Do you really have to be doing causal inference to be “doing science”? Surely much scientific progress can be made by building models that predict phenomena 10% better than current state of the art?
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I’m happy to blur things usually but here I think the distinctions matter.
Why? This is a classic case of different degrees. There's a continuum between classifying a galaxy and doing Nobel prizewinning work. In fact, the Zooites show it, rather nicely, with many, many different levels of engagement & understanding.
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The different degrees do matter, of course. But there are hundreds of them, and few (if any) people encompass all of them. I've known Nobel prizewinning scientists who understand little of the mathematical models they're testing; I've known others who've never collected any data
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Murray Gell-Mann knows it all ;) I think about engagement a lot (as do you!), and worry about getting people over a line: from helping to doing.
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