[mvhvv]

Assumptions and reductions are always required, there is no researcher in the world that reads every book or paper released in their field, and for those that do read voraciously, only a tiny fragment of that is remembered or understood on the grounds that the author intended.

Part of learning is to deciding which parts to ignore. The book is rejected on it's face because its core claim is essentially "I solved a major issue in another field by reducing it down to the one I know", which is a big red-flag for crank claims.

The article's focus on spreadsheets is part of why it's so easy to brush it aside. The author doesn't realise that the fidelity of the spreadsheet is less important than their own ideological assumptions.

It's possible they cover this in detail in the book, but it's not in this article, nor in any description of the book I've encountered. If something appears as crank-science on it's face (and is getting little traction), then why waste your time on it?

[mdoms]

> Assumptions and reductions are always required, there is no researcher in the world that reads every book or paper released in their field

It's good practice to read the ones you're commenting on.

[mvhvv]

I read the article, and I even read through the presentation linked in the article. I didn't read the book, but I'm also not giving a qualitative review of the book.

I'm talking about why people don't think it's worth engaging with to begin with. It's not that his critics are afraid or incapable of engaging with him, but that he's being dismissed out of hand because (regardless of whether it's true or not) he presents as a crank who doesn't appear to understand the field he's attempting to critique.

There's an infinite supply of cranks in the world, and it's usually good practice to avoid engaging with them.

[mdoms]

> I'm talking about why people don't think it's worth engaging with to begin with.

But that's not what the author is talking about in his article - you did read it, right? His book is drawing criticism from people who haven't read it. It's fine to choose not to engage with something, but if you're going to comment on it you should read it.

[mvhvv]

Yes, like I said, I read the article, and I read the linked notes. The article was not really about people criticising his book without reading it, the article was about not engaging in qualitative criticism of his spreadsheets.

Caplan indirectly mentions a paper criticising him, and his dismissal is that it doesn't acknowledge the math.

It's entirely reasonable to comment on why you're choosing not to dedicate your time to something. Especially when the thing to be analysed relies on fundamentally incommensurable values.

FWIW, from actually reading his notes and the extracts of the spreadsheets he quickly dips into a number of flaky assumptions and uses them to apply "corrective biases" which make it very easy to dismiss without wasting time on arduous numerical analysis.

[Brian_K_White]

I think you couldn't have really given that comment much thought.

It takes no imagination at all to poke a hole in that.