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  1. The Semantics Latent in Shannon Information.M. C. Isaac Alistair - 2019 - British Journal for the Philosophy of Science 70 (1):103-125.
    The lore is that standard information theory provides an analysis of information quantity, but not of information content. I argue this lore is incorrect, and there is an adequate informational semantics latent in standard theory. The roots of this notion of content can be traced to the secret parallel development of an information theory equivalent to Shannon’s by Turing at Bletchley Park, and it has been suggested independently in recent work by Skyrms and Bullinaria and Levy. This paper explicitly articulates (...)
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  • (2 other versions)Unmixing for Causal Inference: Thoughts on McCaffrey and Danks.Kun Zhang & Madelyn R. K. Glymour - 2018 - British Journal for the Philosophy of Science 71 (4):1319-1330.
    McCaffrey and Danks have posed the challenge of discovering causal relations in data drawn from a mixture of distributions as an impossibility result in functional magnetic resonance. We give an algorithm that addresses this problem for the distributions commonly assumed in fMRI studies and find that in testing, it can accurately separate data from mixed distributions. As with other obstacles to automated search, the problem of mixed distributions is not an impossible one, but rather a challenge. 1Introduction2Background3Addressing the Problem4Discussion.
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