This is true but fairly pedantic.

It would be more accurate to say the word predictions the model makes based on the input text will likely be closer to the ones that were made from the training data where people felt like their job was on the line than the ones that were made from the training data where people felt otherwise.

So while the model does not feel, it's predictions are definitely going to change as a result of this input.

Exactly, positive details are almost always better than negative ones.

If you've ever seen the "generate a burger without pickles" conversations, it's clear that including the keyword "pickle" is causing them to show up. If you try "a burger with only [set of toppings]," you'll get far better results.