I’m a month late to the party, but wanted to chime in anyway.
RCTs (and p-values) don’t seem to be popular in physics or geology. I’m curious why Pearl doesn’t find this worth noting. I’ve mentioned before that people seem to care about statistical significance mainly where powerful interest groups might benefit from false conclusions.
Yes, there certainly seems to be a correlation. But I think in this case this can be mostly understood by considering the subject matter as a confounding variable—powerful interest groups mostly care about research that can influence policy-making, which are usually the Social Sciences. And it just so happens that designing a replicable study that measures exactly what you are looking for is a lot easier in physics/geology/astronomy than it is in social science (who knew, the brain is complicated). So Social Science gets stuck with proxies and replication crises and wiggle room for foul play. It is a relatively sensible reaction then to demand some amount of standardization (standard statistical tools, standard experimental methods etc.) within the field. Or, put more bluntly, if you cannot have good faith in the truth of the conclusions of your peers’ research (mostly just because the subject is more difficult than any training prepared them for, not because your peers are evil) you need to artificially create some common ground to start repairing that sweet exponential growth curve.
I’m a month late to the party, but wanted to chime in anyway.
Yes, there certainly seems to be a correlation. But I think in this case this can be mostly understood by considering the subject matter as a confounding variable—powerful interest groups mostly care about research that can influence policy-making, which are usually the Social Sciences. And it just so happens that designing a replicable study that measures exactly what you are looking for is a lot easier in physics/geology/astronomy than it is in social science (who knew, the brain is complicated). So Social Science gets stuck with proxies and replication crises and wiggle room for foul play. It is a relatively sensible reaction then to demand some amount of standardization (standard statistical tools, standard experimental methods etc.) within the field. Or, put more bluntly, if you cannot have good faith in the truth of the conclusions of your peers’ research (mostly just because the subject is more difficult than any training prepared them for, not because your peers are evil) you need to artificially create some common ground to start repairing that sweet exponential growth curve.