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Le risorse e il controllo. I big data oltre il mito
Titolo Rivista: SOCIOLOGIA E RICERCA SOCIALE  
Autori/Curatori: Paolo Parra Saiani 
Anno di pubblicazione:  2016 Fascicolo: 109 Lingua: Italiano 
Numero pagine:  14 P. 28-41 Dimensione file:  76 KB
DOI:  10.3280/SR2016-109004
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Cuts in research and in particular to social research periodically incite petitions and warnings from the main European scientific associations. What are the consequences and challenges posed by the reduction in resources available for research purposes? Can Big Data be an answer, a solution, a way to access the information in a cost-effective way? Or will they increase the gap between rich and poor universities, and the level of inequality between researchers? Is it a way to finally lay the foundations for the society of information and knowledge glimpsed in recent decades, or will the growing importance of Big Data in the research be accompanied by problems still not entirely clear?


  1. S.L. Daza (2012), «Complicity as Infiltration: The (Im)possibilities of Research With/in Nsf Engineering Grants in the Age of Neoliberal Scientism», Qualitative Inquiry, XVIII, 9, pp. 773-86,, DOI: 10.1177/1077800412453021
  2. O. de Leonardis, F. Neresini (2015), «Introduzione», Rassegna italiana di sociologia, LVI, 34, pp. 371-8,, DOI: 10.1423/81796
  3. M. Denscombe (2010), Ground Rules for Social Research. Guidelines for Good Practice, Maidenhead, Open University Press.
  4. D. Fisher (1980), «American Philanthropy and the Social Sciences in Britain, 1919-1939: The Reproduction of a Conservative Ideology», Sociological Review, 28, pp. 277-315,, DOI: 10.1111/j.1467-954X.1980.tb00366.x
  5. D. Fisher (1983), «The Role of Philanthropic Foundations in the Reproduction and Production of Hegemony: Rockefeller Foundations and the Social Sciences», Sociology, 17, pp. 206-33,, DOI: 10.1177/0038038583017002004
  6. D. Fisher (1984), «Philanthropic Foundations and the Social Sciences: A Response to Martin Bulmer», Sociology, 18, pp. 580-7,, DOI: 10.1177/0038038584018004009
  7. D. Fisher (1993), Fundamental Development of the Social Sciences, Ann Arbor, University of Michigan Press.
  8. C. Gini (1941), «Alle basi del metodo statistico. Il principio della compensazione degli errori accidentali e la legge dei grandi numeri», Metron, XIV, 2-3-4, pp. 173-240.
  9. S.A. Golder, M.W. Macy (2014), «Digital Footprints: Opportunities and Challenges for Online Social Research», Annual Review of Sociology, 40, pp. 129-52,, DOI: 10.1146/annurev-soc-071913-043145
  10. E.J. Hackett (2014), «Academic Capitalism», Science, Technology, & Human Values, XXXIX, 5, pp. 635-8,, DOI: 10.1177/0162243914540219
  11. P.M. Hauser (1982), Interview, in J. Platt (1996), A History of Sociological Research Methods in America. 1920-1960, Cambridge, Cambridge University Press. 40
  12. P.M. Hirsch (1972), «Processing Fads and Fashions: An Organization-Set Analysis of Cultural Industry Systems», American Journal of Sociology, 77, 4, pp. 639-59,, DOI: 10.1086/225192
  13. J. Kaiser (2016), «Funding for Key Data Resources in Jeopardy», Science, CCCLI, 6268, January 1, p. 14,, DOI: 10.1126/science.351.6268.14
  14. S. Kumar, F. Morstatter, H. Liu (2014), Twitter Data Analytics, New York, Springer.
  15. D. Lazer, A. Pentland, L. Adamic, S. Aral, A.L. Barabási, D. Brewer, N. Christakis, N. Contractor,
  16. J. Fowler, M. Gutmann, T. Jebara, G. King, M. Macy, D. Roy, M. Van Alstyne (2009), «Computational Social Science», Science, 323, 6 February, pp. 721-3,, DOI: 10.1126/science.1167742
  17. D. Lazer, R. Kennedy, G. King, A. Vespignani (2014), «Big Data. The Parable of Google Flu: Traps in Big Data Analysis», Science, 343, 14 March, pp. 1203-5,, DOI: 10.1126/science.1248506
  18. S. Leonelli (2014), «What Difference does Quantity make? On the Epistemology of Big Data in Biology», Big Data and Society, April-June, pp. 1-11,, DOI: 10.1177/2053951714534395
  19. V. Mayer-Schönberger, K. Cukier (2013), Big Data. A Revolution that will transform how we live, work, and think, Boston, Houghton Mifflin Harcourt.
  20. D. Mazzonis, M. Cini (1981), Il gioco delle regole. L’evoluzione delle strutture del sapere scientifico, Milano, Feltrinelli.
  21. M. Palumbo, E. Garbarino (2006), Ricerca sociale: metodo e tecniche, Milano, FrancoAngeli.
  22. P. Parra Saiani (2009), Gli indicatori sociali, Milano, FrancoAngeli.
  23. P. Parra Saiani (2011), «Knowledge and Participation: Which Democracy?», Revista Latinoamericana de Metodología de las Ciencias Sociales, I, 2, pp. 112-40.
  24. P. Parra Saiani (2012), Democracy and Public Knowledge. An Issue for Social Indicators, in F. Maggino, G. Nuvolati (eds.), Quality of Life in Italy: researches and reflections, Springer – Social Indicators Book Series, pp. 225-42,, DOI: 10.1007/978-94-007-3898-0_12
  25. P. Parra Saiani (2015a), «La sociología frente a los nuevos ataques cientificistas», Revista Latinoamericana de Metodología de las Ciencias Sociales, V, 1, pp. 1-22.
  26. P. Parra Saiani (2015b), Sobre la retorica cientificista: algunas consecuencias metodológicas y políticas del debate epistemológico, in A. Marradi (comp.), Las Ciencias Sociales ¿seguirán imitando a las Ciencias duras? Un Simposio a distancia, Buenos Aires, Editorial Antigua, pp. 185-201.
  27. J. Picó (2001), «El protagonismo de las fundaciones americanas en la institucionalización de la sociología (1945-1960)», Papers, 63/64, pp. 11-32.
  28. R. Pielke Jr (2010), «In Retropect: Science – The Endless Frontier», Nature, 466, pp. 922-3,, DOI: 10.1038/466922a
  29. J. Platt (1996), A History of Sociological Research Methods in America. 1920-1960, Cambridge, Cambridge University Press.
  30. D.J. Price (1963), Little Science, Big Science, New York, Columbia University Press.
  31. D. Ross (2003), Changing Contours of the Social Science Disciplines, in T.M. Porter, D. Ross (eds.), The Cambridge History of Science, vol. 7: The Modern Social Sciences, Cambridge, Cambridge University Press, pp. 205-37.
  32. A.R. Shaikh, A.J. Butte, S.D. Schully, W.S. Dalton, M.J. Khoury, B.W. Hesse (2014), «Collaborative Biomedicine in the Age of Big Data: The Case of Cancer», Journal of Medical Internet Research, XVI, 4, e101;, DOI: 10.2196/jmir.2496
  33. P.E. Stephan (2012), How Economics shapes Science, Harvard, Harvard University Press.
  34. J.Q. Stewart (1947), «Suggested Principles of “Social Physics”», Science, CVI, 2748, August 29, pp. 179-80,, DOI: 10.1525/aa.1947.49.4.02a00300
  35. C. Strong (2015), Humanizing Big Data. Marketing at the Meeting of Data, Social Science and Consumer Insight, London, KoganPage. R. Tinati, S. Halford, L. Carr, C. Pope (2014), «Big Data: Methodological Challenges and Approaches for Sociological Analysis», Sociology, IIL, 4, pp. 663-81,, DOI: 10.1177/0038038513511561
  36. S.P. Turner (2014), American Sociology from Pre-disciplinay to Post-normal, Basingstoke, Palgrave Macmillan.
  37. T. Vigen (2015), Spurious Correlations, New York, Hachette Books.
  38. W.F. Whyte (1943), Street Corner Society. The Social Structure of an Italian Slum, Chicago, Chicago University Press, 4a ed. 1993.
  39. Y. Xie (2014), «“Undemocracy”: Inequalities in Science», Science, 344, May 23, pp. 809-10,, DOI: 10.1126/science.1252743
  40. J. Zaino (2013), «The War against Political Science», Inside Higher Ed., June 30.
  41. G.K. Zipf (1949), Human Behavior and the Principle of Least Effort. An Introduction to Human Ecology, Cambridge, Addison-Wesley Press.
  42. C.F. Adams (1877), Memoirs of John Quincy Adams, Comprising Portions of His Diary from 1795 to 1848, vol. XII, Philadelphia, Lippincott.
  43. G. Alchon (1985), The Invisible Hand of Planning, Princeton, Princeton University Press.
  44. C. Anderson (2008), «The End of Theory: The Data Deluge makes the Scientific Method Obsolete », Wired, June 23, http://www.wired.com/2008/06/pb-theory.
  45. R.F. Arnove (ed.) (1980), Philanthropy and Cultural Imperialism: The Foundations at Home and Abroad, Bloomington, Indiana University Press.
  46. M. Baker (2012), «Gene Data to hit Milestone», Nature, 487, 19 July, pp. 282-3,, DOI: 10.1038/487282a
  47. R.C. Bannister (1987), Sociology and Scientism. The American Quest for Objectivity, 1880-1940, Chapel Hill, University of North Carolina Press.
  48. M. Beretta (2002), Storia materiale della scienza. Dal libro ai laboratori, Milano, Bruno Mondadori.
  49. C. Bezzi, M. Palumbo (1995), Questionario e dintorni, Perugia, Gramma.
  50. L. Bickman, D.J. Rog (2009), The Sage Handbook of Applied Social Research Methods, Thousand Oaks, Sage, 2nd ed.
  51. d. boyd, K. Crawford (2012), «Critical Questions for Big Data. Provocations for a Cultural, Technological, and Scholarly Phenomenon», Information, Communication & Society, XV, 5, pp. 662-9,, DOI: 10.1080/1369118X.2012.678878.P.Boyle(2013),«AUKViewontheU.S.AttackonSocialSciences»,Science,341,August16,p.719,doi:10.1126/science.1242563
  52. E.R. Brown (1979), Rockefeller Medicine Men: Medicine and Capitalism in America, Berkeley, University of California Press.
  53. M. Bulmer (1984), «Philanthropic Foundations and the Development of the Social Sciences in the Early Twentieth Century: A Reply to Donald Fisher», Sociology, 18, pp. 572-9,, DOI: 10.1177/0038038584018004008
  54. A. Butte (2012), What if you outsource Three Double-blind Mice?, Tedmed2012, Washington, http://www.tedmed.com/talks/show?id=7340.
  55. C.S. Calude, G. Longo (2016), The Deluge of Spurious Correlations in Big Data, in Foundations of Science, in press.
  56. L. Cannavò (2007), Introduzione, in L. Cannavò, L. Frudà (a c. di), Ricerca sociale. Dal progetto dell’indagine alla costruzione degli indici, Roma, Carocci, pp. 13-50.
  57. L. Cannavò, L. Frudà (a c. di) (2007), Ricerca sociale. Dal progetto dell’indagine alla costruzione degli indici, Roma, Carocci.
  58. M. Caselli (2005), Indagare col questionario. Introduzione alla ricerca sociale di tipo standard, Milano, Vita e Pensiero.
  59. J.M. Chapoulie (2001), La tradition sociologique de Chicago. 1892-1961, Paris, Seuil.
  60. K. Conger (2012), «Big Data. What It means for Our Health and the Future of Medical Research », Stanford Medicine, Summer, pp. 6-15.
  61. D. Conley, J.L. Aber, H. Brady, S. Cutter, C. Eckel, B. Entwisle, D. Hamilton, S. Hofferth, K. Hubacek, E. Moran, J. Scholz (2015), «Big Data. Big Obstacles», The Chronicle of Higher Education, 2 febbraio, http://chronicle.com/article/Big-Data-Big-Obstacles/151421.

Paolo Parra Saiani, in "SOCIOLOGIA E RICERCA SOCIALE " 109/2016, pp. 28-41, DOI:10.3280/SR2016-109004

   

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