CAUSALIDAD Y COMPLEJIDAD
CAUSALIDAD Y COMPLEJIDAD
Topoi, April 2016 vol 36 issue 1
Disponible online: springer.com
Current research in molecular epidemiology uses biomarkers to model the different disease phases from environmental exposure, to early clinical changes, to development of disease. The hope is to get a better understanding of the causal impact of a number of pollutants and chemicals on several diseases, including cancer and allergies. In a recent paper Russo and Williamson (Med Stud, 2012) address the question of what evidential elements enter the conceptualisation and modelling stages of this type of biomarkers research. Recent research in causality has examined Ned Hall’s distinction between two concepts of causality: production and dependence (Hall in Causation and counterfactuals. MIT Press, Cambridge, pp 225–276, 2004). In another recent paper, Illari (Philos Technol, p 20, 2011b) examined the relatively under-explored production approach to causality, arguing that at least one job of an account of causal production is to illuminate our inferential practices concerning causal linking. Illari argued that an informational account solves existing problems with traditional accounts. This paper follows up this previous work by investigating the nature of the causal links established in biomarkers research. We argue that traditional accounts of productive causality are unable to provide a sensible account of the nature of the causal link in biomarkers research, while an informational account is very promising.