Scaling policy preferences from coded political texts
Scholars estimating policy positions from political texts typically code words or sentences and then build left-right policy scales based on the relative frequencies of text units coded into different categories. Here we reexamine such scales and propose a theoretically and linguistically superior a...
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2011
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sg-smu-ink.soss_research-52312024-09-02T06:29:32Z Scaling policy preferences from coded political texts LOWE, Will BENOIT, Kenneth MIKHAYLOV, Slava LAVER, Michael Scholars estimating policy positions from political texts typically code words or sentences and then build left-right policy scales based on the relative frequencies of text units coded into different categories. Here we reexamine such scales and propose a theoretically and linguistically superior alternative based on the logarithm of odds-ratios. We contrast this scale with the current approach of the Comparative Manifesto Project (CMP), showing that our proposed logit scale avoids widely acknowledged flaws in previous approaches. We validate the new scale using independent expert surveys. Using existing CMP data, we show how to estimate more distinct policy dimensions, for more years, than has been possible before, and make this dataset publicly available. Finally, we draw some conclusions about the future design of coding schemes for political texts. 2011-02-01T08:00:00Z text application/pdf https://ink.library.smu.edu.sg/soss_research/3973 info:doi/10.1111/j.1939-9162.2010.00006.x https://ink.library.smu.edu.sg/context/soss_research/article/5231/viewcontent/2011_ScalingPolicyPreferences_CodedPoliticalTexts_pvoa_by_nc.pdf http://creativecommons.org/licenses/by/3.0/ Research Collection School of Social Sciences eng Institutional Knowledge at Singapore Management University Models and Methods Political Science |
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Models and Methods Political Science LOWE, Will BENOIT, Kenneth MIKHAYLOV, Slava LAVER, Michael Scaling policy preferences from coded political texts |
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Scholars estimating policy positions from political texts typically code words or sentences and then build left-right policy scales based on the relative frequencies of text units coded into different categories. Here we reexamine such scales and propose a theoretically and linguistically superior alternative based on the logarithm of odds-ratios. We contrast this scale with the current approach of the Comparative Manifesto Project (CMP), showing that our proposed logit scale avoids widely acknowledged flaws in previous approaches. We validate the new scale using independent expert surveys. Using existing CMP data, we show how to estimate more distinct policy dimensions, for more years, than has been possible before, and make this dataset publicly available. Finally, we draw some conclusions about the future design of coding schemes for political texts. |
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text |
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LOWE, Will BENOIT, Kenneth MIKHAYLOV, Slava LAVER, Michael |
author_facet |
LOWE, Will BENOIT, Kenneth MIKHAYLOV, Slava LAVER, Michael |
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LOWE, Will |
title |
Scaling policy preferences from coded political texts |
title_short |
Scaling policy preferences from coded political texts |
title_full |
Scaling policy preferences from coded political texts |
title_fullStr |
Scaling policy preferences from coded political texts |
title_full_unstemmed |
Scaling policy preferences from coded political texts |
title_sort |
scaling policy preferences from coded political texts |
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Institutional Knowledge at Singapore Management University |
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2011 |
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https://ink.library.smu.edu.sg/soss_research/3973 https://ink.library.smu.edu.sg/context/soss_research/article/5231/viewcontent/2011_ScalingPolicyPreferences_CodedPoliticalTexts_pvoa_by_nc.pdf |
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