About Discursive Storylines and Techno-Fixes: The Political Framing of the Implementation of Predictive Policing in Germany


One important reason for the current rise of predictive policing in Germany is the recent boost in the development of digital technologies and the associated possibility of analysing huge data sets at relatively low cost by utilising mathematically deduced algorithms. Economic motives also play a vital role in the implementation process, as it is hoped that policing can be organised more rationally by the more effective allocation of police patrols. However, in addition to technical and economic factors, the rise of predictive policing in Germany is above all a political phenomenon, involving the discursive shaping of domestic burglary as a security problem. Furthermore, the ways, how the technologies utilised for predictive crime data analysis are discursively referred to, play a vital role in this discourse. These new prediction tools facilitate rhetorical links for politicians and police authorities in legitimising their ambitions to fight crime and enhance public security, presenting their methods as innovative and effective and making these technologies important components of corresponding security discourses.

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  1. 1.

    Parts of this paper have already been published in German in Egbert (2017).

  2. 2.

    In the case of ‘Minority Report’, however, it is noticeable that positive as well as negative connotations are present when this short story and film are associated with predictive policing.

  3. 3.

    The reference source cited refers to the author’s internal coding system for empirical data and applies to the corresponding interview log and line number.

  4. 4.

    The most prominent example of such individual-related predictive policing approaches is the “strategic subject list”—or “heat list”, as colloquially labelled—with which the Police Department of Chicago tries to identify probable perpetrators and victims of homicides by drawing on indicators like gang membership, criminal record and past homicides in their families and circles of acquaintances (Saunders et al. 2016; Chicago Data Portal 2017).

  5. 5.

    Although this may be the case in some instances, I do not want to imply that the rhetorical connection of rising case numbers of domestic burglaries and predictive policing is per se based on instrumentalisation or is purely power-driven. To the contrary, on a more abstract level I want to point out the mixture of rhetorical topoi and the discursive dynamic resulting from it.

  6. 6.

    All quotations in the remainder of this paper are translations from German by the author.

  7. 7.

    Now that the CDU is in government in NRW, the statements in the coalition agreement with the FDP (Freiheitliche Demokratische Partei [Free Democratic Party]) concerning predictive policing sound much more restrained: “We will complete the ongoing pilot project on predictive policing and will take a decision soon, on the basis of the resulting evaluation, about implementation.” (CDU and FDP 2017, p. 62).

  8. 8.

    Although the implementation of predictive policing in Germany is not framed by highlighting “existential threats” and although no “established rules of the game (of politics)” are broken, the basic rhetorical structure of the discursive framing of the need of predictive policing can be grasped as illustrating the process of “securitization” in the sense of Buzan et al. (1998, 23f.).

  9. 9.

    It has to be added here that, from a criminological perspective, it is rather unclear whether the current increase in case numbers of domestic burglaries is actually based on the activities of Eastern European burglars, as the corresponding conviction rates are very low; this means that there is insufficient certainty about the identities of the offenders (Bartsch et al. 2014).

  10. 10.

    This observation was also made in course of the introduction of CCTV systems in Great Britain (Norris and Armstrong 1999, 63f.), and there are of course several more empirical examples of such a rhetorical accompaniment of implementation processes of security technologies.

  11. 11.

    In fact, the empirical findings about the displacement effect of situational crime prevention measures like predictive policing argue against the displacement hypothesis, highlighting the spatial “diffusion of benefits” (Guerette and Bowers 2009; an overview of empirical findings can be found in Johnson et al. 2014). Referring to the near repeat hypothesis, one argument for denying a strong displacement effect of predictive policing is to highlight the difficulties burglars experience in finding alternative targets at short notice (G28: 34f.).

  12. 12.

    With the semiotic term ‘actant‘, Latour refers to non-human entities participating in certain context of interaction by making a difference, for example as they change the behavior of the human participants.


  1. Andrejevic M (2017) To preempt a thief. Int J Commun 11:879–896

    Google Scholar 

  2. Balogh DA (2016) Near repeat-prediction mit ‘PRECOBS’ bei der Stadtpolizei Zürich. Kriminalistik 70:335–341

    Google Scholar 

  3. Bartsch T et al (2014) Phänomen Wohnungseinbruch—Taten, Täter, Opfer. Kriminalistik 68:483–490

    Google Scholar 

  4. Beck C, McCue C (2009) Predictive policing: what can we learn from Wal-Mart and Amazon about fighting crime in a recession? Police Chief LXXVI, 11. http://acmcst373ethics.weebly.com/uploads/2/9/6/2/29626713/police-chief-magazine.pdf. Accessed 23 Aug 2017

  5. Belina B (2016) Predictive policing. Monatsschr Kriminol Strafrecht 99:85–100

    Google Scholar 

  6. Bennett Moses C, Chan J (2016) Algorithmic prediction in policing: assumptions, evaluation, and accountability. Polic Soc. https://doi.org/10.1080/10439463.2016.1253695

    Article  Google Scholar 

  7. Berliner-Reporter Live (2016) KrimPro—was ist das? Software soll Einbrüche vorhersagen! (video from press conference), 10.08.2016. https://www.facebook.com/berlinreporterlive/videos/vb.1556917707939425/1592848981012964/?type=2&theater. Accessed 25 Aug 2017

  8. Bijker WE, Hughes TP, Pinch T (eds) (2012) The social construction of technological systems. Anniversary Edition. MIT Press, Cambridge

    Google Scholar 

  9. Bogomolov A (2014) Once upon a crime: towards crime prediction from demographics and mobile data. In: ICMI 2014. Proceedings of the 16th International Conference on Multimodal Interaction. 12–16 November 2014, Istanbul, Turkey, pp 427–434. http://dx.doi.org/10.1145/2663204.2663254

  10. Borchers D (2015) Precrime per Predictive Policing: Das Internet der Dinge im Zeugenstand, 26.02.2015. https://www.heise.de/newsticker/meldung/Precrime-per-Predictive-Policing-Das-Internet-der-Dinge-im-Zeugenstand-2559840.html. Accessed 25 Aug 2017

  11. BR (Bayerischer Rundfunk) (2016) “Predictive Policing” bei LKA München. http://www.br.de/mediathek/video/sendungen/nachrichten/lka-muenchen-predictive-policing-100.html. Accessed 23 Aug 2017

  12. Bratton W, Morgan J, Malinowski S (2009) Fighting crime in the information age: the promise of predictive policing. LAPD Research Paper. https://publicintelligence.net/lapd-research-paper-fighting-crime-in-the-information-age-the-promise-of-predictive-policing/. Accessed 20 Sep 2017

  13. Bratton WJ, Morgan J, Malinowski S (2009) Fighting crime in the information age. The promise of predictive policing. In: Paper presented at the annual meeting of the American Society of Criminology 2009, Philadelphia

  14. BSTMI (Bayerisches Staatsministerium des Innern, für Bau und Verkehr [The Bavarian Ministry of the Interior, for Building and Transport]) (2014) Sicherheitsbericht zum Beschluss des Bayer. Landtags vom 30. September 2014. http://www.stmi.bayern.de/assets/stmi/med/aktuell/161207_sicherheitsbericht_gesamt_n.pdf. Accessed 24 Aug 2017

  15. BSTMI (Bayerisches Staatsministerium des Innern, für Bau und Verkehr [The Bavarian Ministry of the Interior, for Building and Transport]) (2014) Bayernweite Kontrollaktion gegen Diebesbanden, 26.11.2014. https://www.stmi.bayern.de/med/pressemitteilungen/pressearchiv/2014/395b/index.php. Accessed 24 Aug 2017

  16. BSTMI (Bayerisches Staatsministerium des Innern, für Bau und Verkehr [The Bavarian Ministry of the Interior, for Building and Transport]) (2015) Wohnungspolitik in Bayern. Rede des Bayerischen Staatsministers des Innern, für Bau und Verkehr, Joachim Herrmann, anlässlich der 19. Generalversammlung des Eigenheimerverbands Bayern am 18. Juli 2015 in Garching. https://www.eigenheimerverband.de/downloads/1329/Wortlaut%20der%20Rede%20von%20Staatsminister%20Herrmann.pdf?1439895135. Accessed 24 Aug 2017

  17. BSTMI (Bayerisches Staatsministerium des Innern, für Bau und Verkehr [The Bavarian Ministry of the Interior, for Building and Transport]) (2015) Herrmann berichtet über Erfahrungen des ‘PRECOBS’-Tests in München und Mittelfranken, 24. June 2015. https://www.stmi.bayern.de/med/pressemitteilungen/pressearchiv/2015/204/index.php. Accessed 24 Aug 2017

  18. BSTMI (Bayerisches Staatsministerium des Innern, für Bau und Verkehr [The Bavarian Ministry of the Interior, for Building and Transport]) (2016) Herrmann stellt Sicherheitsbericht vor, 07.12.2016. https://www.stmi.bayern.de/med/pressemitteilungen/pressearchiv/2016/464/index.php. Accessed 24 Aug 2017

  19. Budras C (2015) Schütze sich, wer kann, 25.05.2015. http://www.faz.net/aktuell/wirtschaft/wie-der-staat-bei-der-hauseinbruch-bekaempfung-versagt-13608811.html. Accessed 23 Aug 2017

  20. Bühl J, Fuchs F (2014) Gesucht: Einbrecher der Zukunft, 12.09.2014. http://www.sueddeutsche.de/digital/polizei-software-zur-vorhersage-von-verbrechen-gesucht-einbrecher-der-zukunft-1.2115086. Accessed 25 Aug 2017

  21. Buzan B, Wæver O, de Wilde J (1998) Security: a new framework for analysis. Lynne Rienner, Boulder

    Google Scholar 

  22. CDU BW (2015) Strobl fordert Ministerpräsident Kretschmann zum Handeln auf, 27.05.2017. http://www.cdu-bw.de/aktuelles/presse/presse-detail/artikel/strobl-fordert-ministerpraesident-kretschmann-zum-handeln-auf.html. Accessed 25 Aug 2017

  23. CDU NRW (2017) Zuhören. Entscheiden. Handeln. Regierungsprogramm der CDU für Nordrhein-Westfalen 2017-2022, 01.04.2017, https://www.cdu-nrw.de/sites/default/files/media/docs/2017-04-01_regierungsprogramm_cdu_fuer_nrw_2017-2022.pdf. Accessed 23 Aug 2017

  24. CDU NRW, FDP NRW (2017) Koalitionsvertrag für Nordrhein-Westfalen 2017-2022. https://www.cdu-nrw.de/sites/default/files/media/docs/vertrag_nrw-koalition_2017.pdf. Accessed 23 Aug 2017

  25. Chainey SP, da Silva BFA (2016) Examining the extent of repeat and near repeat victimisation of domestic burglaries in Belo Horizonte, Brazil. Crime Sci. https://doi.org/10.1186/s40163-016-0049-6

    Article  Google Scholar 

  26. Chicago Data Portal (2017) Strategic subject list. https://data.cityofchicago.org/Public-Safety/Strategic-Subject-List/4aki-r3np. Accessed 22 Aug 2017

  27. Clarke RV (1993) Routine activity and rational choice. Transaction, New Brunswick

    Google Scholar 

  28. Cohen LE, Felson M (1979) Social change and crime rate trends: a routine activity approach. Am Sociol Rev 44:588–608

    Article  Google Scholar 

  29. Cortesi M (2017) Polizeiliche Kriminalstatistik Stadt Zürich 2016, City of Zurich Security Department, 27.03.17. https://www.stadt-zuerich.ch/content/pd/de/index/stadtpolizei_zuerich/medien/medienmitteilungen/2017/maerz/polizeiliche-kriminalstatistik-stadt-zuerich-2016.html. Accessed 23 Aug 2017

  30. Dreißigacker A et al (2017) Wohnungseinbruchdiebstahl als Verbrechen—Was nützen die Neuregelungen zum Wohnungseinbruch? Neue Kriminalpolitik 29:321–333. https://doi.org/10.5771/0934-9200-2017-3-321

    Article  Google Scholar 

  31. Egbert S (2017) Siegeszug der Algorithmen? Predictive Policing im deutschsprachigen Raum. Aus Polit Zeitgesch 67:17–23

    Google Scholar 

  32. Elflein C et al (2014) Der Staat versagt, 13.10.2014. http://www.focus.de/immobilien/wohnen/politik-der-staat-versagt_id_4196533.html. Accessed 23 Aug 2017

  33. Gaskell A (2017) ThirdEye bring predictive policing inside the store. http://www.huffingtonpost.com/adi-gaskell/thirdeye-bring-predictive_b_9437996.html. Accessed 5 Aug 2017

  34. Gent A (2017) Could predictive policing lead to a real-life minority report? https://singularityhub.com/2017/02/02/could-predictive-policing-lead-to-a-real-life-minority-report/. Accessed 23 Sep 2017

  35. Gerstner D (2017) Predictive Policing als Instrument zur Prävention von Wohnungseinbruchdiebstahl. Evaluationsergebnisse zum baden-württembergischen Pilotprojekt P4. https://www.mpicc.de/files/pdf4/rib_50_gerstner_2017.pdf. Accessed 13 Dec 2017

  36. Gluba A (2014) Predictive Policing – eine Bestandsaufnahme. Kriminalistik 6/2014 S:347–352

    Google Scholar 

  37. Gluba A (2016) Mehr offene Fragen als Antworten. Die Polizei 107:53–57

    Google Scholar 

  38. Gluba A (2017) Der Modus Operandi bei Fällen der Near Repeat-Victimisation. Kriminalistik 71:369–375

    Google Scholar 

  39. Gluba A, Pett A (2017) Predictive Policing: Ein (un)bekannter Ansatz. In: Möllers MHW, van Ooyen RC (eds) Jahrbuch Öffentliche Sicherheit 2016/2017. Verlag für Polizeiwissenschaft, Frankfurt, pp 431–440

    Google Scholar 

  40. Groenemeyer A (2015) Soziale Konstruktionen von Ordnungsstörungen. Abweichung als Risiko. In: Dollinger B, Groenemeyer A, Rzepka, Dorothea (eds) Devianz als Risiko. Neue Perspektiven des Umgangs mit abweichendem Verhalten, Delinquenz und sozialer Auffälligkeit, Beltz Juventa, Weinheim, Basel, pp 9–43

  41. Groff ER, La Vigne NG (2002) Forecasting the future of predictive crime mapping. In: Tilley N (ed) Analysis for crime prevention: crime prevention studies, vol 13. Criminal Justice Press, Monsey, pp 29–57

    Google Scholar 

  42. Guerette RT, Bowers KJ (2009) Assessing the extent of crime displacement and diffusion of benefits: a review of situational crime prevention evaluations. Criminology 47:1331–1368. https://doi.org/10.1111/j.1745-9125.2009.00177.x

    Article  Google Scholar 

  43. Heitmüller U (2017) Predictive Policing: Die deutsche Polizei zwischen Cyber-CSI und Minority Report, 17. April 2017. https://www.heise.de/newsticker/meldung/Predictive-Policing-Die-deutsche-Polizei-zwischen-Cyber-CSI-und-Minority-Report-3685873.html. Accessed 23 Aug 2017

  44. Herrmann J (2015) Aktuelles, 27.03.2015. https://www.joachimherrmann.de/index.php?ka=1&ska=1&idn=2360. Accessed 24 Aug 2017

  45. Hilscher M and Heeder M (directors) (2017) Pre-Crime [motion picture]. Rise and Shine Cinema, Hamburg

  46. HMIS (Hessisches Ministerium des Innern und des Sports [Hessian Ministry of the Interior and Sport]) (2016) Innenminister Peter Beuth stellt Prognose-Software „KLB-operativ“vor, 20. July 2016. https://www.hessen.de/pressearchiv/pressemitteilung/innenminister-peter-beuth-stellt-prognose-software-klb-operativ-vor. Accessed 24 Aug 2017

  47. HMIS (Hessisches Ministerium des Innern und des Sports [Hessian Ministry of the Interior and Sport]) (2017) Innenminister Peter Beuth begrüßt Verschärfung bei Einbruchdiebstahl. https://www.hessen.de/presse/pressemitteilung/innenminister-peter-beuth-begruesst-verschaerfung-bei-einbruchdiebstahl-0. Accessed 24 Aug 2017

  48. Hughes TP (2004) Afterword. In: Rosner L (ed) The technological fix: how people use technology to create and solve problems. Routledge, New York, London, pp 208–210

    Google Scholar 

  49. Johnson SD et al (2007) Space-time patterns of risk: a cross national assessment of residential burglary victimization. J Quant Criminol 23:201–219. https://doi.org/10.1007/s10940-007-9025-3

    Article  Google Scholar 

  50. Johnson SD, Guerette RT, Bowers KJ (2014) Crime displacement: what we know, what we don’t know, and what it means for crime reduction. J Exp Criminol 10:549–571. https://doi.org/10.1007/s11292-014-9209-4

    Article  Google Scholar 

  51. Kaufmann, FX (2012)[1973]) Sicherheit als soziologisches und Sozialpolitisches Problem. Reprint of 2nd ed. LIT, Berlin et al

  52. Kaufmann S (2016) Security through technology? Logic, ambivalence and paradoxes of technologised security. Eur J Secur Res 1:77–95. https://doi.org/10.1007/s41125-016-0005-1

    Article  Google Scholar 

  53. Keller R (2011) The sociology of knowledge approach to discourse (SKAD). Hum Stud 34:43–65. https://doi.org/10.1007/s10746-011-9175-z

    Article  Google Scholar 

  54. Keller R (2013) Doing discourse research: an introduction for social scientists. SAGE, Los Angeles

    Google Scholar 

  55. Krauel T (2013) Der Staat versagt bei seinem Kernauftrag, 15.05.2013. https://www.welt.de/debatte/kommentare/article116223952/Der-Staat-versagt-bei-seinem-Kernauftrag.html. Accessed 23 Aug 2017

  56. Kreissl R (2014) Assessing security technology’s impact: old tools for new problems. Sci Eng Ethics 20:659–673. https://doi.org/10.1007/s11948-014-9529-9

    Article  Google Scholar 

  57. Krempl S (2016) Kriminalitätsprognose: Berliner Polizei setzt auf Predictive Policing, 10.08.2016. https://www.heise.de/newsticker/meldung/Kriminalitaetsprognose-Berliner-Polizei-setzt-auf-Predictive-Policing-3291880.html. Accessed 25 Aug 2017

  58. Kroener IJ (2014) CCTV. A technology under the radar?. Ashgate, Farnham

    Google Scholar 

  59. Landtag NRW (2016) Drucksache 16/122344. Antrag der Fraktion der CDU Maßnahmenpaket zur Bekämpfung des Wohnungseinbruchsdiebstahls, 28.06.2016. https://www.landtag.nrw.de/portal/WWW/dokumentenarchiv/Dokument/MMD16-12344.pdf. Accessed 23 Aug 2017

  60. Latour B (2005) Reassembling the social. An introduction to actor-network-theory. Oxford University Press, Oxford

    Google Scholar 

  61. Mantello P (2016) The machine that ate bad people: the ontopolitics of the precrime assemblage. Big Data Soc 3:1–11. https://doi.org/10.1177/2053951716682538

    Article  Google Scholar 

  62. Marx GT (1995) The engineering of social control: the search for the silver bullet. In: Hagan J, Peterson RD (eds) Crime and inequality. Stanford University Press, Stanford, pp 225–246

    Google Scholar 

  63. Maguire M, McVie S (2017) Crime data and criminal statistics. A critical reflection. In: Liebling A, Maruna S, McAra L (eds) The Oxford handbook of criminology, 6th edn. Oxford University Press, Oxford, pp 163–189

  64. McCue C, Parker A (2003) Connecting the dots: data mining and predictive analytics in law enforcement and intelligences analysis. In: The Police Chief, 70(10). http://www.policechiefmagazine.org/connecting-the-dots-data-mining-and-predictive-analytics-in-law-enforcement-and-intelligence-analysis/. Accessed 7 Sep 2017

  65. MDR (Mitteldeutscher Rundfunk) (2016) Software sagt Einbruchszentren hervor. https://www.youtube.com/watch?v=mQvjRILRytU. Accessed 23 Aug 2017

  66. Mendola M (2016) one step further in the surveillance society: the case of predictive policing. http://techandlaw.net/wp-content/uploads/2016/10/One-Step-Further-in-the-Surveillance-Society_The-Case-of-Predictive-Policing.pdf. Accessed 18 Sep 2017

  67. MIK NRW (Ministerium für Inneres und Kommunales [Ministry for Internal and Communal Affairs]) (2017) NRW-Einbruchszahlen gehen im ersten Quartal 2017 30% zurück—Neue Prognose-Software eingesetzt. http://www.mik.nrw.de/startseite/kampf-gegen-einbrueche/skala.html. Accessed 23 Aug 2017

  68. Mohler GO et al (2011) Self-exciting point process modeling of crime. J Am Stat Assoc 106:100–108. https://doi.org/10.1198/jasa.2011.ap09546

    Article  Google Scholar 

  69. Mohler GO et al (2015) Randomized controlled field trials of predictive policing. J Am Stat Assoc 110:1399–1411. https://doi.org/10.1080/01621459.2015.1077710

    Article  Google Scholar 

  70. Norris C, Armstrong G (1999) The maximum surveillance society: the rise of CCTV. Berg, Oxford, New York

    Google Scholar 

  71. Perry WL et al. (2013) Predictive policing: the role of crime forecasting in law enforcement operations. Santa Monica et al: RAND. http://www.rand.org/content/dam/rand/pubs/research_reports/RR200/RR233/RAND_RR233.pdf. Accessed 28 Feb 2017

  72. Polizeipräsident Berlin (2016) Kollege Computer hilft bei der Kriminalitätsprognose, 10.08.2016. https://www.berlin.de/polizei/polizeimeldungen/pressemitteilung.507506.php. Accessed 24 Aug 2017

  73. Saunders J, Hunt P, Hollywood JS (2016) Predictions put into practice: a quasi-experimental evaluation of Chicago’s predictive policing pilot. J Exp Criminol 12:347–371

    Article  Google Scholar 

  74. Schneier B (2003) Beyond fear: thinking sensibly about security in an uncertain world. Copernicus, New York

    Google Scholar 

  75. Schürmann D (2015) “SKALA”. Predictive Policing als praxisorientiertes Projekt der Polizei NRW. Presentation on the KI-Forum of the BKA on 25.06.2015, Wiesbaden. https://www.bka.de/SharedDocs/Downloads/DE/Publikationen/ForumKI/ForumKI2015/kiforum2015SchuermannPositionspapier.html. Accessed 23 Aug 2017

  76. Schweer T (2015) “Vor dem Täter am Tatort”—Musterbasierte Tatortvorhersagen am Beispiel des Wohnungseinbruchs. Die Krim 32:13–16

    Google Scholar 

  77. Sidebottom A, Wortley R (2016) Environmental Criminology. In: Piquero AR (ed) The handbook of criminological theory. Wiley, Chichester, pp 156–181

    Google Scholar 

  78. Sommerer L (2017) Geospatial predictive policing—research outlook & a call for legal debate. Neue Kriminalpolitik 29:147–164. https://doi.org/10.5771/0934-9200-2017-2-147

    Article  Google Scholar 

  79. StZ (Stuttgarter Zeitung) (2015) Die Politik steht unter Druck, 26.04.2015, http://www.stuttgarter-zeitung.de/inhalt.explodierende-einbruchszahlen-im-land-die-politik-steht-unter-druck.9b00787e-5329-463d-93ff-8a2ffc72215a.html. Accessed 25 Aug 2017

  80. Telep CW, Weisburd W (2013) Hot spots and place-based- policing. In: Bruinsma G, Weisburd D (eds) Encyclopedia of criminology and criminal justice. Springer, New York, pp 2352–2363

    Google Scholar 

  81. Townsley M, Homel R, Chaseling J (2003) Infectious burglaries. A test of the near repeat hypothesis. Br J Criminol 43:615–633

    Article  Google Scholar 

  82. Uchida CD (2014) Predictive policing. In: Bruinsma G, Weisburd W (eds) Encyclopedia of criminology and criminal justice. Springer, New York, pp 3871–3880

    Google Scholar 

  83. Valverde M (2001) Governing security, governing through security. In: Daniels RJ, Macklem P, Roach K (eds) The security of freedom: essays on Canada’s anti-terrorism bill. University of Toronto Press, Toronto, pp 82–92

    Google Scholar 

  84. Wang X, Gerber MS, Brown DE (2012) Automatic crime prediction using events extracted from twitter posts. In: Shanchieh JY, Greenberg AM, Endsley M (eds) Social computing, behavioral-cultural modeling and prediction. Springer, Berlin, Heidelberg, pp 231–239

    Google Scholar 

  85. Weinberg AM (1994) The first nuclear era: the life and times of a technological fixer. AIP Press, New York

    Google Scholar 

  86. Wieselmann B (2015) Prognosesoftware ‘PRECOBS’: computer gegen Einbrecher, 31.10.2015. http://www.swp.de/ulm/nachrichten/suedwestumschau/prognosesoftware-_’PRECOBS’_-computer-gegen-einbrecher-11815700.html. Accessed 25 Aug 2015

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The research for this paper was funded by the Fritz Thyssen foundation (Award Number

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Egbert, S. About Discursive Storylines and Techno-Fixes: The Political Framing of the Implementation of Predictive Policing in Germany. Eur J Secur Res 3, 95–114 (2018). https://doi.org/10.1007/s41125-017-0027-3

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  • Security discourse
  • Security technologies
  • Predictive policing
  • Crime risks
  • Political framing
  • Domestic burglary