The Science of Fabrication

The scientific community's barriers against “an epidemic of false, biased, and falisified findings” are weak, Daniele Fanelli, a research fellow at the University of Edinburgh, concedes at the onset of his column in Nature. “Only the most egregious cases of misconduct are discovered and punished,” he continues, while “subtler forms slip through the net, and there is no protection from publication bias.” Dr. Fanelli delineates the deficiencies of the present system with its overreliance on whistleblowers and proposes an alternative. One need not endorse his remedy, however, to concur with his judgment that researchers should be held accountable for what they write. Redefine Misconduct as Distorted Reporting

Data Driven

Our ability to amass droves of data drives certain assumptions. Among them, as David Brook notes in the New York Times, are these: that everything that can be measured should be; that data is a reliable, transparent lens that filters out ideology and emotions; and that data will enable us to foretell the future. In introducing what promises to be an informative, ongoing exploration of what he dubs “data-ism,” Brooks extols data's capacity to disabuse us of views that fly in the face of the evidence and to shed light on emerging and overlooked patterns of behavior. The Philosophy of Data