The word is black-and-white-ism. For instance:
Paul Berman’s chief problem as a thinker is black-and-white-ism, and this is a good example of his failure to make subtle distinctions.
Scientists are guilty of black-and-white-ism all the time: this statistic is wrong, that way of doing things is a mistake, and so on. John Tukey wrote about this tendency in a paper called Analyzing data: Sanctification or detective work? If you believe data analysis is sanctification, there are indeed right ways and wrong ways, as with any ritual. But if science is not a set of rituals, talking about right and wrong confuses graduate students — who begin to think science is a set of rituals — and restricts what you can do. After you say something is wrong, it is harder to do it.