As usual in articles of this kind, the article's content contradicts its title. The study doesn't show that "loneliness raises alcohol tolerance," it shows a correlation between two measured traits.
In studies like this, two effects are measured and found to be correlated. For lack of evidence, an assertion about cause can only be conjecture.
They went further than showing a correlation between two traits. They directly manipulated the pre-alcohol state (alone, or with other crayfish), and measured whether that change outcomes in behavior and neural activity. Presumably they kept everything else the same[0], randomly assigned crayfish to isolation and social environments, and placed them in the same alcohol environment.
Just because the chain of causation is fuzzy doesn't mean A doesn't cause B. Maybe social isolation and alcohol response are trivially connected to something else like movement rate and other variables. That doesn't mean you can't make causal inferences.
[0] I don't know much about crayfish experiments - maybe there's some latent cause like isolated crayfish are handled differently and that causes changes in alcohol-induced behavior and neural activity. I would want to know whether the crayfish showed similar or divergent behavior in an alcohol-free environment. It's possible that alcohol has identical 'gain' on behavior and neural activity, but that still indicates an effect, technically. And nothing is ever 100 percent the same across conditions (this is the fundamental problem with causal analysis) but that's true across every discipline.
If there's an objection to the title, it's that loneliness and social isolation are not the same thing.
> Just because the chain of causation isn't clear doesn't mean A doesn't cause B.
Yes, that's true, but science isn't based on what can't be excluded, it's based on what the evidence supports. If this were not true, any claim that couldn't be disproven would ipso facto become true.
Some have said it this way -- to a pseudoscientist, things are assumed to be true until they're disproven. To a scientist, things are assumed to be false until evidence supports them (the null hypothesis).
> That doesn't mean you can't make causal inferences.
Yes, you can do that, but it's not science. In science, it's not about inference, it's about evidence.
Before publication, any sort of speculation is the norm, it's part of the creative process. But when the science gets published and the title contradicts the article, something went wrong.
> As I understand it, this article is about a controlled experiment. In which case there is no confounding and therefore correlation implies causation.
Without a testable, falsifiable theory -- an explanation, correlations don't --
can't -- imply a cause-effect relationship. Not in a scientific sense, anyway. If I say that puddles cause rain, people will laugh. But if I say I performed a controlled experiment in a very large building like the VAB at Cape Canaveral in which I produce puddles and the puddles really do cause the subsequent rain, but I omit the details (or simply don't understand my own result), I get the last laugh. It's true, but it's not science unless there's a theoretical dimension, not just a description. It's not science unless I understand my result.
Readit News
In studies like this, two effects are measured and found to be correlated. For lack of evidence, an assertion about cause can only be conjecture.
They went further than showing a correlation between two traits. They directly manipulated the pre-alcohol state (alone, or with other crayfish), and measured whether that change outcomes in behavior and neural activity. Presumably they kept everything else the same[0], randomly assigned crayfish to isolation and social environments, and placed them in the same alcohol environment.
Just because the chain of causation is fuzzy doesn't mean A doesn't cause B. Maybe social isolation and alcohol response are trivially connected to something else like movement rate and other variables. That doesn't mean you can't make causal inferences.
[0] I don't know much about crayfish experiments - maybe there's some latent cause like isolated crayfish are handled differently and that causes changes in alcohol-induced behavior and neural activity. I would want to know whether the crayfish showed similar or divergent behavior in an alcohol-free environment. It's possible that alcohol has identical 'gain' on behavior and neural activity, but that still indicates an effect, technically. And nothing is ever 100 percent the same across conditions (this is the fundamental problem with causal analysis) but that's true across every discipline.
If there's an objection to the title, it's that loneliness and social isolation are not the same thing.
Yes, that's true, but science isn't based on what can't be excluded, it's based on what the evidence supports. If this were not true, any claim that couldn't be disproven would ipso facto become true.
Some have said it this way -- to a pseudoscientist, things are assumed to be true until they're disproven. To a scientist, things are assumed to be false until evidence supports them (the null hypothesis).
> That doesn't mean you can't make causal inferences.
Yes, you can do that, but it's not science. In science, it's not about inference, it's about evidence.
Before publication, any sort of speculation is the norm, it's part of the creative process. But when the science gets published and the title contradicts the article, something went wrong.
Without a testable, falsifiable theory -- an explanation, correlations don't -- can't -- imply a cause-effect relationship. Not in a scientific sense, anyway. If I say that puddles cause rain, people will laugh. But if I say I performed a controlled experiment in a very large building like the VAB at Cape Canaveral in which I produce puddles and the puddles really do cause the subsequent rain, but I omit the details (or simply don't understand my own result), I get the last laugh. It's true, but it's not science unless there's a theoretical dimension, not just a description. It's not science unless I understand my result.