skip to main content
10.1145/2702123.2702298acmconferencesArticle/Chapter ViewAbstractPublication PageschiConference Proceedingsconference-collections
research-article

The Politics of Measurement and Action

Authors Info & Claims
Published:18 April 2015Publication History

ABSTRACT

Contemporary decisions about the management of populations, public services, security, and the environment are increasingly made through knowledge gleaned from "big data" and its attendant infrastructures and algorithms. Though often described as "raw," this data is produced by techniques of measurement that are imbued with judgments and values that dictate what is counted and what is not, what is considered the best unit of measurement, and how different things are grouped together and "made" into a measureable entity. In this paper, we analyze these politics of measurement and how they relate to action through two case studies involving high stake public health measurements where experts intentionally leverage measurement to change definitions of harm and health. That is, they use measurement for activism. The case studies offer a framework for thinking about of how the politics of measurement are present in user interfaces. It is usually assumed that the human element has been scrubbed from the database and that significant political and subjective interventions come from the analysis or use of data after the fact. Instead, we argue that human-computer interactions start before the data reaches the computer because various measurement interfaces are the invisible premise of data and databases, and these measurements are political.

References

  1. Agre, P.E. (1994) Surveillance and capture: two models of privacy.? The Information Society, 10, 101--127.Google ScholarGoogle ScholarCross RefCross Ref
  2. Agre, Philip E. (1994). Accountability and Discipline: A Comment on Suchman and Winograd. Computer Supported Cooperative Work, 3(1), 31--35. Google ScholarGoogle ScholarDigital LibraryDigital Library
  3. Barocas, S., Hood, S., & Ziewitz, M. (2013). Governing algorithms: a provocation piece. SSRN Electronic Journal.Google ScholarGoogle Scholar
  4. Bjørn, P., & Balka, E. (2007). Health Care Categories Have Politics Too: Unpacking the Managerial Agendas of Electronic Triage Systems. ECSCW '07.Google ScholarGoogle Scholar
  5. Bowker, G.C. (2000). "Biodiversity Datadiversity." Social Studies of Science, 30, 643--683.Google ScholarGoogle ScholarCross RefCross Ref
  6. Bowker, G.C. (2008). Memory Practices in the Sciences. Cambridge: The MIT Press.Google ScholarGoogle Scholar
  7. Bowker, G. C., & Star, S. L. (1999). Sorting Things Out: Classification and Its Consequences. Cambridge: MIT press. Google ScholarGoogle ScholarDigital LibraryDigital Library
  8. Boyd, D., & Crawford, C. (2012). Critical questions for big data. Information, Communication & Society 15 (5), 662--79.Google ScholarGoogle ScholarCross RefCross Ref
  9. Callaghan, W.M., Creanga, A.A., & Kuklina, E.V. (2012). Severe maternal morbidity among delivery and postpartum hospitalizations in the USA. Obstetrics and Gynecology, 120(5), 1029--36.Google ScholarGoogle ScholarCross RefCross Ref
  10. Callon, M. (2007). What does it mean to say economics is performative? In MacKenzie, D. A., Muniesa, F., & Siu, L. (Eds.). Do economists make markets?: on the performativity of economics. Princeton: Princeton University Press.Google ScholarGoogle Scholar
  11. Callon, M., & Law, J. (2005). "On Qualculation, Agency, and Otherness." Environment and Planning D: Society and Space 23(5), 717--33.Google ScholarGoogle ScholarCross RefCross Ref
  12. Canguilhem, Georges. (1991). The Normal and the Pathological. Cambridge: MIT Press.Google ScholarGoogle Scholar
  13. Cardon, D. (2013). Présentation. Dossier Politique Des Algorithmes, Réseaux 177(1), 9--21.Google ScholarGoogle Scholar
  14. Centers for Disease Control. Severe Maternal Morbidity in the USA - Maternal and Infant Health Reproductive Health. Accessed September 19, 2014. http://www.cdc.gov/reproductivehealth/MaternalInfantH ealth/SevereMaternalMorbidity.html.Google ScholarGoogle Scholar
  15. Deneux-Tharaux, C., Carmona, E., Bouvier-Colle, M.E., & Bréart, G. (2006). Postpartum Maternal Mortality and Cesarean Delivery. Obstetrics and Gynecology 108(3), 541--48.Google ScholarGoogle ScholarCross RefCross Ref
  16. Dourish, P. (In Press). "NoSQL: the shifting materialities of database technology." Computational Culture.Google ScholarGoogle Scholar
  17. Desrosières, A. (2002). The Politics of Large Numbers: A History of Statistical Reasoning. Cambridge: Harvard University Press.Google ScholarGoogle Scholar
  18. Douglas, M. (1986). How Institutions Think. Syracuse: Syracuse University Press, 1986.Google ScholarGoogle Scholar
  19. Foucault, M. Power/Knowledge: Selected Interviews and Other Writings, 1972--1977. 1st American Ed edition. New York: Vintage, 1980.Google ScholarGoogle Scholar
  20. Frankland, E. (1880). Water Analysis for Sanitary Purposes. N.p.Google ScholarGoogle Scholar
  21. Frankland, E. (1877). Experimental Researches in Pure, Applied and Physical Chemistry. J. Van Voorst.Google ScholarGoogle Scholar
  22. Frankland, E., and Royal Institution of Great Britain. (1867). On the Water Supply of the Metropolis. N.p.Google ScholarGoogle Scholar
  23. Gaskin, I.M. (2008). Maternal death in the USA: a problem solved or a problem ignored? The Journal of Perinatal Education 17(2), 9--13.Google ScholarGoogle ScholarCross RefCross Ref
  24. Gitelman, L. (2013). Raw Data Is an Oxymoron. Boston: MIT Press.Google ScholarGoogle ScholarCross RefCross Ref
  25. Hacking, I. (1990). The Taming of Chance. 1st edition. Cambridge England?; New York: Cambridge University Press.Google ScholarGoogle ScholarCross RefCross Ref
  26. Hacking, I. (1991). The making and molding of child abuse. Critical Inquiry, 253--288.Google ScholarGoogle Scholar
  27. Hacking, I. (1999). The Social Construction of What? Cambridge: Harvard University Press.Google ScholarGoogle Scholar
  28. Hamlin, C. (1990) Edward Frankland: The Analyst as Activist. Berkeley: University of California Press.Google ScholarGoogle Scholar
  29. Hamlin, C. (1990). A Science of Impurity: Water Analysis in Nineteenth Century Britain. Berkeley: University of California Press.Google ScholarGoogle Scholar
  30. Haraway, D.J. (1989). Primate Visions: Gender, Race, and Nature in the World of Modern Science. Psychology Press.Google ScholarGoogle Scholar
  31. Irani, L., Vertesi, J., Dourish, P., Philip, K., & Grinter, R. E. (2010). Postcolonial computing: a lens on design and development. In Proc. SIGCHI 2010, 1311--1320. Google ScholarGoogle ScholarDigital LibraryDigital Library
  32. Irwin, S., & Jordan, B. (1987). Knowledge, practice, and power: court-ordered cesarean sections. Medical Anthropology Quarterly 1(3), 319--34.Google ScholarGoogle ScholarCross RefCross Ref
  33. Karasti, H., Baker, K.S., & Halkola, E. (2006). Enriching the notion of data curation in E-Science: data managing and information infrastructuring in the Long Term Ecological Research (LTER) Network.? Computer Supported Cooperative Work, 15(4), 321--58. Google ScholarGoogle ScholarDigital LibraryDigital Library
  34. Kleinman, D.L. & Suryanarayanan, S. (2013). Dying bees and the social production of ignorance. Science, Technology & Human Values 38(4), 492--517.Google ScholarGoogle ScholarCross RefCross Ref
  35. Kuklina, E.V., Whiteman, M.K., Hillis, S.D., Jamieson, D.J., Meikle, S.F., Posner, S.F., & Marchbanks, P.A. (2008). An enhanced method for identifying obstetric deliveries: implications for estimating maternal morbidity. Maternal and Child Health Journal 12(4), 469--77.Google ScholarGoogle ScholarCross RefCross Ref
  36. Larrick, R.P., & Soll, J.B. (2008). The MPG illusion. Science, 320, 1593--1594.Google ScholarGoogle ScholarCross RefCross Ref
  37. Liboiron, M. (2012). Terrible and charismatic waste. Peabody Museum of Archaeology & Ethnology.Google ScholarGoogle Scholar
  38. Liboiron, M. (2013). Plasticizers: a twenty-first-century miasma. In Accumulation: The Material Politics of Plastic, 2013.Google ScholarGoogle Scholar
  39. Liboiron, M. (2015). Disaster data, data activism: grassroots Responses to Representing Hurricane Sandy, in Extreme Weather and Global Media, Eds. Julia Leyda and Diane Negra, Routledge.Google ScholarGoogle Scholar
  40. MacKenzie, D. (2006). Is economics performative? Option theory and the construction of derivatives markets. Journal of the History of Economic Thought, 28(1), 29--55.Google ScholarGoogle ScholarCross RefCross Ref
  41. Morrison, M. (2009). Models, measurement and computer simulation: the changing face of experimentation. Philosophical Studies 143, 33--57.Google ScholarGoogle ScholarCross RefCross Ref
  42. Moser, I., & Law, J. (2006). Fluids or flows? Information and qualculation in medical practice. Information Technology & People, 19(1), 55--73.Google ScholarGoogle ScholarCross RefCross Ref
  43. Mudry, J.J. (2009). Measured Meals: Nutrition in America. SUNY Press.Google ScholarGoogle Scholar
  44. Nagel, E. (1931). On the Logic of Measurement. Thesis (PH.D.) Columbia University, Source: American Doctoral Dissertations,.Google ScholarGoogle Scholar
  45. Orlikowski, W. J., & Scott, S. V. (2013). Knowledge eclipse: producing sociomaterial reconfigurations in the hospitality sector. In: Tsoukas, H., Nicolini, D. and Carlisle, P., (eds.) How Matter Matters: Objects, Artifacts, and Materiality in Organization Studies. Oxford: Oxford University Press.Google ScholarGoogle ScholarCross RefCross Ref
  46. Pasquale, F. (2013). The emperor's new codes: reputation and search algorithms in the finance sector. Governing Algorithms Conference, May 16, 2013.Google ScholarGoogle Scholar
  47. Pine, K. (2012). Fragmentation and choreography: caring for a patient and a chart during childbirth. Proc. CSCW 2012, 887--896. Google ScholarGoogle ScholarDigital LibraryDigital Library
  48. Pine, K.H., & Mazmanian, M. Institutional logics of the EMR and the problem of "perfect" but inaccurate accounts. Proc CSCW, 283--294. Google ScholarGoogle ScholarDigital LibraryDigital Library
  49. Pine, K.H., Wolf, C.T., & Mazmanian, M.. The Work of Re-use: Quality Measurement in Healthcare Organizations. CSCW '14 Workshop: Sharing, Re-Use and Circulation of Resources in Cooperative Scientific Work.Google ScholarGoogle Scholar
  50. Potts, J. (2009). A history of charisma. Basingstoke, UK: Palgrave Macmillan.Google ScholarGoogle ScholarCross RefCross Ref
  51. Porter, T.M. (1996). Trust in Numbers: The Pursuit of Objectivity in Science and Public Life. Princeton: Princeton University Press.Google ScholarGoogle ScholarCross RefCross Ref
  52. Proctor, R., & Schiebinger, L.L. (2008). Agnotology: The Making and Unmaking of Ignorance. Palo Alto: Stanford University Press.Google ScholarGoogle Scholar
  53. Ribes, D., & Jackson, S.J. (2013). Data bite man: the work of sustaining a long-term study. In "Raw Data" Is an Oxymoron, 147--66. Cambridge: MIT Press.Google ScholarGoogle Scholar
  54. Richards, T. (1993). The Imperial Archive: Knowledge and the Fantasy of Empire. Verso.Google ScholarGoogle Scholar
  55. Rittel, H.W.J., & Webber, M.M. (1973). Dilemmas in a general theory of planning. Policy Sciences, 4, 155--69.Google ScholarGoogle ScholarCross RefCross Ref
  56. Robertson, M. (2012). Measurement and alienation: making a world of ecosystem services. Transactions of the Institute of British Geographers 37, 386--401.Google ScholarGoogle ScholarCross RefCross Ref
  57. Scott, J.C. (1998). Seeing Like a State: How Certain Schemes to Improve the Human Condition Have Failed. Yale University Press.Google ScholarGoogle Scholar
  58. Scott, J. (1994). Power: Critical Concepts. Taylor & Francis.Google ScholarGoogle Scholar
  59. Smolan, R. (2012). The Human Face of Big Data. Sausalito: Against All Odds Productions.Google ScholarGoogle Scholar
  60. Steiner, C., & Dixon, W. (2012). Automate This: How Algorithms Came to Rule Our World. New York: Portfolio/Penguin.Google ScholarGoogle Scholar
  61. Suchman, Lucy. (1993). "Do Categories Have Politics"? Computer Supported Cooperative Work, 2(3), 177--190.Google ScholarGoogle ScholarCross RefCross Ref
  62. Thrift, N. (2004). Movement-Space: the changing domain of thinking resulting from the development. Economy and Society 33(4), 582--604.Google ScholarGoogle ScholarCross RefCross Ref
  63. "A Healthy Nation Timeline." UK National Archives, n.d. http://www.nationalarchives.gov.uk/education/victorian britain/healthy/timeline2.htm.Google ScholarGoogle Scholar
  64. Vertesi, J. (2011). Transnational, never neutral: regulatory politics and the deployment of technological systems, workshop paper for Transnational HCI workshop at CHI 2011, Vancouver, BC, Canada.Google ScholarGoogle Scholar
  65. Winner, L. (1986): 'Do Artifacts have Politics?' In L. Winner (ed.): The Whale and The Reactor: A Search for Limites in an age of High Technology, University of Chicaga Press, Chicago, 1986, pp. 28--40.Google ScholarGoogle Scholar
  66. World Health Organization. Maternal Mortality Accessed September 19, 2014. http://www.who.int/mediacentre/factsheets/fs348/en/..Google ScholarGoogle Scholar

Index Terms

  1. The Politics of Measurement and Action

    Recommendations

    Comments

    Login options

    Check if you have access through your login credentials or your institution to get full access on this article.

    Sign in
    • Published in

      cover image ACM Conferences
      CHI '15: Proceedings of the 33rd Annual ACM Conference on Human Factors in Computing Systems
      April 2015
      4290 pages
      ISBN:9781450331456
      DOI:10.1145/2702123

      Copyright © 2015 ACM

      Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

      Publisher

      Association for Computing Machinery

      New York, NY, United States

      Publication History

      • Published: 18 April 2015

      Permissions

      Request permissions about this article.

      Request Permissions

      Check for updates

      Qualifiers

      • research-article

    PDF Format

    View or Download as a PDF file.

    PDF

    eReader

    View online with eReader.

    eReader