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, 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.
 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.
In science, addressing causation requires a testable, falsifiable theory. Without a theory -- an explanation -- we can only describe what took place. The authors of the paper freely acknowledge that they don't understand their result in a theoretical sense. But the article's title -- "Drunken crayfish show that loneliness raises alcohol tolerance" -- is perfect nonsense and an embarrassment for a half-dozen reasons.
By the way, the moderators edited the submission's title since I posted this morning. Unfortunately, it seems that New Scientist's editorial standards aren't as high as those at HN.
The experiment that was done is evidence in favor of this theory. It is not conclusive, because it is only one experiment, but it does suggest a causal relationship, and not just a correlation.
That is not a theory, it's a statement about an observation -- it describes, it doesn't explain. Theories explain observations.
> A theory does not need to contain an explanation to be a valid scientific theory.
A scientific theory is an explanation. That's how it's defined. A description cannot be a theory because it doesn't say why the result took place, only that it did.
If I say, “The night sky is filled with tiny points of light,” I've offered a description. Another observer might contradict my description, for example by emerging from his cave on an overcast night and not seeing any points of light, but that contradicting observation can itself be contradicted on the next clear night, without any chance for resolution (so a contradiction is not a falsification). Apart from being shallow, inconclusive and trivial, this process is not science.
If instead I say, “Those points of light are distant thermonuclear furnaces like our sun,” I've offered an explanation, one that makes predictions about phenomena not yet observed and that's falsifiable by empirical test. On the basis of this explanation we might build a small-scale star (a fusion reactor) to see if our experiment shows any similarity to the spectra and behavior of stars. This deep explanation represents a theoretical claim that's linked to other areas of human knowledge, predicts phenomena not yet observed and is conclusively falsifiable by comparison with reality (our fusion reactor might fail to imitate the stars). It's science.
Quote: "A scientific theory is an explanation of some aspect of the natural world that can, in accordance with the scientific method, be repeatedly tested, using a predefined protocol of observations and experiments. Established scientific theories have withstood rigorous scrutiny and are a comprehensive form of scientific knowledge." (emphasis added)
You are conflating two different definitions of explain. It is possible to explain what is happening without explaining how. It is possible to know that A causes B without knowing why (This is purpose of the scientific method). If it were actually impossible to have evidence that something is true without knowing why it is true, than it would be impossible to have evidence of anything at all. You could invalidate any knowledge by just asking "why", because there is always another "why". To give an example, we know that mass causes gravitational attraction even though we don't fully understand the mechanism that causes it.
That's a description -- an account of what was observed. By definition, an explanation must add something to a description.
"The night sky is filled with points of light." -- a description.
"Those points are distant thermonuclear furnaces, powered by atomic fusion." -- an explanation.
"Similar bird species have differently shaped beaks." -- a description.
"Bird species evolve traits that confer a survival advantage in their distinct environments." -- an explanation.
> It is possible to know that A causes B without knowing why ..."
One cannot claim to know that A causes B without also knowing why, otherwise puddles cause rain. Science is not merely about knowing -- it's about knowing that we know. An observation asserts a fact without context. A scientific theory offers more than mere description, and its standing rests solely on the fact that it has resisted falsification.
> To give an example, we know that mass causes gravitational attraction even though we don't fully understand the mechanism that causes it.
Yes, but that's not a scientific theory, it's a description -- mass causes gravitational attraction, or equivalently, gravitational attraction causes mass (my point is the claim is wrong but without a theory, we can't know that it's wrong). As long as there's no testable theory, the two descriptions are equivalent.
The Greeks believed our sight resulted from our eyes shooting beams out into the environment. Until we had a testable theory, no one could reasonably dispute that idea.
A theory is not a description -- it offers more than an account of observed facts. The water rises across the beach over a period of hours: a description. The sun and moon apply tidal forces -- a spatial differential in gravitational force -- to the water, causing it to periodically rise and fall: an explanation, one that can be tested and potentially falsified.
The experimenters changed the environment and noted a change in behavior. This isn't enough to be able to say which aspect of the change induced the behavioral change, in particular because the study isn't testing a theory, or a cause. It's testing an effect -- the outcome of an environmental change.
This is something that Richard P. Feynman described in some detail in his now-famous talk entitled "Cargo Cult Science." He describes a number of social science studies that went off the rails because the experimenters were too quick to draw conclusions based on experiments the investigators didn't really understand. As a counterpoint he describes one outstanding experiment in which the experimenter went to great lengths to find out why a certain effect took place. Feynman's point was that science requires great care that we don't draw conclusions not sufficiently informed by skepticism.
To summarize, to be able to claim a cause -- effect relationship, we would need to understand the cause -- we would need a falsifiable theory about why a change took place, not merely that there was a change.
A pointless method of study that's responsible for building the world you see around you, including the computer you're using for this conversation.
In science the problem is not getting the answers, it's being sufficiently skeptical of those who think they already have the answers.
> ... since we can't yet describe that from quantum phenomena upwards?
But that's not true -- we can describe it, but we can't explain it. Literature describes, science explains. Good science resists premature explanation.
And you can definitely make causal inferences if you don't understand everything. If that weren't true, you wouldn't be able to infer that moving your arm makes the coffee cup in your hand move unless you knew everything about physics.
The experiment showed a change in behavior resulting from a change in environment. There's no cause proposed that rises above opinion and conjecture. To be able to say why the change took place, we would need a falsifiable theory that offers an explanation, not just a description, which is all this study provides.
Further reading: http://calteches.library.caltech.edu/51/2/CargoCult.htm
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.