Skip to main content

Modelle des Demos. Hybride Repräsentation und die Politik der Inferenzen

  • Chapter
  • First Online:
Die Fabrikation von Demokratie
  • 211 Accesses

Zusammenfassung

Der Beitrag verortet die zunehmende Relevanz digitaler Modelle in organisationalen und politischen Prozessen als Rekonfiguration gesellschaftlicher Selbstbeobachtung. Vor dem Hintergrund eines praxistheoretischen Zugangs, der Modellierung als durch materiale Infrastrukturen und vernetzte Wissensformen strukturierte Praxis der Produktion von Gesellschaftswissen versteht, wird argumentiert, dass diese Rekonfiguration das Zusammenwirken von epistemischer und politischer Repräsentation durch Formen hybrider Repräsentation prägt, in denen das Volk als komplexes Datenobjekt zur Sprache gebracht werden soll. Anhand der Beispiele von Computational Social Science und Algorithmic Decision-Making wird angedeutet, wie Modellierungspraktiken als Teil der Ökonomie politischer Repräsentation wirken können. Mit der Organisation von Inferenzen wird eine Dimension der Performativität dieser hybriden Repräsentationspraktiken in den Blick genommen.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 59.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 74.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Literatur

  • AlgorithmWatch. (2020). “Automating Society” Hrsg. von F. Chiusi, S. Fischer, N. Kayser-Bril & M. Spielkamp.

    Google Scholar 

  • Angwin, J., Larson, J., Mattu, S., & Kirchner, L. (2016). Machine bias. In ProPublica. https://www.propublica.org/article/machine-bias-risk-assessments-in-criminal-sentencing

  • Barnes, T. J., & Wilson, M. W. (2014). Big data, social physics, and spatial analysis: The early years. Big Data & Society, 1(1).

    Google Scholar 

  • Barocas, S., & Selbst, A. D. (2016). Big data’s disparate impact. California Law Review, 104, 671–732.

    Google Scholar 

  • Bourdieu, P. (1993). Sozialer Sinn. Kritik der theoretischen Vernunft. Suhrkamp.

    Google Scholar 

  • Bourdieu, P. (1995). Sozialer Raum und “Klassen“. Zwei Vorlesungen. Suhrkamp.

    Google Scholar 

  • Bourdieu, P. (2010). Politik. Schriften zur Politischen Ökonomie 2. Suhrkamp.

    Google Scholar 

  • Bruns, A. (2019). After the ‘APIcalypse’: Social media platforms and their fight against critical scholarly research. Information, Communication & Society, 22(11), 1544–1566.

    Article  Google Scholar 

  • Bunge, M. (1993). Realism and antirealism in social science. Theory and decision, 35(3), 207–235.

    Google Scholar 

  • Buolamwini, J., & Gebru, T. (2018). Gender shades: Intersectional accuracy disparities in commercial gender classification. Proceedings of Machine Learning Research, 81, 1–15.

    Google Scholar 

  • Burrell, J. (2016). How the machine ‘thinks’: Understanding opacity in machine learning algorithms. Big Data & Society, 3(1), 1–12.

    Article  Google Scholar 

  • Callon, M. (1984). Some elements of a sociology of translation: Domestication of the scallops and the fishermen of St. Brieuc Bay. The Sociological Review, 32(1_suppl), 196–233.

    Google Scholar 

  • Camic, C., Gross, N., & Lamont, M. (Hrsg.). (2011). Social knowledge in the making. University of Chicago Press.

    Google Scholar 

  • Coopmans, C. (Hrsg.). (2014). Representation in scientific practice revisited. MIT Press.

    Google Scholar 

  • Coopmans, C., Vertesi, J., Lynch, M. E., & Woolgar, S. (Hrsg.). (2014). Representation in scientific practice revisited. MIT Press.

    Google Scholar 

  • Desrosières, A. (1991). How to make things which hold together: Social science, statistics and the state. In P. Wagner, B. Wittrock, & R. Whitley (Hrsg.), Discourses on society (S. 195–218). Springer Netherlands.

    Google Scholar 

  • Diehl, P. (2016). Repräsentation im Spannungsfeld von Symbolizität, Performativität und politischem Imaginären. In P. Diehl & F. Steilen (Hrsg.), Politische Repräsentation und das Symbolische (S. 7–22). Springer.

    Google Scholar 

  • Diehl, P. (2019). Das politische Imaginäre und die politische Repräsentation. Österreichische Zeitschrift für Soziologie, 44, 37–55.

    Article  Google Scholar 

  • Diehl, P., Sintomer, Y., & Hayat, S. (2014). Einleitung. Trivium, 16.

    Google Scholar 

  • Diehl, P., & Steilen, F. (Hrsg.). (2016). Politische Repräsentation und das Symbolische. Historische, politische und soziologische Perspektiven. Springer VS.

    Google Scholar 

  • Disch, L. (2008). The people as ‘presupposition’ of representative democracy – An essay on the political theory of Pierre Rosanvallon. Redescriptions: Political Thought, Conceptual History and Feminist Theory, 12(1), 47.

    Google Scholar 

  • Disch, L. (2010). ‘Faitiche’-izing the people: What representative democracy might learn from science studies. In B. Braun & S. Whatmore (Hrsg.), Political matter. Technoscience, democracy, and public life. University of Minnesota Press.

    Google Scholar 

  • Disch, L. (2011). Toward a mobilization conception of democratic representation. American Political Science Review, 105(1), 100–114.

    Article  Google Scholar 

  • Egmond, V. S., & Zeiss, R. (2010). Modeling for policy: Science-based models as performative boundary objects for dutch policy making. Science Studies, 23(1), 58–78.

    Google Scholar 

  • Edwards, P. N. (2013). A vast machine. Computer models, climate data, and the politics of global warming. MIT Press.

    Google Scholar 

  • Ensign, D., Friedler, S. A., Neville, S., Scheidegger, C., & Venkatasubramanian, S. (2018). Runaway feedback loops in predictive policing. Proceedings of Machine Learning Research, 81, 1–12.

    Google Scholar 

  • Espeland, W. N., & Sauder, M. (2007). Rankings and reactivity: How public measures recreate social worlds. American Journal of Sociology, 113(1), 1–40.

    Article  Google Scholar 

  • Eyert, F. (2023). Mathematical science communication as a strategy for democratizing algorithmic governance. In A. M. Hartkopf & E. Henning (Hrsg.), Handbook of Mathematical Science Communication (S. 295–321). World Scientific.

    Google Scholar 

  • Eyert, F., & Lopez P. (2023). Rethinking Transparency as a Communicative Constellation. Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency, 444–454.

    Google Scholar 

  • Eyert, F., Irgmaier, F., & Ulbricht, L. (2020). Extending the framework of algorithmic regulation. The Uber case. Regulation & Governance, 16(1), 23–44.

    Google Scholar 

  • Garcia, D., Pellert, M., Lasser, J., & Metzler, H. (2021). Social media emotion macroscopes reflect emotional experiences in society at large. https://arxiv.org/abs/2107.13236.

  • Gramelsberger, G., & Mansnerus, E. (2012). The inner world of models and its epistemic diversity: Infectious disease and climate modelling. In C. Bissell & C. Dillon (Hrsg.), Ways of thinking, ways of seeing. Mathematical and other modelling in engineering and technology (S. 167–195). Springer.

    Google Scholar 

  • Green, B. (2018). Data science as political action: Grounding data science in a politics of justice. https://arxiv.org/abs/1811.03435.

  • Hacking, I. (1983). Representing and intervening. Introductory topics in the philosophy of natural science. Cambridge University Press.

    Book  Google Scholar 

  • Hacking, I. (2000). The social construction of what? Harvard University Press.

    Book  Google Scholar 

  • Han, B.-C. (2013). Digitale Rationalität und das Ende des kommunikativen Handelns. Matthes & Seitz.

    Google Scholar 

  • Hayat, S. (2019). Representation as proposition: Democratic representation after the constructivist turn. In L. Disch, M. v. de Sande, & N. Urbinati (Hrsg.), The constructivist turn in political representation (S. 121–140). Edinburgh University Press.

    Google Scholar 

  • Healy, K. (2015). The performativity of networks. European Journal of Sociology, 56(2), 175–205.

    Article  Google Scholar 

  • Heintz, B. (2021). Big Observation – Ein Vergleich moderner Beobachtungsformate am Beispiel von amtlicher Statistik und Recommendersystemen. Kölner Zeitschrift für Soziologie und Sozialpsychologie, 73, 137–167.

    Google Scholar 

  • Hofmann, J. (2018). Big data im Wahlkampf: Wählerinnen- und Wählermodellierung, micro-targeting und Repräsentationsansrpüche. In Kolany-Reiser (Hrsg.), Dimensionen von Big Data. Eine multidisziplinäre Annäherung (S. 163–168). Springer.

    Google Scholar 

  • Hooker, S. (2021). Moving beyond ‘algorithmic bias is a data problem’. Patterns, 2(4), 1–4.

    Article  Google Scholar 

  • Humphreys, P. (2004). Extending ourselves. Computational science, empiricism, and scientific method. Oxford University Press.

    Book  Google Scholar 

  • Humphreys, P. (2009). The philosophical novelty of computer simulation methods. Synthese, 169(3), 615–626.

    Article  Google Scholar 

  • Johnson-Laird, P. N. (1983). Mental models. Towards a cognitive science of language, inference, and consciousness. Harvard University Press.

    Google Scholar 

  • Kannangara, S., & Wobcke, W. (2022). Determining political interests of issue-motivated groups on social media: Joint topic models for issues, sentiment and stance. Journal of Computational Social Science, 5(1), 811–40.

    Google Scholar 

  • Katzenbach, C., & Ulbricht, L. (2019). Algorithmic governance. Internet Policy Review, 8(4).

    Google Scholar 

  • Kaufmann, M., Egbert, S., & Leese, M. (2018). Predictive policing and the politics of patterns. The British Journal of Criminology, 59(3), 674–692.

    Article  Google Scholar 

  • Knuuttila, T. (2011). Modelling and representing: An artefactual approach to model-based representation. Studies in History and Philosophy of Science Part A, 42(2), 262–271.

    Article  Google Scholar 

  • Kupilik, M., & Witmer, F. (2018). Spatio-temporal violent event prediction using Gaussian process regression. Journal of Computational Social Science, 1(2), 437–451.

    Article  Google Scholar 

  • Latour, B. (1990). Drawing things together. In M. Lynch & S. Woolgar (Hrsg.), Representation in scientific practice (S. 19–68). MIT Press.

    Google Scholar 

  • Latour, B. (2003). What if we talked politics a little? Contemporary Political Theory, 2003(2), 143–164.

    Article  Google Scholar 

  • Latour, B. (2004). Politics of nature. How to bring the sciences into democracy. Harvard University Press.

    Google Scholar 

  • Laurent, B. (2013). Du laboratoire scientifique à l’ordre constitutionnel: Analyser la représentation à la suite des études sociales des sciences. Raisons politiques, 50(2), 137–155.

    Article  Google Scholar 

  • Law, J., & Urry, J. (2004). Enacting the social. Economy and Society, 33(3), 390–410.

    Article  Google Scholar 

  • Lazer, D. M. J., Pentland, A., Watts, D. J., Aral, S., Athey, S., Contractor, N., Freelon, D., et al. (2020). Computational social science: Obstacles and opportunities. Science, 369(6507), 1060–1062.

    Article  Google Scholar 

  • Lazer, D., Pentland, A., Adamic, L., Aral, S., Barabasi, A.-L., Brewer, D., Christakis, N., et al. (2009). Computational social science. Science, 323(5915), 721–723.

    Article  Google Scholar 

  • Longo, J., Kuras, E., Smith, H., Hondula, D. M., & Johnston, E. (2017). Technology use, exposure to natural hazards, and being digitally invisible: Implications for policy analytics. Policy & Internet, 9(1), 76–108.

    Article  Google Scholar 

  • Lopez, P. (2019). Reinforcing intersectional inequality via the AMS algorithm in Austria. In Proceedings of the STS Graz Conference 2019. Critical issues in science, technology, and society studies (S. 289–309).

    Google Scholar 

  • Luhmann, N. (1998). Die Gesellschaft der Gesellschaft. Suhrkamp.

    Google Scholar 

  • Lynch, M., & Woolgar, S. (Hrsg.). (1990). Representation in scientific practice. MIT Press.

    Google Scholar 

  • MacKenzie, D. A., Muniesa, F., & Siu, L. (Hrsg.). (2008). Do economists make markets? On the performativity of economics. Princeton University Press.

    Google Scholar 

  • Malik, M. M., Mayer, K., Lamba, H., & Müller-Birn, C. (2019). Workshop on critical data science. At the 13th international AAAI conference on web and social media (ICWSM-19) June 11, 2019. https://projects.iq.harvard.edu/files/critical-data-science/files/wcds2019_proposal.pdf.

  • Mau, S. (2020). Numbers matter! The society of indicators, scores and ratings. International Studies in Sociology of Education, 29(1–2), 19–37.

    Article  Google Scholar 

  • Mohler, G. O. (2011). Self-exciting point process modeling of crime. Journal of the American Statistical Association, 106(493), 100–108.

    Article  Google Scholar 

  • Mol, A. (1999). Ontological politics. A word and some questions. The Sociological Review, 47(S1), 74–89.

    Google Scholar 

  • Müller, H.-P. (2016). Politisches Feld und politische Repräsentation. In P. Diehl & F. Steilen (Hrsg.), Politische Repräsentation und das Symbolische. Historische, politische und soziologische Perspektiven (S. 85–106). Springer.

    Google Scholar 

  • Nassehi, A. (2019). Muster. Theorie der digitalen Gesellschaft. Beck.

    Book  Google Scholar 

  • Osborne, T., & Rose, N. (1999). Do the social sciences create phenomena? The example of public opinion research. The British Journal of Sociology, 50(3), 367–396.

    Article  Google Scholar 

  • Pentland, A. (2015). Social physics. How social networks can make us smarter. Penguin.

    Google Scholar 

  • Pitkin, H. F. (1972). The concept of representation. University of California Press.

    Google Scholar 

  • Prietl, B. (2021). Warum Ethikstandards nicht alles sind. Zu den herrschaftskonservierenden Effekten aktueller Digitalisierungskritik. Behemoth, 14(2).

    Google Scholar 

  • Reckwitz, A. (2002). Toward a theory of social practices: A development in culturalist theorizing. European Journal of Social Theory, 5(2), 243–63.

    Google Scholar 

  • Reckwitz, A. (2019). Das Ende der Illusionen. Politik, Ökonomie und Kultur in der Spätmoderne. Suhrkamp.

    Google Scholar 

  • Rosanvallon, P. (1998). Le Peuple Introuvable. Histoire de La Représentation Démocratique En France. Gallimard.

    Google Scholar 

  • Ruelens, A. (2022). Analyzing user-generated content using Natural Language Processing: A case study of public satisfaction with healthcare systems. Journal of Computational Social Science, 5(1), 731–49.

    Google Scholar 

  • Sánchez-Monedero, J., & Dencik, L. (2020). The politics of deceptive borders: ‘Biomarkers of deceit’ and the case of iBorderCtrl. Information, Communication & Society, 25(3), 413–430.

    Google Scholar 

  • Savage, M., & Burrows, R. (2007). The coming crisis of empirical sociology. Sociology, 41(5), 885–899.

    Article  Google Scholar 

  • Saward, M. (2005). Governance and the transformation of political representation. In Janet Newman (Hrsg.), Remaking governance. Peoples, politics and the public sphere (S. 179–196). Policy Press.

    Google Scholar 

  • Saward, M. (2006). The representative claim. Contemporary Political Theory, 5(3), 297–318.

    Article  Google Scholar 

  • Schäfer, H. (Hrsg.) (2016). Praxistheorie. Ein soziologisches Forschungsprogramm. Transcript.

    Google Scholar 

  • Schatzki, T. R., Knorr-Cetina, K., & von Savigny, E. (Hrsg.). (2001). The practice turn in contemporary theory. Routledge.

    Google Scholar 

  • Schauer, F., & Zeckhauser, R. (2007). Regulation by generalization. Regulation & Governance, 1(1), 68–87.

    Article  Google Scholar 

  • Scott, J. C. (1998). Seeing like a state. How certain schemes to improve the human condition have failed. Yale University Press.

    Google Scholar 

  • Simon, M. (2019). Path dependency and adaptation: The effects of policy on migration systems. Journal of Artificial Societies and Social Simulation, 22(2).

    Google Scholar 

  • Smee, B. (13. September 2021). Queensland police to trial AI tool designed to predict and prevent domestic violence incidents. The Guardian. https://www.theguardian.com/australia-news/2021/sep/14/queensland-police-to-trial-ai-tool-designed-to-predict-and-prevent-domestic-violence-incidents.

  • Ulbricht, L. (2020). Scraping the demos. Digitalization, web scraping and the democratic project. Democratization, 27(3), 426–442.

    Google Scholar 

  • Urbinati, N., & Warren, M. E. (2008). The concept of representation in contemporary democratic theory. Annual Review of Political Science, 11(1), 387–412.

    Article  Google Scholar 

  • Voß, J.-P. (2018). Big Data als epistemische Innovation? Kulturell-kognitiv hergestellte Erwartungen durch Big Data. In Kolany-Reiser (Hrsg.), Dimensionen von Big Data. Eine multidisziplinäre Annäherung (S. 155–163). Springer.

    Google Scholar 

  • Wachter, S., & Mittelstadt, B. (2019). A right to reasonable inferences: Re-thinking data protection law in the age of Big Data and AI. Columbia Business Law Review, 2019(2).

    Google Scholar 

  • Wagner, P., Weiss, C. H., Wittrock, B., & Wollman, H. (1991). Social sciences and modern states. National experiences and theoretical crossroads. Cambridge University Press.

    Book  Google Scholar 

  • Wagner, C., Strohmaier, M., Olteanu, A., Kıcıman, E., Contractor, N., & Eliassi-Rad, T. (2021). Measuring algorithmically infused societies. Nature, 595(7866), 197–204.

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Florian Eyert .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2024 Der/die Autor(en), exklusiv lizenziert an Springer Fachmedien Wiesbaden GmbH, ein Teil von Springer Nature

About this chapter

Check for updates. Verify currency and authenticity via CrossMark

Cite this chapter

Eyert, F. (2024). Modelle des Demos. Hybride Repräsentation und die Politik der Inferenzen. In: Voß, JP., Schölzel, H. (eds) Die Fabrikation von Demokratie. Politologische Aufklärung – konstruktivistische Perspektiven. Springer VS, Wiesbaden. https://doi.org/10.1007/978-3-658-42936-2_5

Download citation

  • DOI: https://doi.org/10.1007/978-3-658-42936-2_5

  • Published:

  • Publisher Name: Springer VS, Wiesbaden

  • Print ISBN: 978-3-658-42935-5

  • Online ISBN: 978-3-658-42936-2

  • eBook Packages: Social Science and Law (German Language)

Publish with us

Policies and ethics