Second, Wright traces the allure of “model-free” methods to their objectivity. This has indeed been a holy grail for statisticians since day one—or since March 15, 1834, when the Statistical Society of London was founded. Its founding charter said that data were to receive priority in all cases over opinions and interpretations. Data are objective; opinions are subjective. This paradigm long predates Pearson. The struggle for objectivity—the idea of reasoning exclusively from data and experiment—has been part of the way that science has defined itself ever since Galileo.
This is the subject-object duality Pirsig denounces in Zen and Motorcycle Maintenence. It's the same thing Hume and Kant were arguing over. I agree, there is no such thing as separation of subject and object. Our minds were moulded by evolution to understand and comprehend the universe; it thus follows our minds might have a thing or two to say after a few billion years of experience. The universe is so complicated I think it requires a point of view; or it requires an angle through which to perceive. So I think that it is actually the opposite of this; pure data is almost pure subjectivity; there are so many ways to interpret it; one needs to use other information to constrain that interpretation.
