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I wasn't saying it was the same, my point is that reporting the data on which one can update in Bayesian manner is the norm. (As is updating, e.g. if the null hypothesis is really plausible, at p<0.05 nobody's really going to believe you anyway)
With regards to the Bayes factor. The issue is that there is a whole continuum of alternate hypotheses. There's no single factor between those that you can report on which could be used for combining evidence in favour of quantitatively different alternative "most supported" hypotheses. The case of the null hypothesis (vs all possible other hypotheses) is special in that regard, and so that is what a number is reported for.
With regards to the case of the ratio between evidence for two point hypotheses, as discussed in the article you link: Neyman-Pearson lemma is quite old.
With regards to the cause of experiment termination, you have to account somewhere for the fact that termination of the experiment has the potential to cherry pick and thus bias the resulting data (if that is what he's talking about, because its not clear to me what is his point and it seems to me that he misunderstood the issue).
Furthermore, the relevant mathematics probably originates from the particle physics, where it serves a different role: a threshold on the p-value is here to quantify the worst-case likelihood that your experimental apparatus will be sending people on the wild goose chase. It has more to do with the value of the experiment than probabilities, given that priors for hypotheses in physics would require a well defined hypotheses space (which is absent). And given that the work on the production of stronger evidence is a more effective way to spend your time there than any debating of the priors. And given that the p-value related issues in any case can be utterly dwarfed by systematic errors and problems with the experimental set up, something the probability of which changes after the publication as other physicists do or do not point towards potential problems in the set up.
A side note: there's a value of information issue here. I know that if I were to discuss Christian theology with you (not the atheism, but the fine points of the life of Jesus, that sort of thing, which I never really had time or inclination to look into), the expected value of information to you would be quite low. Because most of the time that I spent practising mathematics and such, you spent on the former. It would be especially the case if you entered some sort of very popular contest in any way requiring theological knowledge, and scored #10th of all time on a metric that someone else seen fit to chose in advance. The same goes for discussions of mathematics, but the other way around. This is also the case for any experts you are talking to. They're rather rational people, that's how they got to have impressive accomplishments, and a lot of practical rationality is about ignoring low expected value pursuits. Einsteins and Fermis of this world do not get to accomplish so much on so many different occasions without great innate abilities for that kind of thing. They also hold teaching positions and it is more productive for them to correct misconceptions in the eager students who are up to speed on the fundamental knowledge.
(with #10th I'm alluding to this result of mine ).
Mmm. I've read a lot of dumb papers where they show that their model beats a totally stupid model, rather than that their model beats the best model in the literature. In algorithm design fields, you generally need to publish a use case where your implementation of your new algorithm beats your implementation of the best other algorithms for that problem in the field (which is still gameable, because you implement both algorithms, but harder).
Thinking about the academic controversy I learned about most recently, it seems like if authors had to say "this evidence is n:1 support for our hypothesis over the hypothesis proposed in X" instead of "the evidence is n:1 support for our hypothesis over there being nothing going on" they would have a much harder time writing papers that don't advance the literature, and you might see more scientists being convinced of other hypotheses because they have to implement them personally.
In physics a new theory has to be supported over the other theories, for example. What you're talking about would have to be something that happens in sciences that primarily find weak effects in the noise and co-founders anyway, i.e. psychology, sociology, and the like.
I think you need to specifically mention what fields you are talking about, because not everyone knows that issues differ between fields.
With regards to malemployment debate you link, there's a possibility that many of the college graduates have not actually learned anything that they could utilize, in the first place, and consequently there exist nothing worth describing as 'malemployment'. Is that the alternate model you are thinking of?
Most of the examples I can think of come from those fields. There are a few papers in harder sciences which people in the field don't take seriously because they don't address the other prominent theories, but which people outside of the field think look serious because they're not aware that the paper ignores other theories.
I was thinking mostly that it looked like the two authors were talking past one another. Group A says "hey, there's heterogeneity in wages which is predicted by malemployment" whereas Group B says "but average wages are high, so there can't be malemployment," which ignores the heterogeneity. I do think that a signalling model of education (students have different levels of talent, and more talented students tend to go for more education, but education has little direct effect on talent) explains the heterogeneity and the wage differentials, and it would be nice to see both groups address that as well.
Once again, which education? Clearly, a training course for, say, a truck driver, is not signalling, but exactly what it says on the can: a training course for driving trucks. A language course, likewise so. Same goes for mathematics, hard sciences, and engineering disciplines. Which may perhaps be likened to necessity of training for a formula 1 driver, irrespective of the level of innate talent (within the human range of ability).
Now, if that was within the realm of actual science, something like this "signalling model of education" would be immediately invalidated by the truck driving example. No excuses. One can mend it into a "signalling model of some components of education in soft sciences". Where there's a big problem for "signalling" model: a PhD in those fields in particular is a poorer indicator of ability, innate and learned, than in technical fields (lower average IQs, etc), and signals very little.
edit: by the way, the innate 'talent' is not in any way exclusive of importance of learning; some recent research indicates that highly intelligent individuals retain neuroplasticity for longer time, which lets them acquire more skills. Which would by the way explain why child prodigies fairly often become very mediocre adults, especially whenever lack of learning is involved.
If there was a glut of trained truck drivers on the market and someone needed to recruit new crane operators, they could choose to recruit only truck drivers because having passed the truck driving course would signal that you can learn to operate heavy machinery reliably, even if nothing you learned in the truck driving course was of any value in operating cranes.
OSHA rules would still require that the crane operator passes the crane related training.
The term 'signalling' seem to have heavily drifted and mutated online to near meaninglessness.
If someone attends a truck driving course with the intention of driving trucks - or a math course with the intention of a: learning math and b: improving their thinking skills - that's not signalling behaviour.
And conversely, if someone wants to demonstrate some innate or pre-existing quality (such as mathematical ability), they participate in a relevant contest, and this is signalling.
Now, there may well be a lot of people who start in an educated family and then sort of drift through the life conforming to parental wishes, and end up obtaining, say, a physics PhD. And then they go to economics or something similar where they do not utilize their training in much any way. One could deduce about these people that they are more innately intelligent than average, more wealthy than average, etc etc, and that they learned some thinking skills. The former two things are much more reliably signalled with an IQ test and a statement from IRS.
I think it's more that the concept entered LessWrong via Robin Hanson's expansion of the concept into his "Homo Hypocritus" theory. For examples, see every post on Overcoming Bias with a title of the form "X is not about Y". This theory sees all communicative acts as signalling, that is to say, undertaken with the purpose of persuading someone that one possesses some desirable characteristic. To pass a mathematics test is just as much a signal of mathematical ability as to hang out with mathematicians and adopt their jargon.
There is something that distinguishes actual performance from other signals of ability: unforgeability. By doing something that only a mathematician could do, one sends a more effective signal -- that is, one more likely to be believed -- that one can do mathematics.
This is a radical re-understanding of communication. On this view, not one honest thing has ever been said, not one honest thing done, by anyone, ever. "Honesty" is not a part of how brains physically work. Whether we tell a truth or tell a lie, truth-telling is never part of our purpose, but no more than a means to the end of persuading people of our qualities. It is to be selected as a means only so far as it may happen to be more effective than the alternatives in a given situation. The concept of honesty as a virtue is merely part of such signalling.
The purpose of signalling desirable qualities is to acquire status, the universal currency of social interaction. Status is what determines your access to reproduction. Those who signal status best get to reproduce most. This is what our brains have evolved to do, for as long as they been able to do this at all. Every creature bigger than an earthworm does it.
Furthermore, all acts are communicative acts, and therefore all acts are signalling. Everything we do in front of someone else is signalling. Even in solitude we are signalling to ourselves, for we can more effectively utter false signals if we believe them. Every thought that goes through your head is self-signalling, including whatever thoughts you have while reading this. It's all signalling.
Such, at least, is the theory.
...which means that describing an act as "signalling" is basically meaningless, insofar as it fails to ascribe to that act a property that distinguishes it from other acts. It's like describing my lunch as "material". True, yes, but uninteresting except as a launching point to distinguish among expensive and cheap signals, forgeable and unforgeable signals, purely external signals and self-signalling, etc.
That said, in most contexts when a behavior is described as "signalling" without further qualification I generally understand the speaker to be referring more specifically to cheap signalling which is reliably treated as though it were a more expensive signal. Hanging out with mathematicians and adopting their jargon without really understanding it usually falls in this category; completing a PhD program in mathematics usually doesn't (though I could construct contrived exceptions in both cases).
That a proposition has the form "every X is a Y" does not make it uninteresting. For example: All matter is made of atoms. All humans are descended from apes. God made everything. Every prime number is a sum of three squares. Everyone requires oxygen to live. True or false, these are all meaningful, interesting statements. "All acts are acts of signalling" is similarly so.
Yes, this subtext is present whenever the concept of signalling is introduced (another example of an "all X is Y" which is nevertheless a meaningful observation).
You can say that whether it's signaling is determined by the motivations of the person taking the course, or the motivations of the people offering the course, or the motivations of employers hiring graduates of the course. And you can define motivation as the conscious reasons people have in their minds, or as the answer to the question of whether the person would still have taken the course if it was otherwise identical but provided no signaling benefit. And there can be multiple motivations, so you can say that something is signaling if signaling is one of the motivations, or that it's signaling only if signaling is the only motivation.
If you make the right selections from the previous, you can argue for almost anything that it's not signaling, or that it is for that matter.
If I wanted to defend competitions from accusations of signaling like you defended education, I could easily come up with lots of arguments. Like people doing them to challenge themselves, experience teamwork, test their limits and meet like-minded people. And the fact that lots of people that participate in competitions even though they know they don't have a serious chance of coming on top, etc.
(Sure, but I meant that only truck drivers would be accepted into the crane operator training in the first place, because they would be more likely to pass it and perform well afterward.)
Given the way the term is actuallly used, I wouldn't call that "signalling" because "signalling" normally refers to demonstrating that you have some trait by doing something other than performing the trait itself (if it's capable of being performed). You can signal your wealth by buying expensive jewels, but you can't signal your ability to buy expensive jewels by buying expensive jewels. And taking a math test to let people know that you're good at math is not signalling, but going to a mathematicians' club to let people know that you're good at math may be signalling.
This seem to be the meaning common on these boards, yes.
Going to mathematicians club (and the like) is something that you can do if you aren't any good at math, though. And it only works as a "signal" of being good at math because most people go to that club for other reasons (that would be dependent on being good at math).
Signalling was supposed to be about credibly conveying information to another party whenever there is a motivation for you to lie.
It seems that instead signalling is used to refer to behaviours portrayed in "Flowers for Charlie" episode of "It's always sunny in Philadelphia".
Generally, the signalling model of education refers to the wage premium paid to holders of associates, bachelors, masters, and doctoral degrees, often averaged across all majors. (There might be research into signalling with regards to vocational degrees, but I think most people that look into that are more interested in licensing / scarcity effects.)
Well, in the hard science majors, there's considerable training, which is necessary for a large fraction of occupations. Granted, a physics PhD who became an economist may have been signalling, but it is far from the norm. What is the norm is that vast majority of individuals employed as physics PhDs would be unable to perform some parts of their work if they hadn't undergone relevant training, just as you wouldn't have been able to speak a foreign language or drive a car without training.