These are particulars to the examples she provided. The unifying idea is that people often choose models or data based on self interest, even at the expense of accuracy. When discussing the cause of an event, it's not enough to say "a bad model is to blame" or "bad data is to blame." At this point, the model or data are instruments serving the self interest of the modeller, and they are incidental in the cause and effect relationship.