Page 58 - MODES of EXPLANATION

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philosophical approaches to the world and, in light of the seemingly endless increases in the
variety and depths of “data” available to us, an ever-changing challenge to how we view the
make-up of the world itself.
“Facts are precisely what we do not have, only interpretations.” (Nietzsche, 1967)
“Everything we aim at is a reconstruction that links our knowledge of the world with
experience.” (Quine, 1985)
“According to one large family of views, scientific explanations essentially subsume a
phenomenon (or its description) under a general representation … Authors disagree
about the precise form that these representations should take: For Carl Hempel, they
are generalizations in first order logic; for Philip Kitcher they are argument schemas;
for Bechtel and Abrahamsen they are mental models; for Churchland, they are
prototype vectors; for Machamer, Darden and Craver, they are mechanism schemas.”
(Craver, 2014)
“The postmodern view, inspired by Derrida, Paul De Man, J. Hillis Miller, and
brought forward by Stanley Fish and Richard Rorty, implies that there can be an
infinite number of equally correct readings of a given text. Words as such do not
possess any meaning, it is the reader who endows them with one.” (de Sanctis, 2012)
In the quest for an explanation, one of the possible items we may seek to explain is how we
decide to afford (ascribe) ontic status to some pattern that we perceive to be evident in the
data we have encountered. This is often a background question for the person (team, scientist,
investigator) who has made the ontic ascription (attribution, decision), but it becomes a
central “how” or “why” to those who seek to better understand the consequences of the
status. These questions become ever more prominent when one attempts to assert some
causal attributes to the item. The issue becomes ever more pronounced when one realizes that
we often get things wrong. According to Gilovich (1991), most of our fellow human beings:
“(1) See what they want or expect to see.
(2) Misperceive random data.
(3) Over-generalize from incomplete data.
(4) Love a ‘good’ story.
(5) Accept what is plausible rather than what is real.
(6) Are strongly influenced by authority, the printed word, or what others around
them think.”
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