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That said, they should be well-informed on the subject. So it probably does contain a lot of good information.
Recently I have been beginning to question university education. It seems that today's education system has mismatched priorities which may have an impact on the reproducibility crisis. You see, to come up with a fantastic new alloy, you don't have to be a genius. Or even very good. You have to be persistent, and clever enough to realize when you've found something interesting. You will need to understand your field…
I do suspect that profit motive isn't enough to drive effective R&D, though, I just don't know exactly how to articulate a model for why except at the basic level that that truly searching R&D has a higher risk profile than other opportunities for profit.
I support the idea of more tax-supported public funding for a variety of things. I'd also support reshaping the tax code to incentivize R&D. But I'm also not sure that's a going to give everybody their opportunity -- I'd imagine there'd still be lucky ones there too. And we'd still have a lot of work to do to address incentives that drive reproducibility issues.
The site is down so I can't read the original report, but I've read reports on this topic in the past so I'm going to chime in with some "usual suspects" caveats: 1. No result is 100% reproducible because you can never completely reproduce the conditions of any experiment. The best you can hope to do is to reproduce the conditions that matter , but enumerating those has to be part of the theory you are testing, and s…
I am not sure this is correct. The rules that govern celestial bodies is same as the ones that govern objects on earth. So why are they not reproducible? It does not require to measure forces between celestial bodies to measure the value of G. Measuring the forces between two masses on earth is enough.
The site is down so I can't read the original report, but I've read reports on this topic in the past so I'm going to chime in with some "usual suspects" caveats: 1. No result is 100% reproducible because you can never completely reproduce the conditions of any experiment. The best you can hope to do is to reproduce the conditions that matter , but enumerating those has to be part of the theory you are testing, and s…
4.) You mean that papers are published with P When did this become a "standard"? Most papers I have seen in respectable journals and other sources would not strive for such a high Pvalue, it would be much lower like 0.001.
> When did this become a "standard"?
I have no idea. You'll have a ask a historian.
Lets take a page from Marx. Science is many things, in particular a relationship between capital and labor. The scientific method is a wonderful idea, but it is subordinate to the economic forces that underlie scientific activity. Look at the conflicts and contradictions between those doing science (labor) and those deciding the science to be done (capital), and that is the ultimate source of these crises. The execut…
The site is down so I can't read the original report, but I've read reports on this topic in the past so I'm going to chime in with some "usual suspects" caveats: 1. No result is 100% reproducible because you can never completely reproduce the conditions of any experiment. The best you can hope to do is to reproduce the conditions that matter , but enumerating those has to be part of the theory you are testing, and s…
4.) You mean that papers are published with P When did this become a "standard"? Most papers I have seen in respectable journals and other sources would not strive for such a high Pvalue, it would be much lower like 0.001.
While not everyone in a particular field has been a party to this myopic view of statistical significance, enough have been that the American Statistical Association released a statement on the topic not long ago. That may not seem like a big deal but, given the organization's historical reticence to officially weigh in on such issues, it really is.
ASA statement on p-Values: https://www.amstat.org/asa/files/pdfs/P-ValueStatement.pdf
The site is down so I can't read the original report, but I've read reports on this topic in the past so I'm going to chime in with some "usual suspects" caveats: 1. No result is 100% reproducible because you can never completely reproduce the conditions of any experiment. The best you can hope to do is to reproduce the conditions that matter , but enumerating those has to be part of the theory you are testing, and s…
I have a pedantic correction, but a relevant one. If a journal makes a rule that results must have p < .05, and then scientists go off and do a bunch of well-managed science they will get results with a range of p-values. .05 will be a ceiling, not a floor, on the possible p-values. More papers have a p-values right around .05 than they would if results were being produced fairly, so that's actually evidence of bad practices.
Earlier quoted context omitted.
So you'd ignore one of the most horrific and important examples of widely accepted science going wrong because of an internet meme?
Science didn't go wrong. The data was bad, the processes were bad, there was no replication. How was that science?
People are really quick to say this, but how many people have actually studied the 'racial science' literature of the 20s and 30s and figured out to what extent it meets the methodological standards of today? Yes, we know that they drew incorrect (and reprehensible) conclusions. It doesn't necessarily follow that their methods were any worse (epistemically speaking) than methods that currently pass muster.
Lets take a page from Marx. Science is many things, in particular a relationship between capital and labor. The scientific method is a wonderful idea, but it is subordinate to the economic forces that underlie scientific activity. Look at the conflicts and contradictions between those doing science (labor) and those deciding the science to be done (capital), and that is the ultimate source of these crises. The execut…
Maybe the biggest problem is what you mention, but in another direction. For whatever reason there seems to be extremely little interest in the private direct funding of science. In times past the aristocracy would often fund scientific research on all sorts of topics. Today the practice seems to have all but disappeared, certainly if we measure relative ratios of the practice.
We know that weak classifiers can be bagged to produce a strong classifier al la Adaboost. Each study is a weak classifier and would have a 'reproducibility crisis' if retested on new data. However after lots of studies of similar phenomena, a strong classifier emerges. In the field, we call this converging lines of evidence.
I'm not sure I really agree with this, because in science studies are biased towards aligning with the results of previous studies. This can be due to many factors: authors' expectations, journals like to publish positive over negative results, peer reviewers will look more critically (in an analytical sense) at work that disagrees with accepted research, etc.... It can be very hard for many reasons to stand up and s…
If the replication crisis had been as well-known back then, she might have fared better.