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A supervised machine learning approach to trace doctorate recipients' employment trajectories
2019
Quantitative Science Studies
Only scarce information is available on doctorate recipients' career outcomes (BuWiN, 2013). With the current information base, graduate students cannot make an informed decision whether to start a doctorate or not (Benderly, 2018; Blank, 2017). However, administrative labour market data, which could provide the necessary information, is incomplete in this respect. In this paper, we describe the record linkage of two datasets to close this information gap: data on doctorate recipients collected
doi:10.1162/qss_a_00001
fatcat:ocsd3566prhz7mln74nk3pv4cq