Tim Walz has taken on a leveled-up approach in a race to the finish of the 2024 election, after a more cautious and buttoned-up start as Kamala Harris’ running mate.
In the weeks following the vice presidential debate, Democratic vice presidential nominee Tim Walz has been sounding more like the aggressive campaigner who got the role than the buttoned-up figure he’s cut since joining the ticket.
Dressed in khakis and a navy Harris-Walz sweatshirt Monday, Walz delivered some of his sharpest attacks yet against former President Donald Trump. Walz appeared more natural in his latest appearances on the trail, including in his signature flannel in rural Pennsylvania, after shedding the blue sport coat and white collared shirt he’s favored for the last few months.
He’s also getting back on the TV circuit, with appearances coming up on “The View” and “The Daily Show,” according to a campaign official, after Walz went viral pre-running mate selection with his labeling of the GOP ticket as “weird” in a cable news interview.
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Did you open the paper and read it? The hypothesis are very simple.
They need to be set up with two parts, the first a predicate, then the second part is a couple options…
So for example a hypothesis can be set up in two parts as follows:
Part A:
“The author of this comment { } about a border wall”
Part B:
[“thinks negatively” | “thinks positively” “is neutral”]
The options are intended to fill in the gap in the curly braces.
The model will give a probabilistic ranking of the three options, so you need to think carefully about how you set up your hypothesis.
Like I said drop them here or dm me and I can run them once I’ve scrapped UMs comments.
[Edit: I’ve got UM’s comments, and I’ve saved them to disk. Let me know if you’ve got your questions ready, or if you still need help understanding how to set up a hypothesis]
[Addendum] @[email protected]
I’m going to give you a worked example.
This is on UM’s most recent comment:
So I set up the predicate:
‘The author of this post {} Joe Biden.’
with the options:
[‘supports’, ‘opposes’, ‘is not talking about’]
and we get the result:
{‘sequence’: ‘She was on my ballot, so she is a candidate. I don’t know how to explain this any better.’,
‘labels’: [‘is not talking about’, ‘supports’, ‘opposes’],
‘scores’: [0.9906510710716248, 0.008063388988375664, 0.0012855551904067397]}
So this comment we would score as “not talking about Joe Biden”. Anything you can think of that can fit within that framework. I dont know UM, but you seem to, so you probably know what would be interesting to ask.