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Reblogged:Who Paid for That? Is Not an Argument

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Have you ever been flummoxed or annoyed by someone asking Who funded that? -- or otherwise dismissing a valid claim simply because the work that established that claim was financed by someone that person disapproves of?

If so, Joakim Book wrote the column for you back in October last year.

Among many good points is one worth keeping tucked away for any future (and probably inevitable) encounter with this erroneous practice:
Possible comeback: "Who's your boss? Is he paying you to tell me this?" (Image by Celyn Kang, via Unsplash, license.)
As soon as the Bought-and-Paid-For objection is raised, two strange things happen. First, we start investigating the funding relationships behind the research in a totally unworthy fashion -- remarkably akin to identity politics: what someone says is downplayed in favor of the skin color, gender, class, or demographics of the person saying it, or in this case their funding bodies. That is, we cease following the proud tradition of the Enlightenment and turn back time a few centuries in the application of scientific inquiry: devout believer or heretic destined for the stake?

Second, we disregard the evidence of the case in question! Instead of looking at what matters for the case at hand we look at what doesn't matter: the identity of the researcher, her previous allegiances or funding backgrounds. [links omitted, bold added]
Book continues, providing as a counterexample his own work, which was indirectly attacked because he is affliated with a think tank that received a donation from -- gasp! -- the Koch Foundation.

Book is careful to state that people from both the left and the right are guilty of this error. In my experience, it has been more common on the left, but it is becoming more common on the right.

Regarding leftists, they seem blind to the possibility of government funding being a corrupting influence. I would watch for the right, which seems less and less rational -- and more like the left -- by the minute these days, to start making a similar error, but in the opposite direction: They will start assuming that government funding is a reason for suspicion, if they haven't already.

Regarding the last: Consider how the right's new anti-vaxxers talk about the FDA and the CDC now. Regardless of whether either agency should exist, the fact is that there are now scientists doing legitimate work for each and who make public statements and arguments about facts, vaccines in particular, for example. Judgements about these statements have to be made in a full context, of which institutional affiliation and funding are but a part.

-- CAV

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I agree with this, but I'd generalize a bit further:

"Who paid for that" is really just another kind of ad hominem.

The evidence for and against a claim should be the only thing that matters for establishing its truth. The question is not who says it, but why they say it, and whether they have a good reason, rooted in facts.

Too many people seem obsessed with asking "who says that," as if identifying the people saying something is enough, by itself, to determine whether it is true or false. "Who paid for that" is just another form of "who says that."

Many of these people are tribalists. What they are saying boils down to, "everything my tribe says is true, while everything your tribe says is false." It's childish, really, and there's no way to reason with such people.

I suppose such people find it easier to determine a claim's tribal affiliation than to actually try to assess the evidence. It's also far, far less accurate, but in my experience, a lot of people (in the general population) care more about fitting in with their group than about being accurate. Sigh...

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To paraphrase Marx , " I wouldn't be a member of any tribe that would let me in their sweatlog."

I'm not sure if the funding is or should be an issue about the reasonable-ness of scientific findings when those findings come from voices that gloss over the fact that observation and data collection of multiyear studies can be reasonably compressed to nth/year studies and still hold the same standards of reliability.

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