 Various authors have tried to show that robustness-based reasoning plays an important role in judgments about data reliability in experimental biology. For example, Weber (1998b) argues that the coincidence of genetic maps of Drosophila produced by different mapping techniques provided an important argument for the fidelity of these maps in the 1930s. Culp (1995) argued that robustness provides a way out of a methodological conundrum know as “data-technique circles”, which is a more apt designation for Collins’ “experimenter’s regress”. According to Collins (1985), scientists must trust data on the grounds of their being produced by a reliable instrument, but they can only judge an instrument to be reliable on the basis of it’s producing the right kind of data. According to Culp (1995), robustness provides a way out of this circle. If the data obtained by independent methods agree, then this supports both the reliability of these data and of the instrument that produced these data. She attempts to demonstrate this on the example of different methods of DNA sequencing.