How scientists navigate between the need to capitalize on their prior knowledge by specializing, and the urge to adapt to evolving research opportunities? Drawing from diverse perspectives on adaptation, in particular from institutional change and cultural evolution, this paper proposes a Bayesian model of the evolution of scientists' research portfolios in response to transformations in their field. The model relies on scientific abstracts and authorship data to evaluate the influence of intellectual, social, and institutional resources on scientists' trajectories within a cohort of $2\,195$ high-energy physicists between 2000 and 2019. The reallocation of research efforts in response to the incentives to adapt is shown to be mainly structured by learning costs, thus maximizing the utility of the scientific capital disseminated among scientists. Two dimensions of social capital, namely ``diversity'' and ``power'', have opposite effects on the magnitude of change in scientists' research interests: while ``diversity'' disrupts and expands research interests, ``power'' stabilizes physicists' research agendas -- as does institutional stability. Social capital plays a more crucial role in shifts between cognitively distant research areas.

翻译：科学家如何在专业化以利用既有知识，与适应不断变化的研究机会之间进行权衡？本文借鉴制度变迁与文化演化中关于适应的多元视角，提出一个贝叶斯模型，用以解释科学家研究组合随领域变革而演化的过程。该模型利用科学摘要和作者署名数据，评估智力、社会与制度资源对2000年至2019年间2195名高能物理学家群组中职业轨迹的影响。研究表明，为响应适应激励而进行的研究努力再分配，主要受学习成本结构制约，从而最大化散布于科学家群体中的科学资本的效用。社会资本的两个维度——即“多样性”与“权力”——对科学家研究兴趣变化的程度具有相反效应：“多样性”颠覆并扩展研究兴趣，而“权力”则如同制度稳定性一样，使物理学家的研究议程趋于稳定。社会资本在认知距离较远的研究领域之间的转换中发挥更为关键的作用。