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Volume 1, Issue 2

From the Editors

This marks our second issue of Communications of the Blyth
Institute (CBI). As usual, this issue of CBI includes papers
on a diverse array of topics, including machine learning,
consciousness, philosophy of science, and mathematics.

Issue Focus

The focus of this issue is philosophy of science. To that
end, we have included papers on:

• The shifts required for science in thinking about con-
sciousness (Rakover),

• How to quantifying generalizations (Bartlett and Hol-
loway),

• Uncovering hidden usage of theology in science (Hunter
and Dilley and Tafacory),

• Null hypothesis construction (Hunter),

• Science education (Dilley and Tafacory), and

• The nature of truth (Koch).

Every endeavor of knowledge involves both epistemology
(how do we know that something is true?) and ontology
(what is the structure of truth?). These philosophical ques-
tions frame the outlines of how science works. While some
believe that the ontology and epistemology of science are set
in stone, in truth it is a continuously-changing enterprise—
hopefully for the better.

Philosophy of science is used both internally (for scientists
to analyze and adjust their own thinking) and externally
(for non-scientists to judge the quality and applicability of
the outputs of science). Those who discount the value of
philosophy to science simply show their ignorance of the
subject. The basic rules of inference come from philoso-
phy. The identity of indiscernibles, the principle of suffi-
cient reason, and the law of non-contradiction are indis-
pensible to scientific reasoning, but they originate in meta-
physics. Many of the advances of science, such as null hy-
pothesis testing, are actually philosophical advances about
the nature of epistemology. So, while many in the popular

press wonder how useful philosophy is to science, the actual
practice of science is bathed in philosophy.

We are thankful to all of our contributors for maintaining
high standards of academic excellence.

Criticism Welcome

However, the progress of any model requires criticism as
well. If you have a comment or criticism of a paper pub-
lished in CBI, we encourage you to submit a letter (or even
a full rebuttal paper) for publication. More than anything,
CBI exists to facilitate communication among researchers
in a variety of fields, and that includes well-founded criti-
cism.

Cross-field analysis and criticism is also encouraged. Dif-
ferent disciplines bring different mindsets, and applying
knowledge and perspectives from a diversity of fields helps
to sharpen and refine ideas more effectively.

Future Issue Focus

The actual focus of each of our issues is dependent on the
submissions we receive and pass peer review. However, we
are hoping to put together an issue focusing on machine
learning and artificial intelligence in the near future. If you
work in that area, we hope you consider us for publication.

—The CBI Editors


