Scientific collaboration in data‐intensive research networks: PhD fellows' expectations and early experiences
基于对四个风能培训网络中23位博士研究员的访谈，研究了他们对科学合作的期望与早期经验，发现期望虽高但实际经验受组织、内容、过程和个人层面条件影响，合作可能带来不平衡风险。
Abstract Collaboration has become important at all stages of research careers. In data‐intensive research fields such as wind energy, many PhD fellows are socialized to such collaboration in networks that train a cohort of PhD fellows. Based on interviews with 23 PhD fellows in four wind‐energy training networks, we investigate their expectations and early experiences regarding scientific collaboration. We find that expectations for collaboration are high, but also that the PhD fellows' expectations and early experiences differ. Their experiences are influenced by conditions that make collaboration a balancing act at the organizational, content, process, and personal levels. At the organizational level, learning scientific collaboration involves negotiating interdependencies that are created at the network‐proposal stage and presume collaborations about data among the PhD fellows in the network. At the content and process levels, the PhD fellows are dependent on collaboration to collect, analyze, share, validate, and compare data. At the personal level, devising a doable dissertation involves that the individual PhD fellow succeeds in realizing these collaborations. While the studied wind‐energy research networks nurture a collaborative environment, the collaboration they presume and the rewards it promises come with the risk of imposing imbalanced collaborations on some PhD fellows.