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A Peek Inside: How Provisional Ballots Can Cast Light Upon Voter ID and Turnout

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Name: APSA 2008 Annual Meeting
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http://www.apsanet.org


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MLA Citation:

Andersen, David. "A Peek Inside: How Provisional Ballots Can Cast Light Upon Voter ID and Turnout" Paper presented at the annual meeting of the APSA 2008 Annual Meeting, Hynes Convention Center, Boston, Massachusetts, Aug 28, 2008 <Not Available>. 2009-05-23 <http://www.allacademic.com/meta/p279824_index.html>

APA Citation:

Andersen, D. , 2008-08-28 "A Peek Inside: How Provisional Ballots Can Cast Light Upon Voter ID and Turnout" Paper presented at the annual meeting of the APSA 2008 Annual Meeting, Hynes Convention Center, Boston, Massachusetts Online <APPLICATION/PDF>. 2009-05-23 from http://www.allacademic.com/meta/p279824_index.html

Publication Type: Conference Paper/Unpublished Manuscript

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Associated Document Available All Academic Inc.
Associated Document Available Political Research Online
Associated Document Available APSA 2008 Annual Meeting

Document Type: application/pdf
Page count: 25
Word count: 1677
Text sample:

 
 
 A
Peek
Inside:
 Using
Provisional
Ballots
to
Explore
Photo
Identification
Laws

 and
Voter
Turnout
at
the
Polls
 
 
 
 David
Andersen
 PhD
Candidate
 Department
of
Political
Science
 Rutgers
University
 
 
 
 
 
 
 
 
 
 
 
 Prepared
for
delivery
at
the
2008
Annual
Meeting
of
the
 American
Political
Science
Association 
August
28‐31 
2008 A
Peek
Inside:
 Using
Provisional
Ballots
to
Explore
Photo
Identification
Laws

 and
Voter
Turnout
at
the
Polls
 Provisional
ballots
can
be
a
valuable
tool
in
assessing
how
electoral
 rules 
such
as
Indiana’s
new
photo
identification
law 
impact
voter
 turnout
within
the
polls
themselves.

They
provide
a
unique
 measurement
of
how
many
people
encounter
administrative
 difficulties
within
the
polls 
forcing
them
to
vote
via
alternative
 means.

They
also
leave
a
record
of
how
many
of
those
provisional
 votes
are
subsequently
verified
after
election
day.

This
paper
has
3
 major
aims:
1)
make
the
case
for
how
provisional
ballots
can
move
 forward
the
investigation
of
photo
identification
requirements 
2)
 generate
hypothesis
about
what
results
might
look
like 
and
3)
 examine
data
from
the
2006
election
cycle.

 Crawford
v.
Marion
County
Election
Board 
the
recent
Supreme
Court
case
 upholding
Indiana’s
controversial
photo
identification
requirement 
rested
upon
a
 state
legislature’s
ability
to
regulate
a
perceived
threat
to
the
electoral
system
via
 any
means
that
would
not
be
facially
discriminatory.

The
court
relied
upon
the
lack
 of
evidence
that
photo
identification
requirements
necessarily
suppressed
turnout
 among
disadvantaged
groups
in
its
ruling 
while
at
the
same
time
deciding
that
the
 law
did
not
require
the
demonstration
of
actual
voter
fraud
at
the
polls.

In
the
 presence
of
suspected
voter
fraud 
the
ruling
declared
that
the
legislature
had
the
 right
to
impose
rigid
standards
to
protect
against
perceived
threats
so
long
as
they
 were
not
clearly
discriminatory.

The
burden
of
proof
rests
almost
purely
upon
the
 opponents
of
photo
identification
to
demonstrate
the
impact
of
the
law
is
in
fact
 disproportionately
felt.
 
 Photo
identification
requirements
have
been
studied
only
for
the
past
4
 years 
as
they
have
come
into
existence 
but
other
administrative
procedures
have
 been
studied
for
far
longer 
providing
guidance
to
contemporary
researchers
on
 how
to
investigate
the
effect
of
new
identification
standards.

As
early
as
1909 
 identification
requirements
at
the
poll
(in
this
case
simply
matching
a
declared
 name
with
a
pre‐registered
address)
were
demonstrated
to
reduce
turnout
in
New
 York
City
(Lapp
1909).

Large
declines
in
aggregate
turnout
were
noted
in
this
 study 
the
assumption
being
that
this
was
primarily
due
to
reductions
in
poll
fraud.

 The
simpler
electoral
procedures
of
the
time
permitted
a
straightforward
 interpretation
of
how
turnout
altered
after
voters
were
required
to
register
ahead
of

(3.33) (3.48) Evenly Split 121 26.55% 31.44% 4.89% (2.67) (3.22) (3.76) Mostly Urban 92 23.22% 33.77% 10.55% (2.64) (3.71) (4.05) Very Urban 60 32.92% 41.41% 8.49% (2.90) (3.80) (3.85) Total 543 22.82% 29.69% 6.86% (1.17) (1.51) (1.65) F Statistic 4.328 3.898 .497 (sig) (.002) (.004) (.738) 
 
 24



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