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How to explore your scientific values and develop a vision for your field
As a new professor, I was caught off guard by one part of the job: my role as an evaluator.
My work, for example, straddles the border between neuroscience and artificial intelligence, so I frequently need to consider how much I value neuro-AI proposals that focus on biological fidelity versus those that draw more from computer science topics. The “lumpers versus splitters” debate, for example—whether one should try to unify different examples by using only broad categories or divide them into ever smaller ones—applies across research topics at many levels, ranging from cell types to psychological capacities. Developing a sense for when exploring a large and diverse dataset can provide insight versus when more targeted designs are needed also makes these decisions easier.
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