Persistence Paradox in Dynamic Science: Evidence from the Deep Learning Revolution
The study investigated whether persistence is always good in science by looking at scientists during the deep learning revolution starting in 2012. It found that while sticking to old research methods increased output, it hurt scientific impact after 2013. This 'rigidity penalty' suggests that during rapid technological shifts, clinging too tightly to past expertise can become a liability.