| This thesis develops a novel strategy for evaluating the state of scientific contestation on issues. The analysis rests on Latour's black box imagery, here observed in scientific citation networks, and models it with a community detection network algorithm borrowed from Physics. As consensus forms, the importance of internal divisions to the overall network structure declines. The strategy is validated against cases were historiography reports when consensus was formed, such as the carcinogenicity of smoking and anthropogenic climate change. Then, the same analysis is employed to currently contested cases: the suspected carcinogenicity of cellular phones, the relationship of minimum wages and unemployment, and the relationship between vaccines and autism. Extracting meaning from the internal structure of scientific knowledge carves a niche for renewed sociological commentary on science, which allows comparative research in an unprecedented scale and focus. Such comparative analysis reveals a typology of three trajectories scientific propositions may experience en route to consensus. |
