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> As a typical example, Russian propaganda sources have replied to accusation of Russian war crimes in Ukraine with "The US has invaded Iraq and committed count

> As a typical example, Russian propaganda sources have replied to accusation of Russian war crimes in Ukraine with "The US has invaded Iraq and committed countless war crimes." Sure, and if someone only called out Russian war crimes you shouldn't take them as "a person who dislikes war crimes" but "a person who dislikes Russia", and expect them to produce information on that basis. This is not fallacious, it's vital information to understand what they're saying: when they say "Russia has committed a war crime", it does not imply that this is an uncommon crime to have committed. Other nations could be committing that war crime all the time and that person wouldn't raise it to your attention, because they're focused on Russia. The knowledge of their stance is necessary to understand what they're saying at all. And that's even before accounting for positive bias, where you're not mentioning American war crimes despite knowing of them because you have positive feelings about America. (The same thing happens, of course, in reverse.) You can't have a discussion only in the positive space of what is actually said; words simply don't work like that. Every concretization in a message implies information by means of generalizations you didn't make. If I say "jews murder thousands of people every year", then I imply that this number lies above the baserate of murders; if it in fact doesn't or is less than the baseline, then I've been (possibly intentionally) deceptive without ever saying a false word. (Base rate fallacy!) This is not a rare corner case, it's extremely widespread. > The arguer wanted to relativize the arguments against tech billionaires in the real topic. Correct, and this is a valid argumentative technique. Why wouldn't it be? That's just a framing/categorization debate. They're a proxy for causal-structure debates for people who don't know the term "causal structure". "Is Elon Musk an usual or unusual member of the category of billionaire social network owners" is material to the article.

jonathanstrange 3y ago
I couldn't disagree more, especially about Russia example because the Russian war qualifies, by application of objective criteria from UN conventions and ICC, as a genocide. You're right about the murders example, but this is not related at all to the above debate and, again, a deviation. Whether Elon Musk is an outlier and exceptionally evil as a tech billionaire or whether every tech billionaire is as evil as him has absolutely not the slightest bearing on his evilness. That's why the accusation of whataboutism is perfectly adequate and reasonable in this case. As I said in my initial post, the moral independence of actions is codified in law and common practice. The "others did it too" defense does not work in criminal court, and I can assure you that it will also not work for Russia. > Correct, and this is a valid argumentative technique. It's provably a fallacy. On a side note, framing has nothing to do with making fallacious arguments, it only pertains to how you express arguments. "The glass is half full" vs "The glass is half empty" -- that's framing. Two different arguments about the same topic -- that's not framing. It also has nothing to do with the baserate fallacy. If someone commits a baserate fallacy, you simply point out that they've committed a baserate fallacy. This only makes sense for statistical arguments. Framing and categorization are also two totally different terms for different application domains. Framing does not concern the categories and population you choose when making statistical inferences. I don't know why people misuse the term all the time, it's not hard to understand if you look at the original literature in experimental psychology. Framing is also not related in any obvious way with causal structure/causal models. Moreover, your example about Elon Musk is not about causal structure, it concerns a statistical property; at least, I cannot see how a causal model can be used to support "usual" vs. "unusual" attributions. However, I grant you that maybe it could be spelled out in causal modeling terms, for example in Judea Pearl's approach, but it's not obvious how to do that. Anyway, for me this discussion is closed. You're not very persuasive because you're using the wrong terminology. As I said, I'm interested in this topic also from a professional perspective. I know what I'm talking about (whether you believe me or not). I'll keep it at that and close this conversation.

jonathanstrange 3y ago

I couldn't disagree more, especially about Russia example because the Russian war qualifies, by application of objective criteria from UN conventions and ICC, as a genocide. You're right about the murders example, but this is not related at all to the above debate and, again, a deviation. Whether Elon Musk is an outlier and exceptionally evil as a tech billionaire or whether every tech billionaire is as evil as him has absolutely not the slightest bearing on his evilness. That's why the accusation of whataboutism is perfectly adequate and reasonable in this case. As I said in my initial post, the moral independence of actions is codified in law and common practice. The "others did it too" defense does not work in criminal court, and I can assure you that it will also not work for Russia. > Correct, and this is a valid argumentative technique. It's provably a fallacy. On a side note, framing has nothing to do with making fallacious arguments, it only pertains to how you express arguments. "The glass is half full" vs "The glass is half empty" -- that's framing. Two different arguments about the same topic -- that's not framing. It also has nothing to do with the baserate fallacy. If someone commits a baserate fallacy, you simply point out that they've committed a baserate fallacy. This only makes sense for statistical arguments. Framing and categorization are also two totally different terms for different application domains. Framing does not concern the categories and population you choose when making statistical inferences. I don't know why people misuse the term all the time, it's not hard to understand if you look at the original literature in experimental psychology. Framing is also not related in any obvious way with causal structure/causal models. Moreover, your example about Elon Musk is not about causal structure, it concerns a statistical property; at least, I cannot see how a causal model can be used to support "usual" vs. "unusual" attributions. However, I grant you that maybe it could be spelled out in causal modeling terms, for example in Judea Pearl's approach, but it's not obvious how to do that. Anyway, for me this discussion is closed. You're not very persuasive because you're using the wrong terminology. As I said, I'm interested in this topic also from a professional perspective. I know what I'm talking about (whether you believe me or not). I'll keep it at that and close this conversation.