Second, sociology and anthropology are among the least empirical of academic disciplines. What reason would you have to involve them?
Third, many studies are of the type "my theory predicts X and my experiment shows p < 0.05". That's almost wrong by definition. Bayesian theory explains why.
Fourth, many studies have conclusions/claims that cannot be inferred from the actual finding.
> When nearly every policy can be backed by "some papers published in <some journal>", stuff like this becomes important.
It is important, but as long as academia is a "turn out papers for tenure" industry, it won't be fixed. Don't take the conclusions of a paper for true. They're meant for other academics.
And i think that R and python being popular in the academic fields belies the fact that no one wants to talk to statisticians about their data. It's a lot easier to massage inputs to a machine than a human.
I was under the impression we were talking about reproducibility in this thread; therefore my point about policy being influenced by something you suggest is "meant for other academics"
When nearly every policy can be backed by "some papers published in <some journal>", stuff like this becomes important. For a recent example, the US White house is engaging in a 5 year study to determine if releasing sulfur dioxide into the stratosphere would accomplish enough "cooling" to offset the "climate crisis". the "climate crisis" is something that exists in computer models, few of the models agree, and if they do, it behooves us to look at when they started agreeing and find out why that change happened.
a more personal example: I can't reproduce getting CaCO out of seawater, yet.