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>When you think about it, it's insane that metascience isn't studied more. We're going to question every little detail about the universe, but we're just going

>When you think about it, it's insane that metascience isn't studied more. We're going to question every little detail about the universe, but we're just going to take on faith that peer-review and publication in journals is an effective method for weeding out "bad" science? In a sense we do have this: engineering and finance. Engineering turns good hard science into new tools, machines and weapons, and Finance turns good (predictive) soft science into new ways to make money.

hpoe 5y ago
I think this is an important point, ultimately good science will produce, verifiable, testable, actionable results. Until you have that no matter how much math you use, how many lab coats you've got, no matter how many journals you publish in you're just sitting there playing with strings.
- jrochkind1 5y ago
  Telling when this has happened can be less trivial than you would assume though. People (scientists even) were sure that phrenology produced verifiable, testable, actionable results for a generation or two. In the long run it usually comes out, but the run can be longer than you think, and you may not be where you think in it with regard to any particular current theory. I wonder what things we know all "know" are proven by science will be dismissed by later generations. (I personally guess a lot of genetics-related stuff will be). (Note that something doesn't need to be verifiable, reliable, or true to be "actionable". You can act on anything...)
jhap 5y ago
> In a sense we do have this: engineering and finance. Engineering turns good hard science into new tools, machines and weapons, and Finance turns good (predictive) soft science into new ways to make money. I think this is a common critique, but I also think it is missing the point. What if the question of interest isn't so easily verifiable like in Engineering? Do we just throw up our hands and give up on those questions? [The alternative to good social science is not no social science, it’s bad social science](https://statmodeling.stat.columbia.edu/2021/03/12/the-social-sciences-are-useless-so-why-do-we-study-them-heres-a-good-reason/ https://statmodeling.stat.columbia.edu/2021/03/12/the-social...). Finance is also a bit tautological in this regard. It seems that often prediction models are impossible to disprove (e.g., our arbitrage method doesn't work anymore, the market updated). Yes good for putting skin in the game, but doesn't seem like it does much to advance our long-term understanding of humans.
- logicchains 5y ago
  >What if the question of interest isn't so easily verifiable like in Engineering? Do we just throw up our hands and give up on those questions? [The alternative to good social science is not no social science, it’s bad social science](https://statmodeling.stat.columbia.edu/2021/03/12/the-social https://statmodeling.stat.columbia.edu/2021/03/12/the-social...). Some things may well be complex enough that it's simply impossible, with the amount of resources available to the average university, to conduct a thorough enough study on a representative enough sample that accounts for enough confounding factors to make a statistically sound prediction that generalises. If this were the case for a significant proportion of the subjects of study of a particular field, then it might well be better to "give up" and admit we don't and cannot know, otherwise we're essentially creating a factory for bad science (as the available resources relative to the scope of the problem aren't sufficient to create good science, and there's no negative feedback to stop the bad science).
- ImprobableTruth 5y ago
  If there's "good social science" that can't be used to make predictions, what differentiates it from bad social science?
  - akiselev 5y ago
    Its utility [1]. The social sciences study a lot of things that people in group A intuitively understand that group B can be completely ignorant of - say, for example, how to navigate a complex social structure like office politics in a modern workplace. Making any sort of predictions about intangible outcomes where the Hawthorne effect is in full effect is pretty much impossible since group A will respond to the new knowledge gained by group B, in effect changing the system we're trying to predict. Individual's psychologies respond to the changing psychology of the group in nondeterministic ways (at least, relative to our ability to collect data on input variables and internal state). We can bikeshed what makes something a "science" till the cows come home but the philosophy of science and epistemology were not settled with Bacon and Popper - the end goal has always understanding in the broadest sense. Those studies have value as long as they help someone make sense of and adapt to the social systems they're in. It does mean though that those studies should be approached with extreme caution (see the decades wasted on string theory) and anyone basing their research off past results needs to carefully validate their assumptions. [1] I think in this case "predictive" as a scientific term of art is too restricting. Social sciences often deal with very personal interactions that appear nondeterministic at the scale of a society but are relatively predictable when applied to a stereotypical office or school setting.

hpoe 5y ago

I think this is an important point, ultimately good science will produce, verifiable, testable, actionable results. Until you have that no matter how much math you use, how many lab coats you've got, no matter how many journals you publish in you're just sitting there playing with strings.

jrochkind1 5y ago
Telling when this has happened can be less trivial than you would assume though. People (scientists even) were sure that phrenology produced verifiable, testable, actionable results for a generation or two. In the long run it usually comes out, but the run can be longer than you think, and you may not be where you think in it with regard to any particular current theory. I wonder what things we know all "know" are proven by science will be dismissed by later generations. (I personally guess a lot of genetics-related stuff will be). (Note that something doesn't need to be verifiable, reliable, or true to be "actionable". You can act on anything...)

jhap 5y ago

> In a sense we do have this: engineering and finance. Engineering turns good hard science into new tools, machines and weapons, and Finance turns good (predictive) soft science into new ways to make money. I think this is a common critique, but I also think it is missing the point. What if the question of interest isn't so easily verifiable like in Engineering? Do we just throw up our hands and give up on those questions? [The alternative to good social science is not no social science, it’s bad social science](https://statmodeling.stat.columbia.edu/2021/03/12/the-social-sciences-are-useless-so-why-do-we-study-them-heres-a-good-reason/ https://statmodeling.stat.columbia.edu/2021/03/12/the-social...). Finance is also a bit tautological in this regard. It seems that often prediction models are impossible to disprove (e.g., our arbitrage method doesn't work anymore, the market updated). Yes good for putting skin in the game, but doesn't seem like it does much to advance our long-term understanding of humans.

logicchains 5y ago
>What if the question of interest isn't so easily verifiable like in Engineering? Do we just throw up our hands and give up on those questions? [The alternative to good social science is not no social science, it’s bad social science](https://statmodeling.stat.columbia.edu/2021/03/12/the-social https://statmodeling.stat.columbia.edu/2021/03/12/the-social...). Some things may well be complex enough that it's simply impossible, with the amount of resources available to the average university, to conduct a thorough enough study on a representative enough sample that accounts for enough confounding factors to make a statistically sound prediction that generalises. If this were the case for a significant proportion of the subjects of study of a particular field, then it might well be better to "give up" and admit we don't and cannot know, otherwise we're essentially creating a factory for bad science (as the available resources relative to the scope of the problem aren't sufficient to create good science, and there's no negative feedback to stop the bad science).
ImprobableTruth 5y ago
If there's "good social science" that can't be used to make predictions, what differentiates it from bad social science?
- akiselev 5y ago
  Its utility [1]. The social sciences study a lot of things that people in group A intuitively understand that group B can be completely ignorant of - say, for example, how to navigate a complex social structure like office politics in a modern workplace. Making any sort of predictions about intangible outcomes where the Hawthorne effect is in full effect is pretty much impossible since group A will respond to the new knowledge gained by group B, in effect changing the system we're trying to predict. Individual's psychologies respond to the changing psychology of the group in nondeterministic ways (at least, relative to our ability to collect data on input variables and internal state). We can bikeshed what makes something a "science" till the cows come home but the philosophy of science and epistemology were not settled with Bacon and Popper - the end goal has always understanding in the broadest sense. Those studies have value as long as they help someone make sense of and adapt to the social systems they're in. It does mean though that those studies should be approached with extreme caution (see the decades wasted on string theory) and anyone basing their research off past results needs to carefully validate their assumptions. [1] I think in this case "predictive" as a scientific term of art is too restricting. Social sciences often deal with very personal interactions that appear nondeterministic at the scale of a society but are relatively predictable when applied to a stereotypical office or school setting.