Laplace once argued that if one could “comprehend all the forces by which nature is animated,” it would be possible to predict the future and explain the past. The advent of analysis of large-scale data sets has been accompanied by newfound concerns about “Laplace’s Demon” as it relates to certain fields of science as well as management, evaluation, and audit. I begin by asking how statistical data are constructed, illustrating the hermeneutic acts necessary to create a variable. These include attributing a certain characteristic to a particular phenomenon, isolating the characteristic of interest, and assigning a value to it. In addition, a population must be identified and a sample must be “taken” from that population. Next, I examine how statistical analyses are conducted, examining the interpretive acts there as well. In each case, I show how big data add new challenges. I then show how statistics are incorporated into audits and evaluations, emphasizing how alternative interpretations are concealed in the audit process. I conclude by noting that these issues cannot be “resolved” as Laplace suggested. His Demon, already banished from physics, needs to be banished from other fields of science, management, audits, and evaluations as well.
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Kenneth Cukier;
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Big Data: A Revolution that Will Transform how We Live, Work, and Think
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Essay Review
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Review Essay: Corporate Capitalism and the Growing Power of Big Data
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Lyria Bennett Moses;
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Is Your Algorithm Dangerous?
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Big Data in the European Union
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Snapshot of Big Data Trends in Latin America
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Tien, James M.;
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Overview of Big Data: A US Perspective
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Huang, Guangyan;
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Leung, Clement;
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Smart Cities
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(2023)
Pensare per mappe. Ontologie per una pratica scientifica
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Gregory Rodriguez;
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Research Methodology in Mass Observation Past and Present: “Scientifically, about as Valuable as a Chimpanzee's Tea Party at the Zoo”?
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Users Gone Astray: Spreadsheet Charts, Junky Graphics, and Statistical Knowledge
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Philosophy of Systems Biology: Perspectives from Scientists and Philosophers
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How Our Days Became Numbered: Risk and the Rise of the Statistical Individual
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