[brofallon]

Here's a good example, take a look at the recently published articles in PloS Computational Biology: https://journals.plos.org/ploscompbiol/ Just scanning through them... there aren't really any that are a simple "we made a single hypothesis, performed a significance test, and because p < 0.05 we attempted to publish it". In my experience that's just not the usual way science is actually performed (but my experience is very limited to certain branches of biology). I don't mean to say that p-values aren't used at all, just that their application seems to be limited and used mostly to bolster very specific sub-arguments buried in a larger story. I guess the story is that the unit of work that a particular journal article represents is often the union of many statistical tests/ hypotheses / models / simulations / etc that together form a possibly-compelling story about how something works. Not really sure if that's better or worse from a statistical sanity perspective...