Sorting Things Out - Classification and Its Consequences

By Maiko Spiess. 2010

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The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Evaluation & Benchmarks

Citations in the corpus

Learning Transferable Visual Models From Natural Language Supervision (2021, background): “There are inherent problems with race and gender classifications, as e.g. Bowker & Star (2000) and Keyes (2018) have shown.”
Large image datasets: A pyrrhic win for computer vision? (2020, background): “…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 world [9].”
A Survey of Race, Racism, and Anti-Racism in NLP (2021, neutral): “(Bowker and Star, 2000).”
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.”
Tilting at Windmills? The Environmental Movement and the Emergence of the U.S. Wind Energy Sector (2009, background): “Commodity markets and information technologies are particularly prone to this type of collective forgetting (Bowker and Star, 2000).”
Tackling Online Abuse: A Survey of Automated Abuse Detection Methods (2019, background): “This points to a critical issue: automated systems embody the morals and values of their creators and annotators (Bowker and Star, 2000; Blackwell et al., 2017).”
Toward Information Infrastructure Studies: Ways of Knowing in a Networked Environment (2009, background): “The art and science of classification plays an underappreciated but recurring role in the organization of information (Bowker & Star, 1999; Epstein, 2007).”
Classification situations: Life-chances in the neoliberal era (2013, unknown): “…social-categorical differences ‘‘play out’’, are ‘‘expressed in’’, or ‘‘distort’’ institutions, we thus seek to identify, in a manner not unlike Bowker and Star (2000), how institutions systematically sort and slot people into new types of categories (which we may call ‘‘market categories’’)…”
A time‐based blended learning model (2011, background): “The current emphasis on blended learning in teaching and learning evolved it into what Susan Leigh Star terms a boundary object (Bowker & Star, 1999).”
Reliability and Inter-rater Reliability in Qualitative Research (2019, background): “systems that reproduce inequality, including the power assumptions embedded into the very concept of coding and labeling [12].”
A Framework for Deprecating Datasets: Standardizing Documentation, Identification, and Communication (2021, background): “Datasets necessarily represent a worldview, including how the data is collected, labelled and applied, and these particular representations and classiﬁcations of the world have social and political values embedded within them [15, 29].”
Counting Things and People: The Practices and Politics of Counting (2009, background): “Bowker and Star (1999) treat classification as a ubiquitous practical activity that orders the world in some ways while precluding others.”
Knowledge Collaboration in Online Communities (2011, background): “In social sciences, although boundaries divide and disintegrate collectives, they also coordinate and integrate social action (Bowker and Star 1999, Lamont and Molnár 2002).”
Revisiting Gendered Web Forms: An Evaluation of Gender Inputs with (Non-)Binary People (2021, background): “Forms are just the user-facing component of a broad gendered ecosystem that extends into platform databases, data standards, infrastructures, policy, and even law [69].”
Critical Race Theory for HCI (2020, background): “History shows that racial categories are ﬂuid [16]).”
Algorithmic realism: expanding the boundaries of algorithmic thought (2020, background): “sites of political and social struggles” with “brutal consequences” for those being classi ed [15].”
Artsheets for Art Datasets (2021, background): “…aware that, from antiquity to the present, the activity of collecting has often been inextricable from projects that are imperialist, oppressive, or fractious, and which reinforce the position of so-called superior groups that extract art and artefacts from marginalized people [50, 51, 52, 53, 54].”
The real-time city? Big data and smart urbanism (2013, background): “Data do not exist independently of the ideas, techniques, technologies, people and contexts that conceive, produce, process, manage, analyze and store them (Bowker and Star 1999; Lauriault 2012; Ribes and Jackson 2013).”