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On contextuality in behavioural data.

Ehtibar N DzhafarovJanne V KujalaVíctor H CervantesRu ZhangMatt Jones
Published in: Philosophical transactions. Series A, Mathematical, physical, and engineering sciences (2016)
Dzhafarovet al.(Dzhafarovet al.2016Phil. Trans. R. Soc. A374, 20150099. (doi:10.1098/rsta.2015.0099)) reviewed several behavioural datasets imitating the formal design of the quantum-mechanical contextuality experiments. The conclusion was that none of these datasets exhibited contextuality if understood in the generalized sense proposed by Dzhafarovet al.(2015Found. Phys.7, 762-782. (doi:10.1007/s10701-015-9882-9)), while the traditional definition of contextuality does not apply to these data because they violate the condition of consistent connectedness (also known as marginal selectivity, no-signalling condition, no-disturbance principle, etc.). In this paper, we clarify the relationship between (in)consistent connectedness and (non)contextuality, as well as between the traditional and extended definitions of (non)contextuality, using as an example the Clauser-Horn-Shimony-Holt inequalities originally designed for detecting contextuality in entangled particles.
Keyphrases
  • electronic health record
  • big data
  • rna seq
  • machine learning
  • spinal cord injury
  • spinal cord
  • quantum dots