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J M Keynes’s Method in the A Treatise on Probability, Inexact Measurement and Approximation Using Non Additive Upper and Lower Probabilities, Is a Formal, Inductive Logic Built on G. Boole’s Original Boolean Algebra and Logic: It Has Nothing to Do With ‘…A Given List of Possible Behaviors.’

Authors: Michael Emmett Brady;

J M Keynes’s Method in the A Treatise on Probability, Inexact Measurement and Approximation Using Non Additive Upper and Lower Probabilities, Is a Formal, Inductive Logic Built on G. Boole’s Original Boolean Algebra and Logic: It Has Nothing to Do With ‘…A Given List of Possible Behaviors.’

Abstract

J.M. Keynes’s method in the A Treatise on Probability, inexact measurement and approximation using non additive upper and lower probabilities, is a formal, inductive logic built on G. Boole’s original Boolean Algebra and Logic. It has nothing to do with "…a given list of possible behaviors. ” (Almeida, no date). Keynes’s approach uses intuition, induction, pattern recognition and analogy as a foundation, using different degrees of similarity and dissimilarity connecting the past to the future, to analyze and solve existing problems with major future implications. The researcher, using Keynesian induction and intuition, is able to discover relevant connections from the past that may very likely play a deciding role in unsolved problems extending and dealing with the future. A researcher does not create a solution out of nothing based on his imagining things about the future whimsically when he is daydreaming or sleeping and having dreams.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
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