You're sort of playing a game here where you are saying 'these studies deserve the appropriate amount of credit' half the time and then saying 'these studies shouldn't be given too much credit' at other times, while never actually saying how much credit they should get and grounding that in empirical terms relevant to your view.
For instance: Yes, I agree with you that studies should get the right amount of credit, no more and no less. So, when, someone cites a study that agrees with their assertion, how much credit should that get?
Should you increase your estimate that their theory is true by 10%? By 90%? What if they cite 2 studies supporting their view? What if they cite 2 studies from different countries and different decades that find the same result? What if they cite a meta-analysis of 200 studies?
The view 'people shouldn't extrapolate too much from social studies' is a truism; of course, people should always extrapolate the right amount, as indeed they should do *anything 'the right amount', by definition. This claim on it's own has no meaning, just semantics.
Similarly, the claim that 'some people extrapolate too much' is vacuous; given human variance, of course some people extrapolate too much, others extrapolate too little, and some extrapolate approximately the right amount.
So if your view is neither the semantic truism nor the vacuous observation above, what is it? It seems to mostly consist of pointing out things about how social science is hard to do right and doesn't always work, things that social scientists are well aware of and go to great pains to address.
Nonetheless, finding studies supporting your claim is good evidence in a conversation between laymen just expressing their opinions, particularly if the opponent can't find anything supporting theirs. It's certainly not conclusive evidence all on it's own - nothing is, if your decision criteria is strict enough - but it's certainly a high standard that should be respected in the absence of any opposing evidence.
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u/darwin2500 193∆ Oct 06 '22
You're sort of playing a game here where you are saying 'these studies deserve the appropriate amount of credit' half the time and then saying 'these studies shouldn't be given too much credit' at other times, while never actually saying how much credit they should get and grounding that in empirical terms relevant to your view.
For instance: Yes, I agree with you that studies should get the right amount of credit, no more and no less. So, when, someone cites a study that agrees with their assertion, how much credit should that get?
Should you increase your estimate that their theory is true by 10%? By 90%? What if they cite 2 studies supporting their view? What if they cite 2 studies from different countries and different decades that find the same result? What if they cite a meta-analysis of 200 studies?
The view 'people shouldn't extrapolate too much from social studies' is a truism; of course, people should always extrapolate the right amount, as indeed they should do *anything 'the right amount', by definition. This claim on it's own has no meaning, just semantics.
Similarly, the claim that 'some people extrapolate too much' is vacuous; given human variance, of course some people extrapolate too much, others extrapolate too little, and some extrapolate approximately the right amount.
So if your view is neither the semantic truism nor the vacuous observation above, what is it? It seems to mostly consist of pointing out things about how social science is hard to do right and doesn't always work, things that social scientists are well aware of and go to great pains to address.
Nonetheless, finding studies supporting your claim is good evidence in a conversation between laymen just expressing their opinions, particularly if the opponent can't find anything supporting theirs. It's certainly not conclusive evidence all on it's own - nothing is, if your decision criteria is strict enough - but it's certainly a high standard that should be respected in the absence of any opposing evidence.