13 pages, via Online Journal, This paper contributes to our understanding of farm data value chains with assistance from 54 semi-structured interviews and field notes from participant observations. Methodologically, it includes individuals, such as farmers, who hold well-known positionalities within digital agriculture spaces—platforms that include precision farming techniques, farm equipment built on machine learning architecture and algorithms, and robotics—while also including less visible elements and practices. The actors interviewed and materialities and performances observed thus came from spaces and places inhabited by, for example, farmers, crop scientists, statisticians, programmers, and senior leadership in firms located in the U.S. and Canada. The stability of “the” artifacts followed for this project proved challenging, which led to me rethinking how to approach the subject conceptually. The paper is animated by a posthumanist commitment, drawing heavily from assemblage thinking and critical data scholarship coming out of Science and Technology Studies. The argument’s understanding of “chains” therefore lies on an alternative conceptual plane relative to most commodity chain scholarship. To speak of a data value chain is to foreground an orchestrating set of relations among humans, non-humans, products, spaces, places, and practices. The paper’s principle contribution involves interrogating lock-in tendencies at different “points” along the digital farm platform assemblage while pushing for a varied understanding of governance depending on the roles of the actors and actants involved.
9 pages., Via online journal., Food labels legislated by the U.S. government have been designed to provide information to consumers. It has been asserted that the simple disclosures “produced using genetic engineering” on newly legislated U.S. food labels will send a signal that influences individual preferences rather than providing information. Vermont is the only US state to have experienced mandatory labeling of foods produced using genetic engineering (GE) via simple disclosures. Using a representative sample of adults who experienced Vermont’s mandatory GE labeling policy, we examined whether GE labels were seen by consumers and whether the labels provided information or influenced preferences. Nearly one-third of respondents reported seeing a label. Higher income, younger consumers who search for information about GE were more likely to report seeing a label. We also estimated whether labels served as information cues that helped reveal consumer preferences through purchases, or whether labels served as a signal that influenced preferences and purchases. For 50.5% of consumers who saw a label, the label served as an information cue that revealed their preferences. For 13% of those who saw the label, the label influenced preferences and behavior. Overall, for 4% of the total sample, simple GE disclosures influenced preferences. For a slight majority of consumers who used a GE label, simple disclosures were an information signal and not a preference signal. Searching for GE information, classifying as female, older age and opposing GE in food production significantly increased the probability that GE labels served as an information source. Providing such disclosures to consumers may be the least complex and most transparent option for mandatory GE labeling.
