This reminds me of the 2013 finding that showed an earlier 2010 study praising austerity as a recovery mechanism was flawed because of an Excel calculation error and lack of diligence.
It just may be that these things should be reviewed a little closer by people who are obsessive about correctness
No amount of review is enough. As anyone who's worked in quant science will attest, a model that hasn't repeatedly made correct out-of-sample predictions is most likely worthless, as it's far far easier to overfit a model to data than to predict the future.
flaws in the London epidemiological model about how to respond to covid.
That one was fun. I got into an argument with a scientist who was (IIRC) working with or for the specific professor that made that mess, and he blamed the entire software engineering/computer science industry for making C++ too hard to use, and said it should never have been released if mistakes like this could be made. And then accused me of gatekeeping when I said perhaps they should get an expert to look over this stuff before submitting results to governments to form a policy basis.
The attitude seemed to be "I am a scientist and am clearly very smart, and therefore anything you do must be trivial in comparison. If I can't pick up in seconds what takes you years to learn and more years to perfect, you've clearly done it all wrong and it's your fault."
The wikipedia writeup is a lot kinder to it than anyone was at the time, it was generally considered poorly put together and full of errors that made reproducibility questionable if not impossible.
Please note I'm not a covid conspiracist and I don't have a strong anti-lockdown streak, I got vaccinated and stayed indoors when asked to. I do have a general interest in government policy being based on sound information though.
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This reminds me of the 2013 finding that showed an earlier 2010 study praising austerity as a recovery mechanism was flawed because of an Excel calculation error and lack of diligence.
https://inthesetimes.com/article/the-excel-error-heard-round...
It also reminds me of the flaws in the London epidemiological model about how to respond to covid.
It just may be that these things should be reviewed a little closer by people who are obsessive about correctness
No amount of review is enough. As anyone who's worked in quant science will attest, a model that hasn't repeatedly made correct out-of-sample predictions is most likely worthless, as it's far far easier to overfit a model to data than to predict the future.
That one was fun. I got into an argument with a scientist who was (IIRC) working with or for the specific professor that made that mess, and he blamed the entire software engineering/computer science industry for making C++ too hard to use, and said it should never have been released if mistakes like this could be made. And then accused me of gatekeeping when I said perhaps they should get an expert to look over this stuff before submitting results to governments to form a policy basis.
The attitude seemed to be "I am a scientist and am clearly very smart, and therefore anything you do must be trivial in comparison. If I can't pick up in seconds what takes you years to learn and more years to perfect, you've clearly done it all wrong and it's your fault."
Can someone cite what we're talking about here because it sounds vaguely conspiracy theory... During covid.
You know what I mean?
https://en.wikipedia.org/wiki/CovidSim
The wikipedia writeup is a lot kinder to it than anyone was at the time, it was generally considered poorly put together and full of errors that made reproducibility questionable if not impossible.
Please note I'm not a covid conspiracist and I don't have a strong anti-lockdown streak, I got vaccinated and stayed indoors when asked to. I do have a general interest in government policy being based on sound information though.