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The Right Question to Bring Down Susan Rice
Susan Rice admitted she lied. She requested unmaskings of Trump associates.
Rice says her unmasking requests were routine. Maybe they were.
We can find out. It’s simple data analysis. I’ll show you how. But, first, you have to know the right question to ask. And few people do.
Right Questions #
You hear a lot of talk about whether Susan Rice requested unmasking of Trump associates. That’s a good question, but it’s not enough. And almost everyone fails to ask the most important question.
I’ve written before about the question we fail to ask. It’s so simple. Ask for the instances you’re not interested in. Only then will you appreciate the ones you are interested in.
The question investigators need to ask is this: of all the unmaskings Rice requested, now many were Trump associates?
Here are two hypothetical charts. One shows only the instances Rice requested unmasking of Trump people. The other shows her requests for Trump and non-Trump unmaskings.
Now, let’s pretend we ask for all of Susan Rice’s requests for unmasking. And we overlay them with Trump unmaskings.
Now, we see that most of Rice’s unmasking requests involved Trump associates. If these were real data, that is. They’re not. This is just a hypothetical.
We also see that she became increasingly interested in Trump as the election drew closer. And we see that her interest in non-Trump unmaskings remained flat.
Watch the Trend Lines #
When we add trend lines, we get an even better picture of Rice’s obsession with Trump associates.
Again, this is all hypothetical because I don’t have access to the White House unmasking request logs. But the White House does. If Susan Rice’s requests for unmaskings disproportionately involved Trump people, we know she was politically motivated.
White House logs show every single unmasking request, when they came, and who requested them. Let’s hope Congressional investigators remember to ask this most important question. And, remember: sometimes the answer your looking for is in the data you’re not looking at.