- Slides: 12
REGRESSIONS AT WORK: IDEOLOGY AND LAW, CORRELATES OF DEMOCRACY
OUTLINE • Ideological Values and Votes of Supreme Court Justices • National Political Development: Measurement and Analysis
Regression at Work (I) • Theme: Supreme Court decisions • General question: What is the underlying basis of voting by justices? • Specific question: Is voting related to political ideology? • Hypothesis: Y = f (X)
Operationalizing the Independent Variable: Source: Editorials in newspapers (New York Times and Washington Post, Chicago Tribune and Los Angeles Times) Coding of paragraphs: liberal, moderate, conservative, not applicable JI = (liberal- conservative)/(liberal + moderate + conservative) Scale from + 1. 0 to – 1. 0 (ultraliberal to ultraconservative) Thus: perceived values rather than real values
And the Dependent Variable: % “liberal” votes in civil liberties cases, 1953 -1987: • Pro-person accused or convicted of crime • Pro-civil liberties or civil rights claimant • Pro-indigent • Pro-Indian • Anti-government regarding due process and privacy.
Basic Finding: Voting = 51. 25 + 23. 44 (JI) r = +. 80, r 2 =. 64 Thus the force of ideology (or attitudes). Alternative explanations: 1. Legal doctrine and precedent 2. Case facts 3. Internal politics and external forces.
Regression at Work (II) Theme: Determinants of political democracy General question: What social factors tend to produce political democracy? Specific question: Is “democratic development” (Y) associated with “social development” (X)? Hypothesis: Y = f(X)
Operationalizing the Dependent Variable Legislative branch: 2 points for each year (1940 -60) with two or more political parties and opposition held at least 30% of seats 1 point for each year with one or more parties but 30% rule violated 0 points otherwise Executive branch: 1 point for each year (1940 -60) chief executive if elected 0. 5 if selected otherwise or colonial ruler 0 points if hereditary ruler Range: 0 -3 per year, 0 -63 for 21 -year time span
Measures of the Independent Variable Communications: newspaper readers per capita, newsprint consumption per capita, domestic mail per capita, telephones per capita Urbanization: proportion living in cities over 100, 000 Education: literacy rates and students per 100, 000 in Institutions of higher education Agriculture: proportion of labor force in agriculture Economic development: per capita measures of energy consumption, steel consumption, income and motor vehicles
Why T Scores? Definition: T = z x 10 + 50, thus a variation of the “standard score” Advantages: • formation of composite indices • absence of a meaningful zero point • avoidance of negative scores
Key Findings: PD = 31 + (. 2154) COMM, r = +. 812 and r 2 =. 65 standard error of b =. 0179 R 2 for equation using all four independent variables =. 67, so very little additional gain