级（从生产力分布最低10%到最高10%）之间的流动模式。在方法论上，我们将大规模文献计量数据集（Scopus原始数据）转化为适用于科学研究职业生涯纵向研究的综合数据源。全球科学系统呈现出高度固化特征：半数全球顶尖科学家持续保持顶尖水平，三分之一全球底层科学家持续处于底层。在科学界，"跃升者"和"跌落者"极为罕见。生产力等级发生剧烈升降的可能性微乎其微（1%及以下）。回归分析表明，生产力等级具有高度路径依赖性：预测科学家成为顶尖表现者的唯一最重要指标，是其较早职业生涯阶段是否已为顶尖表现者。