1. REGRESSIONS AT WORK: IDEOLOGY AND LAW, CORRELATES OF DEMOCRACY

2. OUTLINE Ideological Values and Votes of Supreme Court Justices National Political Development: Measurement and Analysis

3. 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)

4. 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

5. 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.

6. 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.

7. 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) Regression at Work (II)

8. 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

9. 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

10. 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

11. 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