Sorting Things Out: Classification and Its Consequences
By Geof Bowker, Susan Leigh Star. 1999
Subfields: Social Sciences & Humanities
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Social Sciences & Humanities
- Jan Mouritsen
- R. Stuart Geiger
- Aaron L Halfaker
- S. French
- Nigel Thrift
- Rob Kitchin
- Karl Bryant
- Roy D. Pea
Citations in the corpus
- Measurement and Fairness (2019, background): “Bowker and Star capture the notion that measurements create society through their discussion of classification in computational systems [9].”
- Large image datasets: A pyrrhic win for computer vision? (2020, background): “Finally, zooming out and taking a broad perspective allows us to see that the very practice of embarking on a classification, taxonomization, and labeling task endows the classifier with the power to decide what is a legitimate, normal, or correct way of being, acting, and behaving in the social wor”
- Garbage in, garbage out?: do machine learning application papers in social computing report where human-labeled training data comes from? (2019, neutral): “From a qualitative and Science & Technology Studies perspective, there is extensive work on the practices and implications of various regimes of measurement [7, 20, 32, 57].”
- On the genealogy of machine learning datasets: A critical history of ImageNet (2021, methodology): “…relationship between ML practitioners and the data infrastructure that supports their work can be characterized by a trajectory of naturalization (Bowker and Star, 2000, 294 – 295): as ML datasets become increasingly familiar and relied upon within daily routines, the contingencies of dataset…”
- Problematising intellectual capital research: ostensive versus performative IC (2006, methodology): “It is useful to compare IC to a boundary object, as defined by Bowker and Star (1999, p. 296)”
- Information, Divergence and Risk for Binary Experiments (2009, background): “, 2002; Carey et al., 2007; Wettschereck and Muller, 2001) — this is analogous to PDDL (Ghallab et al., 1998). There are also some limited higher level attempts such as ontologies (Soldatova and King, 2006) and general frameworks (Fayyad et al., 1996). Modelling frameworks: To solve a machine learni”
- Making gender identity disorder of childhood: Historical lessons for contemporary debates (2006, background): “... which GIDC became a psychiatric diagnosis has been seen alternately as the result of scientific progress and expert consensus (Zucker & Spitzer, 2005) or as a conspiracy to keep homosexuality under the purview of psychiatry (Bem, 1993; Burke, 1996; McCarthy, 2003; Moore, 2002; Morgan, 2001; Sedg”
- The Social and Technological Dimensions of Scaffolding and Related Theoretical Concepts for Learning, Education, and Human Activity (2004, background): “practices. Such empirical work in this vein, identified with work in the field of “science studies” (e.g., Bowker & Star, 1999; Galison, 1987, 1997; Knorr-Cetina, 1999; Latour & Woolgar, 1979/1986; Nersessian, 2004; Ochs & Jacoby, 1997; Rheinberger, 1997; Star, 1989), both challenge existing ideal”
- Digital education governance: data visualization, predictive analytics, and ‘real-time’ policy instruments (2016, unknown): “Building on a relational view of infrastructure from science and technology studies, Bowker and Star (1999) describe a dense infrastructural apparatus that consists of technical and social components.”
- Tackling Online Abuse: A Survey of Automated Abuse Detection Methods (2019, background): “the morals and values of their creators and annotators (Bowker and Star, 2000; Blackwell et al., 2017).”
- European energy poverty metrics: Scales, prospects and limits (2020, unknown): “Bowker and Star [30] show, for instance, that the meaning of categories in health policy has been changing historically; this involved not just different interpretations but also different infrastructures including shifts in metrology.”
- Studying Knowledge Management in Information Systems Resarch: Discourses and Theoretical Assumptions (2002, background): “…changing world (March 1991); while too little might result in chaotic social relations, too much implies the silencing of diverse perspectives (Bowker and Star 1999); and while too little might result in expensive mistakes (e.g., faulty new product), too much might result in unwanted…”