6 ms·

The two researchers actually have a number of publications in data science, please sniff again. Your kind of argument is called a an appeal to an irrelevant aut

The two researchers actually have a number of publications in data science, please sniff again. Your kind of argument is called a an appeal to an irrelevant authority. You also forgot to cite your sources or link to the data you are advocating for. Please consider taking the time to properly advocate your point

jlmorton 4y ago
Two people who have never published in epidemiology stumble upon a new method for calculating excess deaths, at odds with all the existing sources, whether official sources like the WHO, domestic official government sources, or other independent groups like The Economist which have tracked this closely. And lo and behold, what do they find? A wildly different result that shows no deaths from Covid and all the deaths from the vaccine. No, I'm not going to sniff again, because it stinks to the high heavens.
- cf141q5325 4y ago
  I think we could all appreciate if anyone with an epidemiology background could explain what disqualifies data scientists from working with this dataset. edit: Not a data scientists myself obviously
  - Arnt 4y ago
    I'm not an epidemiologist, but I've written code for people in various fields. I knew code, they knew the domain. All of them knew things that I would have fucked up, if I had tried to write the code with just my programming knowledge and my big brain, without their domain knowledge and experience. A university education teaches you something. I assume that epidemiology is like the other university fields — when lay people come and show that the epidemiologists are wrong about epidemiology, they're about as likely to be right as the people who write to maths professors claiming to have found a method of trisecting an angle. And the people with the novel claim and the missing education bear the burden of proof.
    - cf141q5325 4y ago
      I dont think that comparison is universally applicable. I wouldnt rule out that this is a lot more similar to a Math Prof telling you that the p-values in for example your psychology paper are nonsense and correcting you. edit: Not saying studying Math qualifies you to design and run studies in Psychology. But once you break down tasks enough you will often find them to be the area of expertise of another discipline. Often its very easy to tell when the Professor that taught you something in university is from another department.
- claytongulick 4y ago
  When we close ourselves off to new information, especially if it's contrary to deeply held beliefs, our opinions devolve from informed to merely dogmatic.
  - jlmorton 4y ago
    That is absurd, and little more than a platitude. Let's set the stage here: * I am not an epidemiologist * The authors of this study are not epidemiologists * The paper has not been peer-reviewed * The authors invent a new statistical method for estimating excess deaths, it is at odds with all other sources, and it just so happens to show no excess deaths from Covid until the vaccine is released In situations like this, you should always default to disbelief.
    - cf141q5325 4y ago
      > In situations like this, you should always default to disbelief. Thats some really unfortunate wording. None of this should be a matter of belief.
    - mandmandam 4y ago
      You are not coming across like you read the paper. Nor does it seem like you are making an argument in good faith. I see a weird ad-hominem, appeals to authority and tradition, and some knee-jerk criticism. You haven't addressed legitimate criticism of your arguments, and you're all over this thread (6 of 44 comments) trying to convince people to dismiss this out of hand. Your main criticism seems to be that the paper points out an anathema correlation, therefore warranting immediate disbelief and removal from discussion... Who are you, to make such a strong claim? Since when is that how discussions or science work, even if you were the world's top epidemiology / statistical method specialist?
      - orwin 4y ago
        Extraordinary claims require extraordinary evidence. I'd say that with only reading the abstract, i gave this study a baysian 15% likelyhood. Then i read the first chapter, and it fell to .0015 or something like this. I actually worked at a cloud provider dedicated to provide a lot of Ram and GPU ressources to researchers, and we worked with 'ARS grand Est' (think local CDC who coordinate hospital response and emergency allocation for all hospital, including private clinics, in a State) in March through june 2020. I've seen the numbers, I've read the rapports firsthand, before the French lockdowns, i imported the data files and seen the different number of reported death at Colmar compared to the biggest hospital of the Area (Strasbourg). There is no way this document is true. Want to be sure? Just look at Bergame vs Sienna, or even just Colmar vs Strasbourg in March/April 2020. This is hugely unlikely.
- grungy 4y ago

jlmorton 4y ago

Two people who have never published in epidemiology stumble upon a new method for calculating excess deaths, at odds with all the existing sources, whether official sources like the WHO, domestic official government sources, or other independent groups like The Economist which have tracked this closely. And lo and behold, what do they find? A wildly different result that shows no deaths from Covid and all the deaths from the vaccine. No, I'm not going to sniff again, because it stinks to the high heavens.

cf141q5325 4y ago
I think we could all appreciate if anyone with an epidemiology background could explain what disqualifies data scientists from working with this dataset. edit: Not a data scientists myself obviously
- Arnt 4y ago
  I'm not an epidemiologist, but I've written code for people in various fields. I knew code, they knew the domain. All of them knew things that I would have fucked up, if I had tried to write the code with just my programming knowledge and my big brain, without their domain knowledge and experience. A university education teaches you something. I assume that epidemiology is like the other university fields — when lay people come and show that the epidemiologists are wrong about epidemiology, they're about as likely to be right as the people who write to maths professors claiming to have found a method of trisecting an angle. And the people with the novel claim and the missing education bear the burden of proof.
  - cf141q5325 4y ago
    I dont think that comparison is universally applicable. I wouldnt rule out that this is a lot more similar to a Math Prof telling you that the p-values in for example your psychology paper are nonsense and correcting you. edit: Not saying studying Math qualifies you to design and run studies in Psychology. But once you break down tasks enough you will often find them to be the area of expertise of another discipline. Often its very easy to tell when the Professor that taught you something in university is from another department.
claytongulick 4y ago
When we close ourselves off to new information, especially if it's contrary to deeply held beliefs, our opinions devolve from informed to merely dogmatic.
- jlmorton 4y ago
  That is absurd, and little more than a platitude. Let's set the stage here: * I am not an epidemiologist * The authors of this study are not epidemiologists * The paper has not been peer-reviewed * The authors invent a new statistical method for estimating excess deaths, it is at odds with all other sources, and it just so happens to show no excess deaths from Covid until the vaccine is released In situations like this, you should always default to disbelief.
  - cf141q5325 4y ago
    > In situations like this, you should always default to disbelief. Thats some really unfortunate wording. None of this should be a matter of belief.
  - mandmandam 4y ago
    You are not coming across like you read the paper. Nor does it seem like you are making an argument in good faith. I see a weird ad-hominem, appeals to authority and tradition, and some knee-jerk criticism. You haven't addressed legitimate criticism of your arguments, and you're all over this thread (6 of 44 comments) trying to convince people to dismiss this out of hand. Your main criticism seems to be that the paper points out an anathema correlation, therefore warranting immediate disbelief and removal from discussion... Who are you, to make such a strong claim? Since when is that how discussions or science work, even if you were the world's top epidemiology / statistical method specialist?
    - orwin 4y ago
      Extraordinary claims require extraordinary evidence. I'd say that with only reading the abstract, i gave this study a baysian 15% likelyhood. Then i read the first chapter, and it fell to .0015 or something like this. I actually worked at a cloud provider dedicated to provide a lot of Ram and GPU ressources to researchers, and we worked with 'ARS grand Est' (think local CDC who coordinate hospital response and emergency allocation for all hospital, including private clinics, in a State) in March through june 2020. I've seen the numbers, I've read the rapports firsthand, before the French lockdowns, i imported the data files and seen the different number of reported death at Colmar compared to the biggest hospital of the Area (Strasbourg). There is no way this document is true. Want to be sure? Just look at Bergame vs Sienna, or even just Colmar vs Strasbourg in March/April 2020. This is hugely unlikely.
grungy 4y ago