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Causality put to the test of the big data movement: a communicational approach

Abstract : The discourses contributing of the Big Data movement suggests that the increasing volume of data and computing capacity would ultimately allow to arise new causalities. However, statistics, according to Breiman (2001), are based on two types of strategies: the "strategy to understand" and the "strategy to predict". The strategy for understanding is part of the register of causality and supposes to be constructed from protocolized data. On the other hand, strategies for forecasting do not seek to make a explanatory model but to offer predictions, probable facts and rely on the volume of data. This communication, in a communicational approach, aims to question the big data discourses, based on the study of the fabric of data in cancer registries.
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Submitted on : Thursday, September 23, 2021 - 9:58:52 AM
Last modification on : Monday, July 4, 2022 - 9:48:35 AM


  • HAL Id : hal-03352315, version 1


Anja Martin-Scholz, Nicolas Savy, Anne Mayère, François Lambotte. Causality put to the test of the big data movement: a communicational approach. Journées du club SMAC – Statistics, Philosophy and Health, Jun 2021, Toulouse, France. ⟨hal-03352315⟩



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