Thinking through Data: How Outliers, Aggregates, and Patterns Shape Perception.

The article reviews *Thinking through Data: How Outliers, Aggregates, and Patterns Shape Perception* by Maja Bak Herrie, which explores the aesthetic and social dimensions of key statistical concepts—outliers, aggregates, and patterns—in data visualization. Herrie introduces the concept of the "digi...

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Detalles Bibliográficos
Publicado en:Contemporary Sociology Vol. 55; no. 3; pp. 244 - 247
Autor principal: Sloane, Mona
Formato: Product Review
Publicado: Sage Publications Inc. May2026
Materias:
Acceso en línea:Ver este registro en EBSCOhost
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      dt: May2026
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        atl: Thinking through Data: How Outliers, Aggregates, and Patterns Shape Perception.
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        au: Sloane, Mona
        affil: University of Virginia
      su:
        Sociology
        Theory of knowledge
        Outliers (Statistics)
        Data visualization
        Statistical measurement
        Pattern perception
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        subj:
          Sociology
          Theory of knowledge
          Outliers (Statistics)
          Data visualization
          Statistical measurement
          Pattern perception
      ab: The article reviews *Thinking through Data: How Outliers, Aggregates, and Patterns Shape Perception* by Maja Bak Herrie, which explores the aesthetic and social dimensions of key statistical concepts—outliers, aggregates, and patterns—in data visualization. Herrie introduces the concept of the "digital object" to analyze how these statistical entities function as both knowledge products and mediators of social meaning, drawing on contemporary art projects to illustrate these dynamics. The book situates statistical operations within the framework of Kulturtechnik, a cultural technique that shapes perception and knowledge production beyond mere technical processes. While the work contributes to sociological discussions on data and mediation, the review notes that Herrie’s treatment of aesthetics remains underdeveloped, limiting deeper engagement with the political and epistemological stakes of data visualization in algorithmic contexts.
      pubtype: Academic Journal
      doctype: Product Review
      src: R
    language: English
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