other studies that directly examined farm-level social change revealed that, despite the presumption of scale-neutrality, it was difficult to isolate the impacts of biological innovations from those of other technological innovations in agriculture because biological innovations were often developed and disseminated in conjunction with other technologies that may not have been scale-neutral (Kloppenburg, 1984).
Additional research conducted on the social impacts of biotechnology in animal agriculture, specifically on the use of BST, noted that rates of adoption of BST were moderate and that, although adoption did not require large herds, scale effects were observed because BST use was more effective in high-producing cows, which were more likely to be found in large herds with complementary feeding technologies (Barham et al., 2004). Beck and Gong (1994) also observed the existence of a scale effect with adoption of BST, with adopters more likely to have larger herds, as well as being younger and having more formal education. Additionally, it was suggested that the quality of farm management had an impact on the benefits accruing to the adoption of BST (Bauman, 1992). The use of BST also was thought to lead to lower prices and thus to result in increased economic pressure on smaller producers (Marion and Wills, 1990). In other words, the body of research on the socioeconomic consequences of the use of biotechnologies, including Green Revolution technologies, indicated that “scale neutrality is not inevitable, but a possibility that depends on institutional context” (DuPuis and Geisler, 1988: 410). To put it another way, the social context of the adoption process and the impacts on that context are interconnected, from which it follows that the social impacts of genetic-engineering technology on farms and communities differ among cultures, commodities, and historical periods.
Thus, though seed varieties are generally conceptualized as being scale-neutral, the adoption of any technology may be biased toward large firms that can spread the fixed costs of learning over greater quantities of production (Caswell et al., 1994). In developing countries, the economics of genetic-engineering technology do not appear to vary with farm size (Thirtle et al., 2003). However, scale may affect accessibility to technology. Small farmers have less influence in input supply and marketing chains with which to secure access to desired technologies. Thus, there can be a scale bias in the development and dissemination processes associated with herbicide-resistance technology that puts small farmers at a disadvantage. In contrast, as noted in Chapter 3, insect-resistance technology can replace insecticide applications that require fixed capital investments, such as for tractors and sprayers. In this regard genetic-engineering technology has the potential to favor small farmers, who would benefit more from a technology that required less fixed capital investment. The scale effects of transgenic varieties may also depend on the pricing (such as quantity