The DOI matches its Crossref record; 2 of the 2 references it cites were found in a registry or an index.
Surveillance and capture: Two models of privacy
Abstract
Two models of privacy issues are contrasted. The surveillance model employs visual metaphors (e.g., “Big Brother is watching") and derives from historical experiences of secret police surveillance. The less familiar capture model employs linguistic metaphors and has deep roots in the practices of applied computing through which human activities are systematically reorganized to allow computers to track them in real time. The capture model is discussed with reference to systems in numerous domains.
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Cites
Coase, R. H. (1937) · Economica · doi:10.1111/j.1468-0335.1937.tb00002.x · Cited by 23,972
Searle, J. R. (1969) · doi:10.1017/cbo9781139173438 · Cited by 11,718
Cited by
Suchman, L. (1995) · Communications of the ACM · doi:10.1145/223248.223263 · Cited by 991
Code/Space: Software and Everyday Life
Kitchin, R., & Dodge, M. (2011) · doi:10.7551/mitpress/9780262042482.001.0001 · Cited by 964
Newlands, G. (2021) · Organization Studies · doi:10.1177/0170840620937900 · Cited by 439
The matter of ‘virtual’ geographies
Kinsley, S. (2014) · Progress in Human Geography · doi:10.1177/0309132513506270 · Cited by 313
Automation, APIs and the distributed labour of platform pedagogies in google classroom
Perrotta, C., Gulson, K. N., Williamson, B., & Witzenberger, K. (2021) · Critical Studies in Education · doi:10.1080/17508487.2020.1855597 · Cited by 208
Metadata
- Authors
- Agre, P. E.
- Venue
- The Information Society
- Publisher
- Informa UK Limited
- Published
- 1994-04
- Volume
- 10
- Issue
- 2
- Pages
- 101-127
- ISSN
- 0197-2243 (ISSN-L)
- 1087-6537
- OpenAlex
- W2158083516
- Cited by
- 401
- References
- 2
- FWCI
- 16.52
- Type
- journal article
- Language
- en
- Open access
- closed
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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.