Martin-Quinn scores
E602784
Martin-Quinn scores are a widely used statistical measure that estimates the ideological positions of U.S. Supreme Court justices over time based on their voting behavior.
All labels observed (1)
| Label | Occurrences |
|---|---|
| Martin-Quinn scores canonical | 1 |
How this entity was disambiguated
This entity first appeared as the object of triple T6498708 — resolving that mention is where its identity was fixed. The disambiguator weighed these candidate entities and picked the highlighted one (or “None”, minting a new entity). This is how homonymy is resolved: the same surface form can point to different entities.
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Martin-Quinn scores Context triple: [Andrew D. Martin, notableWork, Martin-Quinn scores]
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A.
Keeping Score
Keeping Score is an educational multimedia project by the San Francisco Symphony that explores classical music and composers through documentaries, concerts, and online resources.
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B.
SCORE
SCORE is a U.S. nonprofit organization of volunteer business mentors that provides free counseling, resources, and education to small business owners and entrepreneurs.
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C.
Ratings Percentage Index
The Ratings Percentage Index is a statistical ranking system used in U.S. college sports to evaluate and compare teams based on their wins, losses, and strength of schedule.
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D.
McQuinn
McQuinn is a surname of Irish or Scottish origin, likely a variant of the more common name Quinn.
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E.
Pi (score)
Pi (score) is the minimalist, electronic-infused orchestral soundtrack composed by Clint Mansell for Darren Aronofsky’s 1998 psychological thriller film "Pi."
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Martin-Quinn scores Target entity description: Martin-Quinn scores are a widely used statistical measure that estimates the ideological positions of U.S. Supreme Court justices over time based on their voting behavior.
-
A.
Keeping Score
Keeping Score is an educational multimedia project by the San Francisco Symphony that explores classical music and composers through documentaries, concerts, and online resources.
-
B.
SCORE
SCORE is a U.S. nonprofit organization of volunteer business mentors that provides free counseling, resources, and education to small business owners and entrepreneurs.
-
C.
Ratings Percentage Index
The Ratings Percentage Index is a statistical ranking system used in U.S. college sports to evaluate and compare teams based on their wins, losses, and strength of schedule.
-
D.
McQuinn
McQuinn is a surname of Irish or Scottish origin, likely a variant of the more common name Quinn.
-
E.
Pi (score)
Pi (score) is the minimalist, electronic-infused orchestral soundtrack composed by Clint Mansell for Darren Aronofsky’s 1998 psychological thriller film "Pi."
- F. None of above. chosen
Statements (49)
| Predicate | Object |
|---|---|
| instanceOf |
ideal point estimate
ⓘ
judicial ideology measure ⓘ statistical model ⓘ time-series cross-sectional model ⓘ |
| appliesTo | U.S. Supreme Court justices NERFINISHED ⓘ |
| associatedWith |
UC Berkeley
NERFINISHED
ⓘ
University of Michigan NERFINISHED ⓘ |
| assumes |
cases can be ordered along an ideological dimension
ⓘ
justices have stable preferences within short periods ⓘ |
| basedOn |
Supreme Court voting behavior
ⓘ
case outcomes ⓘ |
| captures | changes in justice ideology over time ⓘ |
| coversPeriod | U.S. Supreme Court terms from 1953 onward ⓘ |
| dataSource | Supreme Court Database NERFINISHED ⓘ |
| developedBy |
Andrew D. Martin
NERFINISHED
ⓘ
Kevin M. Quinn NERFINISHED ⓘ |
| documentedIn | “Dynamic Ideal Point Estimation via Markov Chain Monte Carlo for the U.S. Supreme Court, 1953–1999” NERFINISHED ⓘ |
| estimates |
ideological positions of justices
ⓘ
latent policy preferences ⓘ |
| excludes | many unanimous decisions ⓘ |
| firstPublishedIn | early 2000s ⓘ |
| focusesOn | merits decisions ⓘ |
| hasDimension | one-dimensional ideological scale ⓘ |
| hasOrientation | liberal-conservative ⓘ |
| hasWebsite | https://mqscores.lsa.umich.edu/ ⓘ |
| inputData |
case issue areas
ⓘ
votes in non-unanimous cases ⓘ |
| interpretedAs |
higher values more conservative
ⓘ
lower values more liberal ⓘ |
| output |
posterior mean ideal points
ⓘ
posterior uncertainty intervals ⓘ |
| publishedIn | Political Analysis NERFINISHED ⓘ |
| relatedTo |
Judicial Common Space scores
ⓘ
Segal-Cover scores ⓘ ideal point models ⓘ |
| scaleCentering | Court median in a reference term ⓘ |
| unitOfAnalysis | justice-term ⓘ |
| updated | periodically ⓘ |
| usedBy |
journalists
ⓘ
legal scholars ⓘ political scientists ⓘ |
| usedFor |
comparing ideological positions across terms
ⓘ
measuring Court polarization ⓘ quantitative analysis of the Supreme Court ⓘ studying judicial behavior ⓘ tracking ideological drift of justices ⓘ |
| usesMethod |
Bayesian item response theory
ⓘ
Markov chain Monte Carlo NERFINISHED ⓘ |
| variesOver | time ⓘ |
How these facts were elicited
The pipeline generated the facts above by prompting gpt-5.1 with this entity's name + description and the instruction below.
Instruction
You are a knowledge base construction expert. Given a subject entity and a description of it, return factual statements that you know for the subject as a JSON list of dictionaries(triples), where keys must be "subject", "predicate" and "object". The number of facts may be very high, between 25 to 50 or more, for very popular subjects. For less popular subjects, the number of facts can be very low, like 5 or 10. # Requirements - If you don't know the subject at all, return an empty list. - If the subject is not a named entity, return an empty list. - Include at least one triple where predicate is "instanceOf". - Do not get too wordy. - Separate several objects into multiple triples with one object.
Input
Subject: Martin-Quinn scores Description of subject: Martin-Quinn scores are a widely used statistical measure that estimates the ideological positions of U.S. Supreme Court justices over time based on their voting behavior.
Referenced by (1)
Full triples — surface form annotated when it differs from this entity's canonical label.