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Causal Necessity: Pragmatic Investigation of the Necessity of Laws Hardcover – July 1, 1980

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Langue

anglais

Éditeur

Description New Haven : Yale University Press, 1980

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Causal Necessity: Pragmatic Investigation of the Necessity of Laws Hardcover – July 1, 1980
by Brian Skyrms (Author)
Product details

Hardcover: 176 pages
Publisher: Yale University Press; First Edition edition (July 1, 1980)
Language: English
ISBN-10: 0300023391
ISBN-13: 978-0300023398
Shipping Weight: 14.1 ounces

Format BookBook
Author
Skyrms, Brian

Description New Haven : Yale University Press, 1980
xii, 205 p. ; 22 cm.
ISBN 0300023391
Notes

Includes index.

Bibliography: p. 189-201.
Subjects Necessity (Philosophy) | Law -- Philosophy. | Causation. | Pragmatics.
RICHARD
OTTE
CRITICAL
REVIEW:
BRIAN
SKYRMS,
CA
USAL
NECESSITY
(Received
15
November,
1982)
In
a
recent
book,
Causal
Necessity,
Brian
Skyrms
has
attempted
to
deal
with
many
of
the
major
problems
facing
philosophers
today.
1
The
central
idea
of
his
book
is
that
invariance
is
the
key
to
understanding
many
of
these
prob-
lems.
The
idea
of
invariance
is
applied
to
problems
such
as
randomness,
epistemic
probabilities,
confirmation,
conditionals,
and
decision
theory.
In
this
article
I
will
briefly
present
the
essence
of
his
position
on
invariance,
and
then
critically
analyze
it.
The
first
part
of
Skyrms'
book
deals
with
propensities
and
statistical
laws.
Skyrms
believes
that
propensities
are
the
probabilities
that
play
a
role
in
statistical
laws,
and
his
discussion
of
statistical
laws
assumes
this.
Statistical
laws
tell
us
that
certain
systems
have
a
stable
probability;
these
stable
proba-
bilities
are
propensities.
Skyrrns
discusses
in
detail
what
it
means
for
a
proba-
bility
to
be
stable,
and
he
defines
a
notion
of
resiliency
which
is
supposed
to
capture
the
idea
of
invariance
and
stability.
Resiliency
is
defined
as:
Resiliency
of
Pt(q)s
being
a
=
1
-
Maxila
-Pt-(q)[
over
Pl
"
Pn
(where
the
Ptis
are
1
.
"'"
gotten
by
conditionalizing
on
some
truth-functional
compound
of
the
pi
s
which
is
logically
consistent
with
both
q
and
its
negation)
(pp.
11-12).
In
this
definition
the
PiS
are
properties
or
experimental
factors
which
are
considered
relevant
to
the
occurrence
of
q.
Resiliency
measures
the
indepen-
dence
of
q
and
these
factors;
thus
resiliency
is
a
measure
of
stability,
in-
dependence,
and
invariance.
If
the
resiliency
of
a
certain
proposition
is
1,
then
we
know
that
the
proposition
is
necessary
or
invariant.
Degrees
of
resiliency
less
than
one
correspond
to
cases
of
approximate
independence
or
approximate
invariance.
Thus
we
can
look
at
the
resiliency
of
a
proposition
to
determine
how
close
we
are
to
the
ideal.
There
are,
however,
some
problems
that
arise
with
this
def'mition
of
resiliency.
One
problem
concerns
the
way
in
which
the
degree
of
resiliency
is
measured.
Resiliency
is
measured
by
the
maximum
difference
between
a
and
the
probability
of
q
conditional
on
various
truth
functional
cornbina-
426
RICHARD
OTTE
tions
of
the
Pi
s.
But
there
are
cases
in
which
this
difference
is
not
an
adequate
measure
of
the
degree
of
invariance
of
a
proposition.
Events
with
a
very
low
probability
can
be
quite
variant,
and
yet
be
highly
resilient
according
to
Skyrms'
definition.
Suppose
that
we
have
a
certain
atom
with
a
large
half
life;
the
probability
of
this
atom
decaying
in
a
certain
time
interval,
say
one
year,
will
be
quite
small.
Even
if
conditional
on
one
of
the
Pi
s
the
probability
of
decay
is
doubled,
the
decay
of
the
atom
is
highly
resilient,
because
of
the
small
difference
between
the
actual
probability
values.
If
Pr(q)
is
low
enough,
the
difference
between
Pr(q)
and
2Pr(q)
will
be
very
small.
A
small
difference
between
two
numbers
is
compatible
with
a
large
ratio
between
them.
This
seems
to
indicate
that
the
difference
between
these
two
numbers
cannot
be
an
adequate
measure
of
resiliency
or
invariance.
Contrast
the
previous
example
with
another
example
of
an
atom
which
has
a
much
shorter
half
life.
The
probability
that
this
atom
may
decay
in
the
same
time
period
may
be
much
higher,
let
us
say
around
0.25.
If,
relative
to
one
of
the
Pi
s,
the
probability
of
this
atom
decaying
also
doubles,
it
will
not
be
a
very
resilient
probability.
In
this
case
the
resiliency
would
be
0.75,
which
is
not
nearly
as
high
as
the
resiliency
of
the
other
example.
The
only
difference
between
this
example
and
the
previous
one
is
the
actual
probabili-
ty
values
involved.
It
seems
that
if
one
of
these
is
highly
invariant,
so
should
the
other
be.
The
same
atomic
theory
is
behind
both
of
them:
if
one
of
these
probabilities
is
a
propensity,
they
should
both
be
propensities.
Another
example
which
makes
the
same
point
is
as
follows.
The
probabili-
ty
of
an
atom
decaying
in
a
certain
time
interval
may
be
very
low,
and
thus
even
if
there
is
a
Pi
which
doubles
that
probability,
it
will
be
highly
resilient.
However,
the
probability
that
the
same
atom
will
decay
in
a
much
larger
time
interval
will
be
much
larger,
in
which
case
it
is
likely
that
the
decay
of
the
atom
will
not
be
highly
resilient.
The
only
difference
in
this
example
is
the
longer
time
intervals
involved,
which
results
in
different
probability
values.
But
it
seems
clear
that
the
longer
time
interval
does
not
affect
the
indepen-
dence
of
the
propositions
involved;
all
it
does
is
change
the
Images
Skyrms, Brian - Causal Necessity: Pragmatic Investigation of the Necessity of Laws Hardcover – July 1, 1980
Skyrms, Brian - Causal Necessity: Pragmatic Investigation of the Necessity of Laws Hardcover – July 1, 1980
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