The Cult of Statistical Significance: How the Standard Error Costs Us Jobs, Justice, and Lives, by Deirdre McCloskey and Stephen Ziliak, University of Michigan Press, argues that statistical significance in its all too common meaning, philosophical possibilities uncalibrated to the sizes of important effects in the world, is useless for science.
"Yet in medical science, in population biology, in much of sociology, political sciences, psychology, and economics, in parts of literary study, there reigns the spirit of the Mathematics or Philosophy Departments (appropriate in their own fields of absolutes). The result has been a catastrophe for such sciences, or former sciences. The solution is simple: get back to seeking oomph. It would be wrong, of course, to abandon math or statistics. But they need every time to be put into a context of How Much, as they are in chemistry, in most biology, in history, and in engineering science.
"In many of the life and human sciences the existence/whether question of the philosophical disciplines has substituted for the size-matters/how-much question of the scientific disciplines. The substitution is causing a loss of jobs, justice, profits, environment, and even life. The substitution we are worrying about here is called "statistical significance"—a qualitative, philosophical rule which has substituted for a quantitative, scientific magnitude."
I think this results from "scientism" -- from people in the social sciences and humanities, and in politics and the media, wishing to SOUND scientific and as a result failing to BE scientific, putting way too much stock in scientific terms they don't actually understand.
I know and admire Prof. McCloskey from her inspiring, interdisciplinary teaching at an Institute for Humane Studies seminar on "Liberty in Film and Fiction", a life-changing experience I'd recommend to any student.