Reference : ‘A mechanistic interpretation, if possible’: How does predictive modelling causality ...
Scientific journals : Article
Social & behavioral sciences, psychology : Sociology & social sciences
‘A mechanistic interpretation, if possible’: How does predictive modelling causality affect the regulation of chemicals?
Thoreau, François mailto [Université de Liège > Département de philosophie > Philosophie morale et politique >]
Big Data & Society
Yes (verified by ORBi)
[en] Predictive modelling ; quantitative structure–activity relationship ; regulation
[en] The regulation of chemicals is undergoing drastic changes with the use of computational models to predict environmental toxicity. This particular issue has not attracted much attention, despite its major impacts on the regulation of chemicals. This raises the problem of causality at the crossroads between data and regulatory sciences, particularly in the case models known as quantitative structure–activity relationship models. This paper shows that models establish correlations and not scientific facts, and it engages anew the way regulators deal with uncertainties. It does so by exploring the tension and problems raised by the possibility of causal explanation afforded by quantitative structure–activity relationship models. It argues that the specificity of predictive modelling promotes rethinking of the regulation of chemicals.
Researchers ; Professionals

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