Living Multiples: How Large-scale Scientific Data-mining Pursues Identity and Differences
By Adrian Mackenzie, Ruth McNally. 2013
25 citations recorded by the source corpus.
Subfields: Computer Vision and Pattern Recognition, Molecular Biology, Statistical and Nonlinear Physics
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In Computer Vision and Pattern Recognition
In Molecular Biology
In Statistical and Nonlinear Physics
Citations in the corpus
- Scrutinizing an algorithmic technique: the Bayes classifier as interested reading of reality (2017, background): “Both molecules and people could no longer be described in deterministic terms when encountered as ‘ living multiples ’ (Mackenzie & McNally, 2013).”
- Locative media and data-driven computing experiments (2016, methodology): “…techniques, data-driven experiments simultaneously ‘flatten’ and ‘thicken’ certain worlds, dependent upon the techniques invented ‘to track or extract forms of identity, regularity or pattern that we are not able to see, make or say directly or immediately’ (Mackenzie and McNally, 2013: 73–5).”