{'fraction_non_alphanumeric': 0.024585477415666093, 'fraction_numerical': 0.0, 'mean_word_length': 5.944444444444445, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
Appetite for Imprecision: The Role of Bureaucracy in Implementing a Pay-for-Performance Program

Pay-for-performance (PfP) conservation programs emphasize data and modeling to more cost-effectively target incentive payments. Geographers question the rationalist impulse to quantify and problematize the role of techno-science—models, metrics, accounting protocols, and standards—in performing economic rationalities. The critique of techno-science, however, directs empirical research toward the political economy of knowledge production with little consideration of the role of bureaucratic organization in performing calculations. In this article, I study the bureaucratic work in coordinating the largest agri-environmental PfP program in the United States—the Conservation Stewardship Program (CSP). Data for this article were collected in North Dakota, a top-five CSP recipient state. Through semistructured interviews and participant observation of bureaucratic encounters with farmers in localized offices, I found that the situated nature of the street-level bureaucracy placed it in a unique position to interpret, probe, undermine, and promote the PfP agenda. The article argues that data-driven technologies in the CSP were designed with a considerable appetite for imprecision. The appetite for imprecision reflects a structural problem conditioned by the interaction of economic rationality with the nature of technical innovation, administrative rationalities, and political opportunism. Given the momentum to expand data-driven technologies in conservation, the article calls on geographers to consider the dynamic and incomplete ways in which data are mobilized in practice and what efforts to be more transparent eventually conceal.