In Andrew Maul's focus paper "Rethinking Traditional Methods of Survey Validation'" published in this issue of "Measurement: Interdisciplinary Research and Perspectives," Maul contends that self-report measures may be particularly difficult to validate. He cautions that such techniques may fall short of providing the kinds of rigorous tests of relevant hypotheses commonly expected in scientific research, and argues that traditional methods for the construction and validation of self-report survey-based assessments of psychological attributes are urgently in need of rethinking. In this commentary, Brent Duckor begins his comments by stating that it is tempting to see Maul's argument as one of a philosopher-critic, hovering between a transcendent and immanent critique of social science. Maul seems to be saying without overstating the case to his colleagues: noncognitive "measures" that rely on Likert scales are meaningless, in part, because the constructs are ill-defined and the item formats are not aligned with substantive, independent theory. Duckor, notes that the profession should be grateful that the non cognitive research methods Maul exposes in his study have alerted the profession to the potential misuse of such data and the need for a more serious approach to validation as an on-going, use-driven process. [For "Rethinking Traditional Methods of Survey Validation," see EJ1156001.]