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  3. It's Not Personal: Politics and Policy in Lower Court Confirmation Hearings

It's Not Personal: Politics and Policy in Lower Court Confirmation Hearings

Logan Dancey, Kjersten R. Nelson, and Eve M. Ringsmuth
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  • Overview

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In order to be confirmed to a lifetime appointment on the federal bench, all district and circuit court nominees must appear before the Senate Judiciary Committee for a confirmation hearing. Despite their relatively low profile, these lower court judges make up 99 percent of permanent federal judgeships and decide cases that relate to a wide variety of policy areas. To uncover why senators hold confirmation hearings for lower federal court nominees and the value of these proceedings more generally, the authors analyzed transcripts for all district and circuit court confirmation hearings between 1993 and 2012, the largest systematic analysis of lower court confirmation hearings to date. The book finds that the time-consuming practice of confirmation hearings for district and circuit court nominees provides an important venue for senators to advocate on behalf of their policy preferences and bolster their chances of being re-elected. The wide variation in lower court nominees' experiences before the Judiciary Committee exists because senators pursue these goals in different ways, depending on the level of controversy surrounding a nominee. Ultimately, the findings inform a (re)assessment of the role hearings play in ensuring quality judges, providing advice and consent, and advancing the democratic values of transparency and accountability.
  • Cover
  • Title Page
  • Copyright Page
  • Dedication
  • Contents
  • Acknowledgments
  • One. Introduction
  • Two. Confirmation Hearings
  • Three. An Overview of Confirmation Hearings, 1993–2012
  • Four. Why Do Senators Hold Confirmation Hearings?
  • Five. In Pursuit of Policy Goals
  • Six. Hearings as a Venue for Pursuing Electoral Goals
  • Seven. The Content and Consequences of Hearings for Controversial Nominees
  • Eight. The Value of Lower Court Confirmation Hearings
  • Appendixes
  • Notes
  • References
  • Index
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Published: 2020
Publisher: University of Michigan Press
ISBN(s)
  • 978-0-472-12656-9 (ebook)
  • 978-0-472-13183-9 (hardcover)
Series
  • Legislative Politics and Policy Making
Subject
  • Political Science:American Politics
  • Political Science:Governance

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The figure plots the coefficients for three negative binomial regression models. The first predicts the total number of Qualifications questions asked of district court nominees; the second predicts the total number of Issues questions for district court nominees; the third predicts the total number of Judicial questions for district court nominees. Significant coefficients for the Qualifications questions model are Divided Government (coefficient: -0.53, SE: 0.11, p less than 0.01); Presidential Election Year (coefficient: -0.33, SE: 0.14, p less than 0.05); Clinton nominee (coefficient: 0.30, SE: 0.12, p less than 0.01); and total questions (coefficient: 0.08, SE: 0.01, p less than 0.01). Borderline statistically significant coefficient for the Qualifications questions model is ABA Rating (Lowest) (coefficient: 0.26, SE: 0.15, p less than 0.10). Statistically insignificant coefficients for the Qualifications questions model are ABA Rating (Middle), Judicial Experience, Opposition Senator, Obama Nominee, and DC or PR Nominee. Significant coefficients for the Issues questions model are Divided Government (coefficient: 0.87, SE: 0.16, p less than 0.01); Clinton Nominee (coefficient: 0.61, SE: 0.16, p less than 0.01); Obama Nominee (coefficient: 1.21, SE: 0.20, p less than 0.01); and Total Questions (coefficient: 0.10, SE: 0.01, p less than 0.01). Statistically insignificant coefficients are ABA Rating (Lowest), ABA Rating (Middle), Judicial Experience, Opposition Senator, Presidential Election Year, and DC or PR Nominee. Significant coefficients for the Judicial questions model are Clinton nominee (coefficient: 0.32, SE: 0.09, p less than 0.01); Obama nominee (coefficient: 0.35, SE: 0.13, p less than 0.01); and total questions (coefficient: 0.04, SE: 0.01, p less than 0.01). Borderline statistically significant coefficient for the Judicial questions model is ABA Rating (Lowest) (coefficient: -0.21, SE: 0.13, p less than 0.10). Statistically insignificant coefficients for the Qualifications questions model are ABA Rating (Middle), Judicial Experience, Opposition Senator, Presidential Election Year, and DC or PR Nominee.

Number of Questions by Category; District Court Nominees; Negative Binomial Regression

From Chapter 5

Fig. 5.1. Number of Questions by Category; District Court Nominees; Negative Binomial Regression

The figure shows the predicted number of questions in the categories of Qualifications questions, Issues questions, and Judicial questions for district court nominees, comparing times of unified and divided government. In times of unified government, District court nominees can expect 2.06 Qualifications questions (with a confidence interval of 1.67 to 2.46); 0.73 Issues questions (with a confidence interval of 0.50 to 0.96); and 1.88 Judicial questions (with a confidence interval of 1.48 to 2.29). In times of divided government, District court nominees can expect 1.21 Qualifications questions (with a confidence interval of 0.94 to 1.49); 1.76 Issues questions (with a confidence interval of 1.38 to 2.13); and 2.27 Judicial questions (with a confidence interval of 1.89 to 2.65).

Predicted Questions by Category (District Nominees); Unified vs. Divided Government

From Chapter 5

Fig. 5.2. Predicted Questions by Category (District Nominees); Unified vs. Divided Government

The figure plots the coefficients for three negative binomial regression models. The first predicts the total number of Qualifications questions asked of noncontroversial circuit court nominees; the second predicts the total number of Issues questions for noncontroversial circuit court nominees; the third predicts the total number of Judicial questions for noncontroversial circuit court nominees. Significant coefficients for the Qualifications questions model is total questions (coefficient: 0.04, SE: 0.01, p less than 0.01). Statistically insignificant coefficients for the Qualifications questions model are ABA Rating (Lowest), ABA Rating (Middle), Judicial Experience, Opposition Senator, Divided Government, Presidential Election Year, Party Balance of the Circuit, DC Circuit, Clinton Nominee, Obama Nominee, and the interaction between Divided Government and Circuit Balance. Significant coefficients for the Issues questions model are Divided Government (coefficient: 1.22, SE: 0.41, p less than 0.01); Presidential Election Year (coefficient: -0.53, SE: 0.27, p less than 0.05); Obama Nominee (coefficient: 0.88, SE: 0.27, p less than 0.01); the interaction between divided Government and Circuit Balance (coefficient: -5.09, SE: 2.10, p less than 0.05), and total questions (coefficient: 0.09, SE: 0.01, p less than 0.01). Statistically insignificant coefficients are ABA Rating (Lowest), ABA Rating (Middle), Judicial Experience, Opposition Senator, Party Balance of the Circuit, DC Circuit, and Clinton Nominee. Significant coefficient for the Judicial questions model is Clinton nominee (coefficient: 0.35, SE: 0.15, p less than 0.05). Borderline statistically significant coefficient for the Judicial questions model is the interaction between Divided Government and Circuit Balance (coefficient: 2.62, SE: 1.51, p less than 0.10). Statistically insignificant coefficients for the Qualifications questions model are ABA Rating (Lowest), ABA Rating (Middle), Judicial Experience, Opposition Senator, Divided Government, Presidential Election Year, Party Balance of the Circuit, DC Circuit, and Obama Nominee.

Number of Questions by Category; Non-controversial Circuit Nominees; Negative Binomial Regression

From Chapter 5

Fig. 5.3. Number of Questions by Category; Noncontroversial Circuit Nominees; Negative Binomial Regression

When a circuit is evenly divided between Republican and Democratic nominees, the difference in the predicted number of questions between times of divided and unified government is 1.9 (p less than 0.05). As the circuit gets more unbalanced (i.e., more Democratic or Republican), the difference in times of unified and divided government decreases; between a circuit balance of .1 and .2, the difference becomes statistically insignificant.

Difference in Num. of Issues Questions; Comparing Unified vs. Divided Gov't

From Chapter 5

Fig. 5.4. Difference in Number of Issues Questions; Comparing Unified vs. Divided Government

Decision making questions between times of divided and unified government is -0.5, though the difference is not statistically significant. As the circuit gets more unbalanced (i.e., more Democratic or Republican), the difference in times of unified and divided government increases; by a circuit balance of .2, the difference becomes statistically significant (a predicted difference of 1.2, p less than 0.05). The predicted difference continues to increase as the circuit balance increases.

Difference in Num. of Judicial Phil./Dec. Making Questions; Comparing Unified vs. Divided Gov't

From Chapter 5

Fig. 5.5. Difference in Number of Judicial Decision Making and Philosophy Questions; Comparing Unified vs. Divided Government

Prosecutor, Clinton Nominee, Obama Nominee, and DC or PR Nominee.

Whether Nominee Received a Question in Category; District Court Nominees; Logistic Regression

From Chapter 5

Fig. 5.6. Whether Nominee Received a Question in Category; District Court Nominees; Logistic Regression

Prosecutor, Divided Government, Party Balance of the Circuit, and total questions.

Whether Nominee is Asked a Question in Key Categories; Non-controversial Circuit Nominees; Logistic Regression

From Chapter 5

Fig. 5.7. Whether Nominee Is Asked a Question in Key Categories; Noncontroversial Circuit Nominees; Logistic Regression

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