ABSTRACT
While scholars of new public governance (NPG) frequently acknowledge the political character of governance and seek to place “substantive political values more firmly at the center of the governance debate” (Morgan et al. 2013, 121), many of them simultaneously urge an approach to the study of public governance and administration that is more deeply rooted in the methodology of mainstream social science. To use Mark Bevir’s words, despite differences in their approaches, these scholars of governance “generally share a continuing attachment to the idea that social science generates an expertise that is capable of informing public policy” (2010, 197). The reforms inspired by their theories, in Bevir’s view, “represent a quest for efficiency based on new forms of expertise” (177). Laurence Lynn, Carolyn Heinrich, and Carolyn Hill (2000), for example, have called for the application of social science to problems of governance so as to earn government “the respect of citizens who pay for, and whose lives are affected by, its programs and regulatory activities” (2000, 234). These authors see social science research as needed to address what they see as the “general issue of governance,” namely, how “public-sector regimes, agencies, programs, and activities [can] be organized and managed to achieve public purposes” (234). They argue for the development of a model or a “logic of governance,” which they take great pains to express in terms of a reduced-form mathematical equation. As they see it, such a “logic” would be helpful in addressing, among other things, how “goals such as efficiency or high reliability” can “be incorporated into an existing governance regime so as to promote its success,” how a governance regime can “be designed to insure priority in resource allocation and attention to particular goals and objectives,” and how “dispersed governance regimes (across states, across municipalities within a state, across local offices or networks)” can “be induced to converge on the achievement of particular policy objectives” (235–236). These authors express the hope that their science-based approach to governance will encourage other investigators to use what they term “appropriate theoretical and statistical models to specify and subsequently identify significant causal relationships that link governance and performance” (247).
