If you’re an academic and you’re using fake data or misleading statistics, you are doing harm rather than good in your academic career. You are defrauding the public, you are making our academic norms be about fraud, you are destroying both public trust in academia in particular and knowledge in general, and you are creating justified reasons for this destruction of trust. You are being incredibly destructive to the central norms of how we figure things out about the world—one of many of which is whether or not it is bad to eat meat, or how we should uphold moral standards.
And you’re doing it in order to extract resources from the public, and grab your share of the pie.
I would not only rather you eat meat. I would rather you literally go around robbing banks at gunpoint to pay your rent.
If one really, really did think that personally eating meat was worse than committing academic fraud—which boggles my mind, but supposing that—what the hell are you doing in academia in the first place, and why haven’t you quit yet? Unless your goal now is to use academic fraud to prevent people from eating meat, which I’d hope is something you wouldn’t endorse, and not what 99%+ of these people are doing. As the author of OP points out, if you can make it in academia, you can make more money outside of it, and have plenty of cash left over for salads and for subsidizing other people’s salads, if that’s what you think life is about.
You shouldn’t put these in the same category. Fake data is a much graver sin than failing to correct for multiple comparisons or running a study with a small sample size. For the second two, anyone who reads you paper can see what you did (assuming you mention all the comparisons you made) and discount your conclusions accordingly. For a savvy reader or meta-analysis author, a paper which commits these sins can still improve their overall picture of the literature, especially if they employ tools to detect/correct for publication bias. It’s not obvious to me that a scientist who employs these practices is doing harm with their academic career, especially given that readers are getting more and more savvy nowadays.
I don’t think “fraud” is the right word for these statistical practices. Cherry-picking examples that support your point, the way an opinion columnist does, is probably a more fraudulent practice.
It’s fair to say that fake data is a Boolean and a Rubicon, where once you do it once, at all, all is lost. Whereas there are varying degrees of misleading statistics versus clarifying statistics, and how one draws conclusions from those statistics, and one can engage in some amount of misleading without dooming the whole enterprise, so long as (as you note) the author is explicit and clear about what the data was and what tests were applied, so anyone reading can figure out what was actually found.
However, I think it’s not that hard for it to pass a threshold where it’s clearly fraud, although still a less harmful/dangerous fraud than fake data, if you accept that an opinion columnist cherry-picking examples is fraud (e.g. for it to be more fraudulent than that, especially if the opinion columnist isn’t assumed to be claiming that the examples are representative). And I like that example more the more I think about it, because that’s an example of where I expect to be softly defrauded in the sense that I assume that the examples and arguments are words written are soldiers chosen to make a point slash sell papers, rather than an attempt to create common knowledge and seek truth. If scientific papers are in the same reference class as that...
If you’re an academic and you’re using fake data or misleading statistics, you are doing harm rather than good in your academic career. You are defrauding the public, you are making our academic norms be about fraud, you are destroying both public trust in academia in particular and knowledge in general, and you are creating justified reasons for this destruction of trust. You are being incredibly destructive to the central norms of how we figure things out about the world—one of many of which is whether or not it is bad to eat meat, or how we should uphold moral standards.
And you’re doing it in order to extract resources from the public, and grab your share of the pie.
I would not only rather you eat meat. I would rather you literally go around robbing banks at gunpoint to pay your rent.
If one really, really did think that personally eating meat was worse than committing academic fraud—which boggles my mind, but supposing that—what the hell are you doing in academia in the first place, and why haven’t you quit yet? Unless your goal now is to use academic fraud to prevent people from eating meat, which I’d hope is something you wouldn’t endorse, and not what 99%+ of these people are doing. As the author of OP points out, if you can make it in academia, you can make more money outside of it, and have plenty of cash left over for salads and for subsidizing other people’s salads, if that’s what you think life is about.
You shouldn’t put these in the same category. Fake data is a much graver sin than failing to correct for multiple comparisons or running a study with a small sample size. For the second two, anyone who reads you paper can see what you did (assuming you mention all the comparisons you made) and discount your conclusions accordingly. For a savvy reader or meta-analysis author, a paper which commits these sins can still improve their overall picture of the literature, especially if they employ tools to detect/correct for publication bias. It’s not obvious to me that a scientist who employs these practices is doing harm with their academic career, especially given that readers are getting more and more savvy nowadays.
I don’t think “fraud” is the right word for these statistical practices. Cherry-picking examples that support your point, the way an opinion columnist does, is probably a more fraudulent practice.
It’s fair to say that fake data is a Boolean and a Rubicon, where once you do it once, at all, all is lost. Whereas there are varying degrees of misleading statistics versus clarifying statistics, and how one draws conclusions from those statistics, and one can engage in some amount of misleading without dooming the whole enterprise, so long as (as you note) the author is explicit and clear about what the data was and what tests were applied, so anyone reading can figure out what was actually found.
However, I think it’s not that hard for it to pass a threshold where it’s clearly fraud, although still a less harmful/dangerous fraud than fake data, if you accept that an opinion columnist cherry-picking examples is fraud (e.g. for it to be more fraudulent than that, especially if the opinion columnist isn’t assumed to be claiming that the examples are representative). And I like that example more the more I think about it, because that’s an example of where I expect to be softly defrauded in the sense that I assume that the examples and arguments are words written are soldiers chosen to make a point slash sell papers, rather than an attempt to create common knowledge and seek truth. If scientific papers are in the same reference class as that...