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Candidate Mapping: Finding Your PlaceAmongst the Candidates
Justin Donaldson and William Hazlewood
Candidate Mapping: Finding Your Place Amongst the Candidates
Justin Donaldson and William Hazlewood
1 IntroductionSpatial Voting and Policy SpaceMotivation
2 Data and Methodology2008 US Presidential Election DataPolicy Space Methodology
3 Participant StudyStudy OverviewStudy Results
Candidate Mapping: Finding Your Place Amongst the Candidates
Justin Donaldson and William Hazlewood
Spatial Voting Theory
Spatial Voting Theory: How do People Choose a Candidate?
Introduced by Anthony Downs in 1957
Different variations exist: Spatial Proximity (Downs andEnelow 1990) and Directional (Rabinowitz 89)Voters choose their candidates on maximum utility. Theypick candidates that will vote the way that will benefitthem the most.“Most” of this benefit is based on ideology (I support theright to bear arms, therefore I will support a candidatewho feels the same.)
Figure: Lewis & King Political Analysis 8:1 1999Candidate Mapping: Finding Your Place Amongst the Candidates
Justin Donaldson and William Hazlewood
Spatial Voting Theory
Spatial Voting Theory: How do People Choose a Candidate?
Introduced by Anthony Downs in 1957Different variations exist: Spatial Proximity (Downs andEnelow 1990) and Directional (Rabinowitz 89)
Voters choose their candidates on maximum utility. Theypick candidates that will vote the way that will benefitthem the most.“Most” of this benefit is based on ideology (I support theright to bear arms, therefore I will support a candidatewho feels the same.)
Figure: Lewis & King Political Analysis 8:1 1999Candidate Mapping: Finding Your Place Amongst the Candidates
Justin Donaldson and William Hazlewood
Spatial Voting Theory
Spatial Voting Theory: How do People Choose a Candidate?
Introduced by Anthony Downs in 1957Different variations exist: Spatial Proximity (Downs andEnelow 1990) and Directional (Rabinowitz 89)Voters choose their candidates on maximum utility. Theypick candidates that will vote the way that will benefitthem the most.
“Most” of this benefit is based on ideology (I support theright to bear arms, therefore I will support a candidatewho feels the same.)
Figure: Lewis & King Political Analysis 8:1 1999Candidate Mapping: Finding Your Place Amongst the Candidates
Justin Donaldson and William Hazlewood
Spatial Voting Theory
Spatial Voting Theory: How do People Choose a Candidate?
Introduced by Anthony Downs in 1957Different variations exist: Spatial Proximity (Downs andEnelow 1990) and Directional (Rabinowitz 89)Voters choose their candidates on maximum utility. Theypick candidates that will vote the way that will benefitthem the most.“Most” of this benefit is based on ideology (I support theright to bear arms, therefore I will support a candidatewho feels the same.)
Figure: Lewis & King Political Analysis 8:1 1999Candidate Mapping: Finding Your Place Amongst the Candidates
Justin Donaldson and William Hazlewood
Policy Space for Candidates
Candidates have different stanceson a huge variety of issues.
In most cases, the differentvarieties of stances are verylimited (by party platform).
These varieties of stances can becondensed into a relevant “policyspace” by means of dimensionalityreduction.
Figure credit: Poole (Dw-Nominate) and Cahoon (1975)
Candidate Mapping: Finding Your Place Amongst the Candidates
Justin Donaldson and William Hazlewood
Policy Space for Candidates
Candidates have different stanceson a huge variety of issues.
In most cases, the differentvarieties of stances are verylimited (by party platform).
These varieties of stances can becondensed into a relevant “policyspace” by means of dimensionalityreduction.
Figure credit: Poole (Dw-Nominate) and Cahoon (1975)
Candidate Mapping: Finding Your Place Amongst the Candidates
Justin Donaldson and William Hazlewood
Policy Space for Candidates
Candidates have different stanceson a huge variety of issues.
In most cases, the differentvarieties of stances are verylimited (by party platform).
These varieties of stances can becondensed into a relevant “policyspace” by means of dimensionalityreduction.
Figure credit: Poole (Dw-Nominate) and Cahoon (1975)
Candidate Mapping: Finding Your Place Amongst the Candidates
Justin Donaldson and William Hazlewood
Policy Space for Candidates
Candidates have different stanceson a huge variety of issues.
In most cases, the differentvarieties of stances are verylimited (by party platform).
These varieties of stances can becondensed into a relevant “policyspace” by means of dimensionalityreduction.
Figure credit: Poole (Dw-Nominate) and Cahoon (1975)
Candidate Mapping: Finding Your Place Amongst the Candidates
Justin Donaldson and William Hazlewood
Policy Space for Candidates
Candidates have different stanceson a huge variety of issues.
In most cases, the differentvarieties of stances are verylimited (by party platform).
These varieties of stances can becondensed into a relevant “policyspace” by means of dimensionalityreduction.
Figure credit: Poole (Dw-Nominate) and Cahoon (1975)
Candidate Mapping: Finding Your Place Amongst the Candidates
Justin Donaldson and William Hazlewood
Do Most Folks Understand “Policy Space”?
1 Most political policy spaces are intrinsically lowdimensional.
2 Some people may think they have a “fuzzy” notion ofwhere they lie on the dominant intrinsic dimension(currently, typically liberal to conservative*), and whichcandidates are “most like” them.
3 How do their “fuzzy” notions match up to their “actualposition” that would be indicated through the use of policyspace?
4 What can we learn about their position error?
5 What demographic trends are present?
Candidate Mapping: Finding Your Place Amongst the Candidates
Justin Donaldson and William Hazlewood
Do Most Folks Understand “Policy Space”?
1 Most political policy spaces are intrinsically lowdimensional.
2 Some people may think they have a “fuzzy” notion ofwhere they lie on the dominant intrinsic dimension(currently, typically liberal to conservative*), and whichcandidates are “most like” them.
3 How do their “fuzzy” notions match up to their “actualposition” that would be indicated through the use of policyspace?
4 What can we learn about their position error?
5 What demographic trends are present?
Candidate Mapping: Finding Your Place Amongst the Candidates
Justin Donaldson and William Hazlewood
Do Most Folks Understand “Policy Space”?
1 Most political policy spaces are intrinsically lowdimensional.
2 Some people may think they have a “fuzzy” notion ofwhere they lie on the dominant intrinsic dimension(currently, typically liberal to conservative*), and whichcandidates are “most like” them.
3 How do their “fuzzy” notions match up to their “actualposition” that would be indicated through the use of policyspace?
4 What can we learn about their position error?
5 What demographic trends are present?
Candidate Mapping: Finding Your Place Amongst the Candidates
Justin Donaldson and William Hazlewood
Do Most Folks Understand “Policy Space”?
1 Most political policy spaces are intrinsically lowdimensional.
2 Some people may think they have a “fuzzy” notion ofwhere they lie on the dominant intrinsic dimension(currently, typically liberal to conservative*), and whichcandidates are “most like” them.
3 How do their “fuzzy” notions match up to their “actualposition” that would be indicated through the use of policyspace?
4 What can we learn about their position error?
5 What demographic trends are present?
Candidate Mapping: Finding Your Place Amongst the Candidates
Justin Donaldson and William Hazlewood
Do Most Folks Understand “Policy Space”?
1 Most political policy spaces are intrinsically lowdimensional.
2 Some people may think they have a “fuzzy” notion ofwhere they lie on the dominant intrinsic dimension(currently, typically liberal to conservative*), and whichcandidates are “most like” them.
3 How do their “fuzzy” notions match up to their “actualposition” that would be indicated through the use of policyspace?
4 What can we learn about their position error?
5 What demographic trends are present?
Candidate Mapping: Finding Your Place Amongst the Candidates
Justin Donaldson and William Hazlewood
Collected data from two independent websites: 2decide.com,and ontheissues.org.
Figure: 2decide.com
Figure: ontheissues.org
Candidate Mapping: Finding Your Place Amongst the Candidates
Justin Donaldson and William Hazlewood
Candidate and Issue List
Candidates(As of Oct. 2007)
Hillary Clinton
John Edwards
Rudy Giuliani
Mike Gravel
Mike Huckabee
Dennis Kucinich
John McCain
Barack Obama
Ron Paul
Mitt Romney
IssuesRoe v. Wade
Death Penalty
Education: No Child Left Behind
Embryonic Stem Cells:Legalization of Research
Energy & Oil: Pursue ANWRDrilling
Energy & Oil: Adopt KyotoProtocol
Guns: Assault Weapons Ban
Guns: Background Checks forHandguns
Homeland Security: Patriot Act
Homeland Security: Guantanamo
Homeland Security:Waterboarding (torture)
Issues, Cont.Immigration: Border Fence
Internet Neutrality
Iran: Sanctions
Iran: Military Action as Option
Iraq: Initial Invasion Justified
Iraq: Troop Surge
Iraq: Withdrawal
Minimum Wage Increase
Same-Sex: Marriage
Same-Sex: Civil Union
Same-Sex: Constitutional Ban
Universal Healthcare
Homeland Security: DomesticWiretapping
Immigration: Citizenship Path forIllegals
Candidate Mapping: Finding Your Place Amongst the Candidates
Justin Donaldson and William Hazlewood
Processing and Factoring Candidate Data
Candidate responses to issues are ordinally coded to reflect anincreasingly stronger stance on an issue.
Default: Supports < Mixed Opinion < Opposes.
Iraq war withdrawal: Immediate Withdrawal < SupportsPhased Withdrawal < Opposes.
Same sex marriage/union: Supports < Supports butbelieves the issues should be left to the states. < Mixedopinion < Opposes but believes the issue should be left tothe states < Opposes.
Candidate Mapping: Finding Your Place Amongst the Candidates
Justin Donaldson and William Hazlewood
Processing and Factoring Candidate Data
Candidate responses to issues are ordinally coded to reflect anincreasingly stronger stance on an issue.
Default: Supports < Mixed Opinion < Opposes.
Iraq war withdrawal: Immediate Withdrawal < SupportsPhased Withdrawal < Opposes.
Same sex marriage/union: Supports < Supports butbelieves the issues should be left to the states. < Mixedopinion < Opposes but believes the issue should be left tothe states < Opposes.
Candidate Mapping: Finding Your Place Amongst the Candidates
Justin Donaldson and William Hazlewood
Processing and Factoring Candidate Data
Candidate responses to issues are ordinally coded to reflect anincreasingly stronger stance on an issue.
Default: Supports < Mixed Opinion < Opposes.
Iraq war withdrawal: Immediate Withdrawal < SupportsPhased Withdrawal < Opposes.
Same sex marriage/union: Supports < Supports butbelieves the issues should be left to the states. < Mixedopinion < Opposes but believes the issue should be left tothe states < Opposes.
Candidate Mapping: Finding Your Place Amongst the Candidates
Justin Donaldson and William Hazlewood
Matrix Form
Data Gathered into Matrix FormCandidate Issues
Roe V. Wade Uni. Health Death Penalty ...
Clinton Support Oppose Support ...Edwards Support Support Neither ...Giuliani Support Support Let States Decide ...... ... ... ... ...
Data Processed into Similarities/Dissimilarities withGower Dissimilarity
sijk = 1−|xik − xjk |
rkClinton Edwards Giuliani ...
Clinton N/A 0.3 0.1 ...Edwards 0.3 N/A 0.2 ...Giuliani 0.1 0.2 N/A ...... ... ... ... ...
Candidate Mapping: Finding Your Place Amongst the Candidates
Justin Donaldson and William Hazlewood
Matrix Form
Data Gathered into Matrix FormCandidate Issues
Roe V. Wade Uni. Health Death Penalty ...
Clinton Support Oppose Support ...Edwards Support Support Neither ...Giuliani Support Support Let States Decide ...... ... ... ... ...
Data Processed into Similarities/Dissimilarities withGower Dissimilarity
sijk = 1−|xik − xjk |
rk
Clinton Edwards Giuliani ...Clinton N/A 0.3 0.1 ...Edwards 0.3 N/A 0.2 ...Giuliani 0.1 0.2 N/A ...... ... ... ... ...
Candidate Mapping: Finding Your Place Amongst the Candidates
Justin Donaldson and William Hazlewood
Matrix Form
Data Gathered into Matrix FormCandidate Issues
Roe V. Wade Uni. Health Death Penalty ...
Clinton Support Oppose Support ...Edwards Support Support Neither ...Giuliani Support Support Let States Decide ...... ... ... ... ...
Data Processed into Similarities/Dissimilarities withGower Dissimilarity
sijk = 1−|xik − xjk |
rkClinton Edwards Giuliani ...
Clinton N/A 0.3 0.1 ...Edwards 0.3 N/A 0.2 ...Giuliani 0.1 0.2 N/A ...... ... ... ... ...
Candidate Mapping: Finding Your Place Amongst the Candidates
Justin Donaldson and William Hazlewood
Dimensionality Reduction
Sammon mapping was applied to theGower dissimilarity matrix in order toexpress the candidate relationalinformation in two dimensions.
E =1P
i<j [dij∗]
NXi<j
[dij∗ − dij ]
2
dij∗
The error of the representation is very low0.011 (∼ 1%), well within error tolerances.
The dimensions are characterized by theirextremes: Kucinich and Romney, Paul andGiuliani 0 100 200 300 400 500
5010
015
020
025
030
0
Sammon Map of Candidate Similarity
Liberal to Conservative
Non
inte
rven
tion
to In
terv
entio
n
ClintonEdwards_beforeClinton_before
Huckabee
RomneyKucinich McCain
Obama
Gravel
GiulianiEdwards
Paul
Previous and current positions, Obama’s position in Poole’s analysishttp://voteview.ucsd.edu/Clinton_and_Obama.htm
Candidate Mapping: Finding Your Place Amongst the Candidates
Justin Donaldson and William Hazlewood
Dimensionality Reduction
Sammon mapping was applied to theGower dissimilarity matrix in order toexpress the candidate relationalinformation in two dimensions.
E =1P
i<j [dij∗]
NXi<j
[dij∗ − dij ]
2
dij∗
The error of the representation is very low0.011 (∼ 1%), well within error tolerances.
The dimensions are characterized by theirextremes: Kucinich and Romney, Paul andGiuliani 0 100 200 300 400 500
5010
015
020
025
030
0
Sammon Map of Candidate Similarity
Liberal to Conservative
Non
inte
rven
tion
to In
terv
entio
n
ClintonEdwards_beforeClinton_before
Huckabee
RomneyKucinich McCain
Obama
Gravel
GiulianiEdwards
Paul
Previous and current positions, Obama’s position in Poole’s analysishttp://voteview.ucsd.edu/Clinton_and_Obama.htm
Candidate Mapping: Finding Your Place Amongst the Candidates
Justin Donaldson and William Hazlewood
Dimensionality Reduction
Sammon mapping was applied to theGower dissimilarity matrix in order toexpress the candidate relationalinformation in two dimensions.
E =1P
i<j [dij∗]
NXi<j
[dij∗ − dij ]
2
dij∗
The error of the representation is very low0.011 (∼ 1%), well within error tolerances.
The dimensions are characterized by theirextremes: Kucinich and Romney, Paul andGiuliani
0 100 200 300 400 500
5010
015
020
025
030
0
Sammon Map of Candidate Similarity
Liberal to Conservative
Non
inte
rven
tion
to In
terv
entio
n
ClintonEdwards_beforeClinton_before
Huckabee
RomneyKucinich McCain
Obama
Gravel
GiulianiEdwards
Paul
Previous and current positions, Obama’s position in Poole’s analysishttp://voteview.ucsd.edu/Clinton_and_Obama.htm
Candidate Mapping: Finding Your Place Amongst the Candidates
Justin Donaldson and William Hazlewood
Dimensionality Reduction
Sammon mapping was applied to theGower dissimilarity matrix in order toexpress the candidate relationalinformation in two dimensions.
E =1P
i<j [dij∗]
NXi<j
[dij∗ − dij ]
2
dij∗
The error of the representation is very low0.011 (∼ 1%), well within error tolerances.
The dimensions are characterized by theirextremes: Kucinich and Romney, Paul andGiuliani 0 100 200 300 400 500
5010
015
020
025
030
0
Sammon Map of Candidate Similarity
Liberal to Conservative
Non
inte
rven
tion
to In
terv
entio
n
ClintonEdwards_beforeClinton_before
Huckabee
RomneyKucinich McCain
Obama
Gravel
GiulianiEdwards
Paul
Previous and current positions, Obama’s position in Poole’s analysishttp://voteview.ucsd.edu/Clinton_and_Obama.htm
Candidate Mapping: Finding Your Place Amongst the Candidates
Justin Donaldson and William Hazlewood
Dimensionality Reduction
Sammon mapping was applied to theGower dissimilarity matrix in order toexpress the candidate relationalinformation in two dimensions.
E =1P
i<j [dij∗]
NXi<j
[dij∗ − dij ]
2
dij∗
The error of the representation is very low0.011 (∼ 1%), well within error tolerances.
The dimensions are characterized by theirextremes: Kucinich and Romney, Paul andGiuliani 0 100 200 300 400 500
5010
015
020
025
030
0
Sammon Map of Candidate Similarity
Liberal to Conservative
Non
inte
rven
tion
to In
terv
entio
n
ClintonEdwards_beforeClinton_before
Huckabee
RomneyKucinich McCain
Obama
Gravel
GiulianiEdwards
Paul
Previous and current positions, Obama’s position in Poole’s analysishttp://voteview.ucsd.edu/Clinton_and_Obama.htm
Candidate Mapping: Finding Your Place Amongst the Candidates
Justin Donaldson and William Hazlewood
Participant Study Details
The web-based study(http://www.candidatemapper2008.net) collected:
1 Consent and DemographicInformation
2 Issue stance information for eachof the 25 issues. (Plus ability toresearch issues.)
3 Brief open ended exit survey
Candidate Mapping: Finding Your Place Amongst the Candidates
Justin Donaldson and William Hazlewood
Participant Study Details Cont.
1 The study calculates theparticipant’s position in policyspace along with all the othercandidates.
2 The study presents the resultingmap to the user (with their “real”position hidden) and asks them toindicate where they think they liein the policy space
3 The study reveals the participantsposition, and invites them toexplore the map in more detailand answer exit questions.
Candidate Mapping: Finding Your Place Amongst the Candidates
Justin Donaldson and William Hazlewood
Participant Study Details Cont.
1 The study calculates theparticipant’s position in policyspace along with all the othercandidates.
2 The study presents the resultingmap to the user (with their “real”position hidden) and asks them toindicate where they think they liein the policy space
3 The study reveals the participantsposition, and invites them toexplore the map in more detailand answer exit questions.
Candidate Mapping: Finding Your Place Amongst the Candidates
Justin Donaldson and William Hazlewood
Participant Study Details Cont.
1 The study calculates theparticipant’s position in policyspace along with all the othercandidates.
2 The study presents the resultingmap to the user (with their “real”position hidden) and asks them toindicate where they think they liein the policy space
3 The study reveals the participantsposition, and invites them toexplore the map in more detailand answer exit questions.
Candidate Mapping: Finding Your Place Amongst the Candidates
Justin Donaldson and William Hazlewood
Summary Statistics
Focus the analysis on the participants’ political stance (liberal toconservative).
Explore the error (distance) in their explicit positioning vs. thatcalculated by the policy space.
Unit error distance is given in terms of pixels of the participant studyapplet.
Which policy stance group has the lowest error?
Table: Summary statistics for distance error vs. participant stances(vy = very, sw = somewhat, sl = slightly)
N mean stddev stderr
vy liberal 42 86.93 39.70 6.13sw liberal 49 99.03 47.08 6.73sl liberal 20 98.75 66.46 14.86neither 20 112.29 60.50 13.53
sl conserv. 8 136.40 65.09 23.01sw conserv. 22 113.27 68.47 14.60vy conserv. 2 169.90 73.31 51.83
Candidate Mapping: Finding Your Place Amongst the Candidates
Justin Donaldson and William Hazlewood
Summary Statistics
Focus the analysis on the participants’ political stance (liberal toconservative).
Explore the error (distance) in their explicit positioning vs. thatcalculated by the policy space.
Unit error distance is given in terms of pixels of the participant studyapplet.
Which policy stance group has the lowest error?
Table: Summary statistics for distance error vs. participant stances(vy = very, sw = somewhat, sl = slightly)
N mean stddev stderr
vy liberal 42 86.93 39.70 6.13sw liberal 49 99.03 47.08 6.73sl liberal 20 98.75 66.46 14.86neither 20 112.29 60.50 13.53
sl conserv. 8 136.40 65.09 23.01sw conserv. 22 113.27 68.47 14.60vy conserv. 2 169.90 73.31 51.83
Candidate Mapping: Finding Your Place Amongst the Candidates
Justin Donaldson and William Hazlewood
Summary Statistics
Focus the analysis on the participants’ political stance (liberal toconservative).
Explore the error (distance) in their explicit positioning vs. thatcalculated by the policy space.
Unit error distance is given in terms of pixels of the participant studyapplet.
Which policy stance group has the lowest error?
Table: Summary statistics for distance error vs. participant stances(vy = very, sw = somewhat, sl = slightly)
N mean stddev stderr
vy liberal 42 86.93 39.70 6.13sw liberal 49 99.03 47.08 6.73sl liberal 20 98.75 66.46 14.86neither 20 112.29 60.50 13.53
sl conserv. 8 136.40 65.09 23.01sw conserv. 22 113.27 68.47 14.60vy conserv. 2 169.90 73.31 51.83
Candidate Mapping: Finding Your Place Amongst the Candidates
Justin Donaldson and William Hazlewood
Summary Statistics
Focus the analysis on the participants’ political stance (liberal toconservative).
Explore the error (distance) in their explicit positioning vs. thatcalculated by the policy space.
Unit error distance is given in terms of pixels of the participant studyapplet.
Which policy stance group has the lowest error?
Table: Summary statistics for distance error vs. participant stances(vy = very, sw = somewhat, sl = slightly)
N mean stddev stderr
vy liberal 42 86.93 39.70 6.13sw liberal 49 99.03 47.08 6.73sl liberal 20 98.75 66.46 14.86neither 20 112.29 60.50 13.53
sl conserv. 8 136.40 65.09 23.01sw conserv. 22 113.27 68.47 14.60vy conserv. 2 169.90 73.31 51.83
Candidate Mapping: Finding Your Place Amongst the Candidates
Justin Donaldson and William Hazlewood
Summary Statistics
Focus the analysis on the participants’ political stance (liberal toconservative).
Explore the error (distance) in their explicit positioning vs. thatcalculated by the policy space.
Unit error distance is given in terms of pixels of the participant studyapplet.
Which policy stance group has the lowest error?
Table: Summary statistics for distance error vs. participant stances(vy = very, sw = somewhat, sl = slightly)
N mean stddev stderr
vy liberal 42 86.93 39.70 6.13sw liberal 49 99.03 47.08 6.73sl liberal 20 98.75 66.46 14.86neither 20 112.29 60.50 13.53
sl conserv. 8 136.40 65.09 23.01sw conserv. 22 113.27 68.47 14.60vy conserv. 2 169.90 73.31 51.83
Candidate Mapping: Finding Your Place Amongst the Candidates
Justin Donaldson and William Hazlewood
Summary Statistics
Focus the analysis on the participants’ political stance (liberal toconservative).
Explore the error (distance) in their explicit positioning vs. thatcalculated by the policy space.
Unit error distance is given in terms of pixels of the participant studyapplet.
Which policy stance group has the lowest error?
Table: Summary statistics for distance error vs. participant stances(vy = very, sw = somewhat, sl = slightly)
N mean stddev stderr
vy liberal 42 86.93 39.70 6.13sw liberal 49 99.03 47.08 6.73sl liberal 20 98.75 66.46 14.86neither 20 112.29 60.50 13.53
sl conserv. 8 136.40 65.09 23.01sw conserv. 22 113.27 68.47 14.60vy conserv. 2 169.90 73.31 51.83
Candidate Mapping: Finding Your Place Amongst the Candidates
Justin Donaldson and William Hazlewood
T-test Values Between Political Stance
Are the groups of participant political stances statisticallydifferent in their positioning error?
Table: Pairwise t-test values for participant stances(l=liberal,c=conservative)
vl swl sll n slc swc
sw liberal 0.19sl liberal 0.47 0.99
neither *0.10 0.39 0.50sl consrv. *0.07 0.16 0.19 0.38
sw consrv. *0.10 0.38 0.49 0.96 0.41vy consrv. 0.35 0.40 0.39 0.46 0.63 0.46
Candidate Mapping: Finding Your Place Amongst the Candidates
Justin Donaldson and William Hazlewood
T-test Values Between Political Stance
Are the groups of participant political stances statisticallydifferent in their positioning error?
Table: Pairwise t-test values for participant stances(l=liberal,c=conservative)
vl swl sll n slc swc
sw liberal 0.19sl liberal 0.47 0.99
neither *0.10 0.39 0.50sl consrv. *0.07 0.16 0.19 0.38
sw consrv. *0.10 0.38 0.49 0.96 0.41vy consrv. 0.35 0.40 0.39 0.46 0.63 0.46
Candidate Mapping: Finding Your Place Amongst the Candidates
Justin Donaldson and William Hazlewood
T-test Values Between Political Stance Cont.
Are the groups of participant political stances statisticallydifferent in their positioning error?
1 2 3 4 5 6 7
8010
012
014
016
018
020
022
0
Distance Between Selected and Calculated Position
1: Very liberal to 7: Very conservative
Dis
tanc
e
●
● ●
●
●
●
●
Figure: Mean distance distribution between selected and calculateddistances, by participant political stance.Candidate Mapping: Finding Your Place Amongst the Candidates
Justin Donaldson and William Hazlewood
Consistency in Error
Do participant stance groups differ consistently in the directionof their error?
●
●
●
●
●
very_liberal slightly_liberal somewhat_conservative
−20
0−
100
010
020
0
Distance Error in X Dimension
General Participant Political Stance (Very Liberal to Very Conservative)
Dis
tanc
e E
rror
Figure: Difference in x dimension
●
●
●
●
very_liberal slightly_liberal somewhat_conservative
−10
00
100
200
Distance Error in Y Dimension
General Participant Political Stance (Very Liberal to Very Conservative)
Dis
tanc
e E
rror
Figure: Difference in y dimension
Candidate Mapping: Finding Your Place Amongst the Candidates
Justin Donaldson and William Hazlewood
Consistency in Error
Do participant stance groups differ consistently in the directionof their error?
●
●
●
●
●
very_liberal slightly_liberal somewhat_conservative
−20
0−
100
010
020
0
Distance Error in X Dimension
General Participant Political Stance (Very Liberal to Very Conservative)
Dis
tanc
e E
rror
Figure: Difference in x dimension
●
●
●
●
very_liberal slightly_liberal somewhat_conservative
−10
00
100
200
Distance Error in Y Dimension
General Participant Political Stance (Very Liberal to Very Conservative)
Dis
tanc
e E
rror
Figure: Difference in y dimension
Candidate Mapping: Finding Your Place Amongst the Candidates
Justin Donaldson and William Hazlewood
Consistency in Error
Do participant stance groups differ consistently in the directionof their error?
●
●
●
●
●
very_liberal slightly_liberal somewhat_conservative
−20
0−
100
010
020
0
Distance Error in X Dimension
General Participant Political Stance (Very Liberal to Very Conservative)
Dis
tanc
e E
rror
Figure: Difference in x dimension
●
●
●
●
very_liberal slightly_liberal somewhat_conservative−
100
010
020
0
Distance Error in Y Dimension
General Participant Political Stance (Very Liberal to Very Conservative)
Dis
tanc
e E
rror
Figure: Difference in y dimensionCandidate Mapping: Finding Your Place Amongst the Candidates
Justin Donaldson and William Hazlewood
The Big Picture
Isn’t this a VISUALISATION conference?
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Map of Selected and Calculated (Dimensional Scaled) Positions
Liberal to Conservative
Non
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st to
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rven
tioni
st
Clinton
Huckabee
RomneyKucinich McCain
Obama
Gravel
GiulianiEdwards
Paul
very_liberalsomewhat_liberalslightly_liberalneitherslightly_conservativesomewhat_conservativevery_conservativen/a
Figure: Position of all participants who provided both their issueposition stances and their indicated position.
Candidate Mapping: Finding Your Place Amongst the Candidates
Justin Donaldson and William Hazlewood
The Big Picture
Isn’t this a VISUALISATION conference?
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0 100 200 300 400 500
010
020
030
0
Map of Selected and Calculated (Dimensional Scaled) Positions
Liberal to Conservative
Non
inte
rven
tioni
st to
Inte
rven
tioni
st
Clinton
Huckabee
RomneyKucinich McCain
Obama
Gravel
GiulianiEdwards
Paul
very_liberalsomewhat_liberalslightly_liberalneitherslightly_conservativesomewhat_conservativevery_conservativen/a
Figure: Position of all participants who provided both their issueposition stances and their indicated position.
Candidate Mapping: Finding Your Place Amongst the Candidates
Justin Donaldson and William Hazlewood
Conclusions
Low-error representation of candidate relationships onconsistent and (near-) complete issue stances forcandidates.
Participants recognized the liberal to conservativedimension without explanation. Some were confused bythe second ‘government intervention’ dimensions (fromexit questions).Liberal participants tended to have less overall error(Candidate homogeneity?).Liberal participants had consistent directional error.[Barack opposing same-sex marriage and supporting thedeath penalty].Candidate Mapping can help explain the error of voterpositioning in terms of the underlying dimensions (‘You aremore liberal than that!’).Questions?
Candidate Mapping: Finding Your Place Amongst the Candidates
Justin Donaldson and William Hazlewood
Conclusions
Low-error representation of candidate relationships onconsistent and (near-) complete issue stances forcandidates.Participants recognized the liberal to conservativedimension without explanation. Some were confused bythe second ‘government intervention’ dimensions (fromexit questions).
Liberal participants tended to have less overall error(Candidate homogeneity?).Liberal participants had consistent directional error.[Barack opposing same-sex marriage and supporting thedeath penalty].Candidate Mapping can help explain the error of voterpositioning in terms of the underlying dimensions (‘You aremore liberal than that!’).Questions?
Candidate Mapping: Finding Your Place Amongst the Candidates
Justin Donaldson and William Hazlewood
Conclusions
Low-error representation of candidate relationships onconsistent and (near-) complete issue stances forcandidates.Participants recognized the liberal to conservativedimension without explanation. Some were confused bythe second ‘government intervention’ dimensions (fromexit questions).Liberal participants tended to have less overall error(Candidate homogeneity?).
Liberal participants had consistent directional error.[Barack opposing same-sex marriage and supporting thedeath penalty].Candidate Mapping can help explain the error of voterpositioning in terms of the underlying dimensions (‘You aremore liberal than that!’).Questions?
Candidate Mapping: Finding Your Place Amongst the Candidates
Justin Donaldson and William Hazlewood
Conclusions
Low-error representation of candidate relationships onconsistent and (near-) complete issue stances forcandidates.Participants recognized the liberal to conservativedimension without explanation. Some were confused bythe second ‘government intervention’ dimensions (fromexit questions).Liberal participants tended to have less overall error(Candidate homogeneity?).Liberal participants had consistent directional error.[Barack opposing same-sex marriage and supporting thedeath penalty].
Candidate Mapping can help explain the error of voterpositioning in terms of the underlying dimensions (‘You aremore liberal than that!’).Questions?
Candidate Mapping: Finding Your Place Amongst the Candidates
Justin Donaldson and William Hazlewood
Conclusions
Low-error representation of candidate relationships onconsistent and (near-) complete issue stances forcandidates.Participants recognized the liberal to conservativedimension without explanation. Some were confused bythe second ‘government intervention’ dimensions (fromexit questions).Liberal participants tended to have less overall error(Candidate homogeneity?).Liberal participants had consistent directional error.[Barack opposing same-sex marriage and supporting thedeath penalty].Candidate Mapping can help explain the error of voterpositioning in terms of the underlying dimensions (‘You aremore liberal than that!’).
Questions?
Candidate Mapping: Finding Your Place Amongst the Candidates
Justin Donaldson and William Hazlewood
Conclusions
Low-error representation of candidate relationships onconsistent and (near-) complete issue stances forcandidates.Participants recognized the liberal to conservativedimension without explanation. Some were confused bythe second ‘government intervention’ dimensions (fromexit questions).Liberal participants tended to have less overall error(Candidate homogeneity?).Liberal participants had consistent directional error.[Barack opposing same-sex marriage and supporting thedeath penalty].Candidate Mapping can help explain the error of voterpositioning in terms of the underlying dimensions (‘You aremore liberal than that!’).Questions?
Candidate Mapping: Finding Your Place Amongst the Candidates
Justin Donaldson and William Hazlewood
Discussion
Can candidate mapping be used as a form of voting orpolitical awareness tool?
Can it be used to reduce the effects of political ‘gaming,’such as gerrymandering?
Handling weighted issue policy maps is possible, but verychallenging for global visualization!
Candidate Mapping: Finding Your Place Amongst the Candidates
Justin Donaldson and William Hazlewood