You understand that the “hard sciences” are also affected by this crisis, correct? “Soft science” is a borderline meaningless term that stigmatizes entire fields of science to the sole benefit of anti-intellectuals.
Even when we take into consideration that the problem is currently worse in sciences like psychology, economics, sociology, etc.: “these results support the scientific status of the social sciences against claims that they are completely subjective, by showing that, when they adopt a scientific approach to discovery, they differ from the natural sciences only by a matter of degree.” Social sciences are science.
You don’t belong to “the hard sciences crowd”; you belong to a Sheldon Cooper-esque stereotype who devalues work you don’t understand.
No, the difference in the replication crisis between the soft “sciences” and the hard is enormous. The soft are basically producing results equal to making coin tosses.
You have clearly never actually done “hard sciences” research in any meaningful way if this is your take. And computer science does not count as a science at all, it is more like engineering. Mathematics is a “hard science” that can be implemented through computer science, and physics is a “hard science” that can be implemented through electrical engineering (and as a subset computer engineering).
But even then mathematics is closer to philosophy and logic than any of the physical sciences. The physical sciences like physics, chem, bio are very different due to their experimental nature, and how sensitive they can be to specific conditions of the experiments. And the more complex the system being studied is, the harder it is to control variability which is why the social sciences like psychology and economics are working on incredibility difficult problems in systems we do not currently fully understand, and are more vulnerable to difficult reproducing and replicating the conclusions.
This is in contrast to computer science where we fully understand the system because humans have built it, and it is a machine built on the principles discovered by physicists and implemented by electrical engineers to run calculations that are created by mathematicians.
I don’t consider Psychology to be a scientific discipline - I belong to the hard sciences crowd.
My wife is a psychologist.
You understand that the “hard sciences” are also affected by this crisis, correct? “Soft science” is a borderline meaningless term that stigmatizes entire fields of science to the sole benefit of anti-intellectuals.
Even when we take into consideration that the problem is currently worse in sciences like psychology, economics, sociology, etc.: “these results support the scientific status of the social sciences against claims that they are completely subjective, by showing that, when they adopt a scientific approach to discovery, they differ from the natural sciences only by a matter of degree.” Social sciences are science.
You don’t belong to “the hard sciences crowd”; you belong to a Sheldon Cooper-esque stereotype who devalues work you don’t understand.
No, the difference in the replication crisis between the soft “sciences” and the hard is enormous. The soft are basically producing results equal to making coin tosses.
You have clearly never actually done “hard sciences” research in any meaningful way if this is your take. And computer science does not count as a science at all, it is more like engineering. Mathematics is a “hard science” that can be implemented through computer science, and physics is a “hard science” that can be implemented through electrical engineering (and as a subset computer engineering).
But even then mathematics is closer to philosophy and logic than any of the physical sciences. The physical sciences like physics, chem, bio are very different due to their experimental nature, and how sensitive they can be to specific conditions of the experiments. And the more complex the system being studied is, the harder it is to control variability which is why the social sciences like psychology and economics are working on incredibility difficult problems in systems we do not currently fully understand, and are more vulnerable to difficult reproducing and replicating the conclusions.
This is in contrast to computer science where we fully understand the system because humans have built it, and it is a machine built on the principles discovered by physicists and implemented by electrical engineers to run calculations that are created by mathematicians.