The DOI matches its Crossref record.
The Taming of Chance
Abstract
In this important study Ian Hacking continues the enquiry into the origins and development of certain characteristic modes of contemporary thought undertaken in such previous works as the best-selling The Emergence of Probability. Professor Hacking shows how by the late-nineteenth century it became possible to think of statistical patterns as explanatory in themselves, and to regard the world as not necessarily deterministic in character. In the same period the idea of human nature was displaced by a model of normal people with laws of dispersion. These two parallel transformations fed into each other, so that chance made the world seem less capricious: it was legitimated because it brought order out of chaos. Combining detailed scientific historical research with characteristic philosophic breadth and verve, The Taming of Chance brings out the relations between philosophy, the physical sciences, mathematics and the development of social institutions, and provides a unique and authoritative analysis of the 'probabilisation' of the western world.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cited by
The Politics of Life Itself: Biomedicine, Power, and Subjectivity in the Twenty-First Century
Rose, N. (2007) · doi:10.1515/9781400827503 · Cited by 3,294
Espeland, W. N., & Stevens, M. L. (2008) · European Journal of Sociology · doi:10.1017/s0003975609000150 · Cited by 1,265
Hacking, I. (2002) · In the Scope of Logic, Methodology and Philosophy of Science · doi:10.1007/978-94-017-0475-5_13 · Cited by 838
Self-citation(2013) · Cited by 619
“Big Data Surveillance: The Case of Policing
Brayne, S. (2017) · American Sociological Review · doi:10.1177/0003122417725865 · Cited by 596
Algorithmic War: Everyday Geographies of the War on Terror
Amoore, L. (2009) · Antipode · doi:10.1111/j.1467-8330.2008.00655.x · Cited by 410
Ratings and Rankings: Voodoo or Science?
Paruolo, P., Saisana, M., & Saltelli, A. (2013) · Journal of the Royal Statistical Society Series A: Statistics in Society · doi:10.1111/j.1467-985x.2012.01059.x · Cited by 349
Governing risky individuals: The role of psychiatry in new regimes of control
Rose, N. (1998) · Psychiatry, Psychology and Law · doi:10.1080/13218719809524933 · Cited by 345
Amundson, R. (2000) · Studies in History and Philosophy of Science Part C: Studies in History and Philosophy of Biological and Biomedical Sciences · doi:10.1016/s1369-8486(99)00033-3 · Cited by 308
Whitson, J. R. (2013) · Surveillance & Society · doi:10.24908/ss.v11i1/2.4454 · Cited by 300
A Disciplinary Perspective on the Epistemological Status of Risk
Althaus, C. E. (2005) · Risk Analysis · doi:10.1111/j.1539-6924.2005.00625.x · Cited by 286
Ruppert, E., Isin, E., & Bigo, D. (2017) · Big Data & Society · doi:10.1177/2053951717717749 · Cited by 264
Hannah-Moffat, K. (2019) · Theoretical Criminology · doi:10.1177/1362480618763582 · Cited by 236
Life beyond big data–governing with little analytics
Amoore, L., & Piotukh, V. (2015) · Economy and Society · doi:10.1080/03085147.2015.1043793 · Cited by 187
Data retention and the panoptic society: the social benefits of forgetfulness
Blanchette, J.-F., & Johnson, D. G. (2002) · The Information Society · doi:10.1080/01972240252818216 · Cited by 178
Waters, F., Chiu, V., Atkinson, A., & Blom, J. D. (2018) · Frontiers in Psychiatry · doi:10.3389/fpsyt.2018.00303 · Cited by 165
Social Payments: Innovation, Trust, Bitcoin, and the Sharing Economy
Collaborative:, F. O. M. R., Nelms, T. C., Maurer, B., Swartz, L., & Mainwaring, S. (2018) · Theory, Culture & Society · doi:10.1177/0263276417746466 · Cited by 161
Epidemiology and social sciences: towards a critical reengagement in the 21st century
Krieger, N. (2000) · Epidemiologic Reviews · doi:10.1093/oxfordjournals.epirev.a018014 · Cited by 152
Patient data as medical facts: social media practices as a foundation for medical knowledge creation
Kallinikos, J., & Tempini, N. (2014) · Information Systems Research · doi:10.1287/isre.2014.0544 · Cited by 141
Seven dimensions of contemporary participation disentangled
Kelty, C., Panofsky, A., Currie, M., Crooks, R., Erickson, S., Garcia, P., Wartenbe, M., & Wood, S. (2015) · Journal of the Association for Information Science and Technology · doi:10.1002/asi.23202 · Cited by 124
How the Ideology of Low Fat Conquered America
La Berge, A. F. (2007) · Journal of the History of Medicine and Allied Sciences · doi:10.1093/jhmas/jrn001 · Cited by 119
Heuristics of the algorithm: Big Data, user interpretation and institutional translation
Bolin, G., & Andersson Schwarz, J. (2015) · Big Data & Society · doi:10.1177/2053951715608406 · Cited by 107
The Forms and Limits of Insurance Solidarity
Lehtonen, T.-K., & Liukko, J. (2011) · Journal of Business Ethics · doi:10.1007/s10551-012-1221-x · Cited by 75
Understanding Risk in the Context of the Youth Criminal Justice Act
Maurutto, P., & Hannah-Moffat, K. (2007) · Canadian Journal of Criminology and Criminal Justice · doi:10.3138/cjccj.49.4.465 · Cited by 59
Truth machines: synthesizing veracity in AI language models
Munn, L., Magee, L., & Arora, V. (2024) · AI & SOCIETY · doi:10.1007/s00146-023-01756-4 · Cited by 65
Clinical judgement in the era of big data and predictive analytics
Chin‐Yee, B., & Upshur, R. (2018) · Journal of Evaluation in Clinical Practice · doi:10.1111/jep.12852 · Cited by 59
Building truths in AI: Making predictive algorithms doable in healthcare
Henriksen, A., & Bechmann, A. (2020) · Information, Communication & Society · doi:10.1080/1369118x.2020.1751866 · Cited by 58
Warmth and wealth: re-imagining social class in taxonomies of good parenting
Jensen, T. (2010) · Studies in the Maternal · doi:10.16995/sim.86 · Cited by 57
Ethics of quantification: illumination, obfuscation and performative legitimation
Sareen, S., Saltelli, A., & Rommetveit, K. (2020) · Palgrave Communications · doi:10.1057/s41599-020-0396-5 · Cited by 45
Healy, D. (2006) · Global Pharmaceuticals · doi:10.1215/9780822387916-003 · Cited by 35
Everyday Uncertainty: How Blind People Use GenAI Tools for Information Access
Tang, X., Abdolrahmani, A., Gergle, D., & Piper, A. M. (2025) · Proceedings of the 2025 CHI Conference on Human Factors in Computing Systems · doi:10.1145/3706598.3713433 · Cited by 30
Contrasting approaches to projecting long-run global food security
Godfray, H. C. J., & Robinson, S. (2015) · Oxford Review of Economic Policy · doi:10.1093/oxrep/grv006 · Cited by 28
Making Sense of Neoliberal Securitization in Urban Policing and Surveillance
Deukmedjian, J. E. (2013) · Canadian Review of Sociology/Revue canadienne de sociologie · doi:10.1111/cars.12002 · Cited by 27
“The Narrative of the Number: Quantification in Criminal Court
Lynch, M. (2019) · Law & Social Inquiry · doi:10.1111/lsi.12334 · Cited by 22
The Profiling Potential of Computer Vision and the Challenge of Computational Empiricism
Goldenfein, J. (2019) · Proceedings of the Conference on Fairness, Accountability, and Transparency · doi:10.1145/3287560.3287568 · Cited by 21
Armstrong, N., & Agulnik, P. (2020) · HAU: Journal of Ethnographic Theory · doi:10.1086/711880 · Cited by 8
As Above, So Below. Astrology and the Inquisition in Seventeenth-Century New Spain
Avalos, A. (2007) · Cadmus - EUI Research Repository (European University Institute) · doi:10.2870/69590 · Cited by 8
Metadata
- Authors
- Hacking, I.
- Venue
- Cambridge University Press eBooks
- Publisher
- Cambridge University Press
- Published
- 1990-08-31
- OpenAlex
- W2012758517
- Cited by
- 3,586
- References
- 0
- FWCI
- 70.27
- Type
- book
- Language
- en
- Open access
- closed
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.