View Full Version : Sokal's Hoax and Bias

Mel Siff
05-18-2002, 02:26 AM
In an earlier letter I referred to the "Sokal hoax", but omitted to include
this reference:

Alan D. Sokal Transgressing the Boundaries: Towards a Transformative
Hermeneutics of Quantum Gravity
Social Text 46/47, pp217-252 (spring/summer 1996).

Review of Sokal's Hoax by renowned physicist, Dr Steven Weinberg

Like many other scientists, I was amused when I heard about the prank played
by the NYU mathematical physicist Alan Sokal, who late in 1994 submitted a
sham article to the cultural studies journal Social Text. In the article
Sokal reviewed various current topics in physics and mathematics, and, tongue
in cheek, drew various cultural, philosophical, and political morals that he
felt would appeal to fashionable academic commentators who question the
claims of science to objectivity.





An additional commentary on scientific bias:


Confirmation Bias

"It is the peculiar and perpetual error of the human understanding to be more
moved and excited by affirmatives than by negatives." --Francis Bacon

Confirmation bias refers to a type of selective thinking whereby one tends to
notice and to look for what confirms one's beliefs, and to ignore, not look
for, or undervalue the relevance of what contradicts one's beliefs

... This tendency to give more attention and weight to data that supports
our preconceptions and beliefs than we do to contrary data is especially
pernicious when our preconceptions and beliefs are little more than
prejudices. If our beliefs are firmly established upon solid evidence and
valid confirmatory experiments, the tendency to give more attention and
weight to data that fits with our beliefs should not lead us astray as a
rule. Of course, if we become blinded to evidence truly refuting a favored
hypothesis, we have crossed the line from reasonableness to closed-mindedness.

Researchers are sometimes guilty of confirmation bias by setting up
experiments or framing their data in ways that will tend to confirm their
hypotheses. They compound the problem by proceeding in ways that avoid
dealing with data that would contradict their hypotheses.


Dr Mel C Siff
Denver, USA

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