The conundrum of police officer-involved homicides: Counter-data in Los Angeles County

Currie, Morgan; Paris, Britt; Pasquetto, Irene V.; Pierre, Jennifer

doi:10.1177/2053951716663566

Cited by 46 publications

(54 citation statements)

References 14 publications

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“…Perhaps the most vulnerable, minority and lower socioeconomic status subjects are affected by Big Data science in often invisible and unforeseen ways. Currie et al (2016) provide an example of such a case in their analysis of four datasets containing police officer-involved homicide statistics in Los Angeles. Their paper frames ''police officer-involved homicide data as a rhetorical tool that can reify certain assumptions about the world and extend regimes of power'' (1).…”

Section: Cds Workmentioning

confidence: 99%

Critical data studies: An introduction

2016

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Critical Data Studies (CDS) explore the unique cultural, ethical, and critical challenges posed by Big Data. Rather than treat Big Data as only scientifically empirical and therefore largely neutral phenomena, CDS advocates the view that Big Data should be seen as always-already constituted within wider data assemblages. Assemblages is a concept that helps capture the multitude of ways that already-composed data structures inflect and interact with society, its organization and functioning, and the resulting impact on individuals' daily lives. CDS questions the many assumptions about Big Data that permeate contemporary literature on information and society by locating instances where Big Data may be naively taken to denote objective and transparent informational entities. In this introduction to the Big Data & Society CDS special theme, we briefly describe CDS work, its orientations, and principles.

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Section: Cds Workmentioning

confidence: 99%

Critical data studies: An introduction

2016

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“…. 20 We [also] generate our leads organically [online…], then there are leads that we get from syndication that we bid on. [...] Different pieces of information [are] appended to those leads depending on where […they come] from.…”

Section: Ray (Business Analyst): "How This Business Work […] Is Verymentioning

confidence: 99%

“…Before this, he had 7+ years of work experience in technology industry in roles such as engineering manager and senior engineer. 20 The affiliates consist of third-party lending agencies and business associates. are evaluating from month to month whether they would renew their product with us, if we had sent them a bunch from bucket B, and none from A, they are likely to churn.…”

Section: Ray (Business Analyst): "How This Business Work […] Is Verymentioning

confidence: 99%

“…Data science tools and techniques constitute an increasingly common and complex feature of contemporary work settings, impacting modes of knowledge and governance [27,66,67], shaping organizational practices [15,52,99], reconfiguring publics [20,50,56], and simultaneously enabling and constraining the possibilities of human action and agency [9,10,74]. 1 But the limits and tensions of data science work in its collaborative dimensions are not yet fully scoped.…”

Section: Introductionmentioning

confidence: 99%

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Trust in Data Science

Passi

Jackson

2018

Proc. ACM Hum.-Comput. Interact.

134

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The trustworthiness of data science systems in applied and real-world settings emerges from the resolution of specific tensions through situated, pragmatic, and ongoing forms of work. Drawing on research in CSCW, critical data studies, and history and sociology of science, and six months of immersive ethnographic fieldwork with a corporate data science team, we describe four common tensions in applied data science work: (un)equivocal numbers, (counter)intuitive knowledge, (in)credible data, and (in)scrutable models. We show how organizational actors establish and re-negotiate trust under messy and uncertain analytic conditions through practices of skepticism, assessment, and credibility. Highlighting the collaborative and heterogeneous nature of real-world data science, we show how the management of trust in applied corporate data science settings depends not only on pre-processing and quantification, but also on negotiation and translation. We conclude by discussing the implications of our findings for data science research and practice, both within and beyond CSCW.

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“…Building on these critiques, some seek not only to analyze and problematize but also to utilize data science sources and methods in unorthodox ways to help realize new social relations. Fortun et al (), Gabrys (), Currie et al (), and Brucato () describe the use of data by data designers, citizens, and community members in environmental and police brutality initiatives. Singer () and Gradecki and Curry () directly employ data tools in their art to call out government and corporate surveillance to their audiences.…”

Section: Data Science Ascendantmentioning

confidence: 99%

Counter‐mapping data science

Dalton¹,

Stallmann

2017

Canadian Geographies / Géographies canadiennes

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Key MessagesCounter-mapping offers a useful theoretical framework and practical methods for developing grassroots data science not focused on profit.Counter-mapping is inherently a situated combination of ideas and practices for developing and realizing alternative social relations and worlds.Counter-mapping requires careful sensitivity to each situation and associated power relations, especially by the map-maker(s) themselves.Counter-mapping is a combination of critical ideas and practices for social change that offers a productive and promising approach for grassroots data science initiatives. Current information technologies collect, store, and analyze data with new degrees of size, speed, heterogeneity, and detail. While much work utilizing data science technologies is dedicated to generating profit or to national security, some data science projects explicitly attempt to facilitate new social relations, though with inconsistent results and consequences. This paper reviews counter-mapping's particular combination of theory and practice as a potential point of reference for such initiatives. Counter-mapping takes the tools of institutional map-making at government agencies and corporations and applies them in situated, bottom-up ways. Moreover, counter-mapping's multiple theoretical approaches and polyglot practices offer a variety of inspirations and avenues for future work in identifying and realizing alternative, ideally better, possibilities. This paper defines counter-mapping; outlines its multiple theorizations; briefly describes three relevant case studies, The Detroit Geographical Expedition and Institute, Mapping Police Violence, and the Counter-Cartographies Collective; and concludes with a few hard-learned considerations from counter-mapping that are directly pertinent for data-oriented projects focused on change.

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The conundrum of police officer-involved homicides: Counter-data in Los Angeles County

Cited by 46 publications

References 14 publications

Critical data studies: An introduction

Critical data studies: An introduction

Trust in Data Science

Counter‐mapping data science

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