gender and us supreme court oral argument on the ...

GENDER AND U. S. SUPREME COURT ORAL ARGUMENT ON THE ROBERTS COURT: AN EMPIRICAL EXAMINATION James C. Phillips* & Edward L. Carter** ABSTRACT The nomination and confirmation of Justice Sonia Sotomayor to the United States Supreme Court rekindled the debate surrounding gender and judicial behavior. While numerous studies have looked at the potential influence of a judge’s gender on voting patterns, there has been no scholarship to date investigating how the interaction of a Justice’s gender and an attorney’s gender, after controlling for other factors, influences judicial behavior during oral argument. This study empirically explores gender and oral argument by content analyzing over 13,000 sentences from 57 oral arguments during 2004–2009, measuring Justices’ levels of information-seeking and word counts. Statistical analysis of the individual Justices showed that having the same gender as the arguing attorney did influence judicial behavior for some of the Court. Furthermore, ideology also interacted with gender matching in a fairly consistent partisan divide. I. INTRODUCTION With the nomination and confirmation of Justice Sonia Sotomayor to the United States Supreme Court, the topic of gender and judicial behavior and decision-making has once again been brought to the foreground in discussion * UC-Berkeley School of Law, PhD candidate in Jurisprudence and Social Policy; Brigham Young University, M.A. in Mass Communication; [email protected]. ** Associate professor of communications, Brigham Young University; LL.M., University of Edinburgh School of Law; J.D., Brigham Young University; [email protected].

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surrounding the Court.1 Possibly most influential in enacting this resurgent interest in gender and jurisprudence have been the remarks of Justice Sotomayor herself. In a speech on the campus of the University of California at Berkeley, then Judge Sotomayor stated: “I would hope that a wise Latina woman with the richness of her experiences would more often than not reach 2 a better conclusion than a white male who hasn’t lived that life.” Justice Sotomayor is not alone in giving an opinion on the potential influence of gender on the judiciary. Agreeing with Justice Sotomayor’s sentiments, the former chief judge of New York State—Judge Judith S. Kaye—commented on the idea that female judges may see cases differently than male judges: “I struggled with it for the 25 years I served as a judge . . . . To defend the idea that women come out different on some cases, I just feel 3 it . . . . I feel it to the depths of my soul.” Regarding a recent case wherein a 4 13-year-old girl was strip-searched at school on suspicion of having drugs, Justice Ginsburg felt that her male colleagues lacked the ability to properly understand the case after several of them indicated during oral argument that they did not find the search problematic: “They have never been a 13-yearold girl . . . . It’s a very sensitive age for a girl . . . . I didn’t think that my 5 colleagues, some of them, quite understood.” Contrarily, though often attributed to Justice Sandra Day O’Connor, Justice Jeanne Coyne of the Minnesota Supreme Court said that her experience as a judge had taught her that “a wise old man and a wise old 6 woman reach the same conclusion.” Such an observation does not speak to the possibility that judges of differing genders may reach the same conclusion via different paths or divergent courtroom behavior. Likewise, the “hope” of Justice Sotomayor and the soul-deep feelings of Judge Kaye, whatever their groundings in the experiences of these judges, cannot be taken as anything beyond anecdotal evidence without reliable empirical investigation. This study attempts to examine that which has been ignored to date—the influence of gender on judicial behavior during Supreme Court 1. The authors acknowledge that Justice Elena Kagan is also now on the Court, but the studies for this Article were completed before her nomination and confirmation. 2. Sonia Sotomayor, A Latina Judge’s Voice, 13 BERKELEY LA RAZA L.J. 87, 92 (2002). 3. Neil A. Lewis, Debate on Whether Female Judges Decide Differently Arises Anew, N.Y. TIMES, June 4, 2009, at A16. 4. Safford Unified Sch. Dist. v. Redding, 129 S. Ct. 2633 (2009). 5. Lewis, supra note 3. 6. Elaine Martin, Women on the Bench: A Different Voice?, 77 JUDICATURE 126, 126 (1993).

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oral argument—and do so in an empirical way in order to produce reliable findings for scholars and practitioners alike. II. BACKGROUND A. Theories of Gender’s Influence Several schools of thought exist as to why and how gender may or may not influence judicial behavior and decision making. One of the most oftcited and analyzed is the different voice perspective, derived from the work 7 of developmental psychologist Carol Gilligan. More specifically, Gilligan argued that women are outsiders in male-dominated professions, causing women to have greater empathy for individuals and groups outside the 8 mainstream. Additionally, women are more likely to “view the resolution of conflicts as a problem of care and responsibility in relationships,” leading to the creation of a “care-based feminine jurisprudence,” as opposed to the more rights-centered approach characterstic of men that leads to clear winners and losers.9 These emotional differences between women and men could lead to differences in how attorneys argue cases and how judges gather information and determine case outcomes, with women judges bringing a 10 “feminine perspective” to their actions and decisions on the bench. Thus 11 gender influences should be found in all legal contexts and areas of law. 12 Similar to Gilligan’s “ethic of care” is the maximalist approach, which posits that differing socialization and life experiences cause men and women

7. See CAROL GILLIGAN, IN A DIFFERENT VOICE: PSYCHOLOGICAL THEORY AND WOMEN’S DEVELOPMENT (1982). 8. Id.; see also Susan L. Miller & Shana L. Maier, Moving Beyond Numbers: What Female Judges Say About Different Judicial Voices, 29 J. WOMEN, POL. & POL’Y 527, 529 (2008). 9. Fiona Kay & Elizabeth Gorman, Women in the Legal Profession, 4 ANN. REV. L. & SOC. SCI. 299, 321 (2008). 10. Suzanna Sherry, Civic Virtue and the Feminine Voice in Constitutional Adjudication, 72 VA. L. REV. 543, 583 (1986). 11. Christina L. Boyd, Lee Epstein & Andrew D. Martin, Untangling the Causal Effects of Sex on Judging, 54 AM. J. POL. SCI. 389, 390 (2010). 12. “Feminist standpoint theorists (i.e., those who take a maximalist approach) privilege women’s ways of behaving and knowing.” Lisa Cosgrove and Maureen C. McHugh, “Deconstructing Difference: Conceptualizing Feminist Research from Within the Postmodern,” in LYNN C. COLLINS, MICHELLE R. DUNLAP, & JOAN C. CHRISLER (EDS.), CHARTERING A NEW COURSE FOR FEMINIST PSYCHOLOGY 23 (2002).

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to diverge in the areas of decision-making, legal reasoning, and values. Furthermore, Professor Phyllis Coontz contends that men and women judges might “attach different weights to the factual aspects of identical 16 situations.” Akin to the different voice theory is the notion of gender schemas. A schema is a cognitive framework that allows one to organize and see the 17 world. Schemas are, among other things, gender influenced because [I]ndividuals naturally assign different attributes, physical and mental, to men and women. Men are viewed as independent, strong, and rational; women are seen as communal, emotional, and nurturing. While these schemas correspond to the perspective offered by “different voice” theory, proponents of this approach argue that their underlying effect is the overrating of men and the underrating of women. Thus, daily events that unconsciously advantage men accumulate to elevate men in society’s eyes while women slowly yet steadily fall behind. Finally, because we tend to form our impressions about men and women from extreme cases (the ultra feminine vs. the ultra masculine), the result is that our view of the sexes in general becomes polarized, super-intensifying our schematic applications of 18 gender attributes to the benefit of one and the detriment of the other. 19

Based on the work of Pitkin, another argument advanced regarding the influence of gender on courts is one of “representational accounts,” wherein female judges are prone to protect other women as representatives of their 20 class. Scholars have posited that if the representational account framework 13. See Patricia Yancey Martin, John R. Reynolds & Shelley Keith, Gender Bias and Feminist Consciousness Among Judges and Attorneys: A Standpoint Theory Analysis, 27 SIGNS: J WOMAN CULTURE & SOC’Y 665 (2002). 14. See MARTHA CHAMALLASS, INTRODUCTION TO FEMINIST LEGAL THEORY (1999). 15. See Ann C. Scales, The Emergence of Feminist Jurisprudence: An Essay, 95 YALE L.J. 1373 (1986). 16. Phyllis Coontz, Gender and Judicial Decisions: Do Female Judges Decide Cases Differently than Male Judges?, 18 GENDER ISSUES 59, 71 (2000). 17. Virginia Valian, The Cognitive Bases of Gender Bias, 65 BROOK. L. REV. 1037, 1044–45 (1999). 18. John J. Szmer, Tammy A. Sarver & Erin B. Kaheny, Have We Come a Long Way, Baby? Female Attorneys Before the United States Supreme Court, 5–6 (2008), http://www.elsblog.org/the_empirical_legal_studi/2007/02/female_attorney.html (last visited Jan. 7, 2011). 19. See HANNA FENICHEL PITKIN, THE CONCEPT OF REPRESENTATION (1967). 20. Boyd et al., supra note 11, at 3–4.

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is accurate, gender effects should only be observed in cases directly 21 involving women-related policy issues. This viewpoint of women judges as representative of women and their causes in general is sometimes called the 22 feminist consciousness perspective. A third stream of theory also emphasizes gender differences in contending that women “possess unique and valuable information emanating from shared professional 23 experiences.” If this is true, then women attorneys or judges might be able to better persuade male judges based on a position of perceived increased 24 credibility in areas such as sexual discrimination. Finally, some theoretical positions posit that there should be little to no gender differences amongst either attorneys or judges. Termed organizational 25 accounts by some and the minimalist approach by others, the argument is made that judges of both genders “undergo identical professional training, obtain their jobs though the same procedures, and confront similar

21. Id. at 4. 22. See Kay & Gorman, supra note 9, at 321–22. 23. Boyd et al., supra note 11, at 4; see also Charles M. Cameron & Craig P. Cummings, Diversity and Judicial Decision-Making on the U.S. Courts of Appeals, 2003 (Mar. 30, 2003) (unpublished manuscript, on file with author), available at http://www.yale.edu/coic/CameronCummings.pdf; Gerard S. Gryski, Eleanor C. Main & William J. Dixon, Models of State High Court Decision Making in Sex Discrimination Cases, 48 J. POL. 143 (1986) (constructing a policy model that predicts a state high court with at least one female member is likely to rule in favor of a female in a noncriminal sex discrimination case); Jennifer L. Peresie, Note, Female Judges Matter: Gender and Collegial Decisionmaking in the Federal Appellate Courts, 114 YALE L.J. 1759 (2005) (finding a correlation between the gender and decision-making of judges in Title VII sex discrimination and sexual harassment cases). 24. Boyd et al., supra note 11, at 5; Peresie, supra note 23, at 1783; see also Cameron & Cummings, supra note 23; Lisa Baldez, Lee Epstein & Andrew D. Martin, Does the U.S. Constitution Need an Equal Rights Amendment?, 35 J. LEGAL STUD. 243, 272–73 (2006) (“[T]he outcomes of sex discrimination suits will depend, at least in some part, on the types of judges interpreting the constitutional provision and the particular facts of the suit itself.”); Kathleen M. Sullivan, Constitutionalizing Women’s Equality, 90 CALIF. L. REV. 735, 739–740 (2002) (noting Ruth Bader Ginsburg’s success as an attorney in convincing the all male U.S. Supreme Court to rule discrimination based on gender as unconstitutional in several cases from the 1970s). 25. Compare, e.g., Darrell Steffensmeier & Chris Hebert, Women and Men Policymakers: Does the Judge’s Gender Affect the Sentencing of Criminal Defendants?, 77 SOC. FORCES 1163, 1166 (1999), and ROSABETH MOSS KANTER, MEN AND WOMEN OF THE CORPORATION (1977) (terming the argument “organizational accounts”), with Miller & Maier, surpa note 8 (terming the argument the “minimalist approach”).

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constraints once on [or before] the bench,” erasing preexisting gender 27 differences. Thus male and female attorneys should argue similarly in both style and substance, and judges should behave and decide cases in similar manners. B. Empirical Evidence To date, evidence of gender influence on court proceedings and decisions has been mixed. Numerous scholars have contended that female 28 judges reach decisions differently than male judges. For example, a study 26. Boyd et al., supra note 11, at 4 (citing Gregory C. Sisk, Michael Heise & Andrew P. Morriss, Charting the Influences on the Judicial Mind: An Empirical Study of Judicial Reasoning, 73 N.Y.U. L. REV. 1377 (1998); Herbert M. Kritzer & Thomas M. Uhlman, Sisterhood in the Courtroom: Sex of Judge and Defendant in Criminal Case Disposition, 14 SOC. SCI. J. 77 (1977)). 27. Steffensmeier & Hebert, supra note 25, at 1165; see also LANI GUINIER, MICHELLE FINE & JANE BALIN, BECOMING GENTLEMEN: WOMEN, LAW SCHOOL, AND INSTITUTIONAL CHANGE (1997); John Gruhl, Cassia Spohn & Susan Welch, Women as Policymakers: The Case of Trial Judges, 25 AM. J. POL. SCI. 308 (1981) (contending that female judges do not convict and sentence defendants differently than male judges); Elaine Martin, Women Within the Judicial System: Changing Roles, in WOMEN IN POLITICS: OUTSIDERS OR INSIDERS? A COLLECTION OF READINGS 215, 222 (Lois Lovelace Duke, ed., 2d ed. 1996) (finding that while gender mattered some, most of the gender differences were being driven by ideology); Barbara Palmer, Women in the American Judiciary: Their Influence and Impact, 23 WOMEN & POL. 91, 95–96 (2001) (noting scholarship on Justices O’Connor and Ginsburg, as well as other appellate courts, that finds no difference between men and women’s “voices”). 28. David W. Allen & Diane E. Wall, Role Orientations and Women State Supreme Court Justices, 77 JUDICATURE 156 (1993) (finding in a sample of state supreme court women justices that they function as representatives of their gender in the pro-women decisions they make compared to men, as outsiders, and provide a different voice); Sue Davis, Susan Haire & Donald R. Songer, Voting Behavior and Gender on the U. S. Courts of Appeals, 77 JUDICATURE 129 (1993) (women federal circuit judges exhibit substantially different voting patterns than their male colleagues in employment discrimination and search and seizure cases); Gryski et al., supra note 23 (constructing a policy model that predicts a state high court with at least one female member is likely to rule in favor of a female in a noncriminal sex discrimination case); Madhavi McCall, Gender, Judicial Dissent, and Issue Salience: The Voting Behavior of State Supreme Court Justices in Sexual Harassment Cases, 1980–1998, 40 SOC. SCI. J. 79 (2003) (finding women justices more likely to take a pro-woman position in cases involving sexual harassment prior to 1992), Madhavi McCall, Court Decision Making in Police Brutality Cases, 1990–2000, 33 AM. POL. RES. 56 (2005) (finding that women justices were 23% more likely to vote the liberal position in police brutality cases after controlling for ideology and other factors); Donald R. Songer & Kelley A. Crews–Meyer, Does Judge Gender Matter? Decision Making in State Supreme Courts, 81 SOC. SCI. Q. 750 (2000) (finding that women judges take more liberal positions than male judges in death penalty and obscenity cases, and that having a woman on a court changes male judge voting patterns).

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of the Michigan State Supreme Court over 13 years found that 59% of the time white Republican female judges abandoned their party to vote to 29 support female litigants in divorce cases. Studies of the correlation between judge voting and gender in Wisconsin and Minnesota reported similar 30 findings. Others have found that in sex discrimination cases women judges 31 were 10% more likely to find for the party alleging discrimination. Similarly, a study of state supreme courts noted that female justices had a higher likelihood of supporting the woman’s side in cases related to property settlement on divorce, birth control, child support, sex discrimination, and 32 sexual assault. At the federal court of appeals level, female judges were more likely than their male counterparts to side with female plaintiffs in 33 cases of employment discrimination. A study of the Ontario Court of Appeal showed that women judges had a higher likelihood of ruling against male litigants in family law cases and defendants in criminal sexual assault 34 cases. Regarding the influence of gender in courtroom interactions between lawyers and judges, a study of Israeli courts indicated that competence of 35 women judges and attorneys was constantly questioned. This same research showed that in the courtroom “judges more often address women lawyers than men lawyers in a nondeferent and even demeaning form and interrupt them more frequently, and witnesses seldom use women lawyers’ 36 professional titles.” However, some have argued that gender, while consequential, has a much more subtle influence than traditionally

29. Elaine Martin & Barry Pyle, Gender, Race, and Partisanship on the Michigan Supreme Court, 63 ALB. L. REV. 1205, 1225 (2000). 30. Elaine Martin & Barry Pyle, Gender and Racial Diversification of State Supreme Courts, 24 WOMEN & POL. 35 (2002). 31. See, e.g., Boyd et al., supra note 11, at 390. 32. See Allen & Wall, supra note 28, at 165. 33. See Sean Farhang & Gregory Wawro, Institutional Dynamics on the U.S. Court of Appeals: Minority Representation Under Panel Decision Making, 20 J.L. ECON. & ORG. 299 (2004); Peresie, supra note 23, at 1761–62; Donald R. Songer, Sue Davis & Susan Haire, A Reappraisal of Diversification in the Federal Courts: Gender Effects in the Courts of Appeals, 56 J. POL. 425, 436 (1994). 34. James Stribopoulos & Moin A. Yahya, Does a Judge’s Party of Appointment or Gender Matter to Case Outcomes?: An Empirical Study of the Court of Appeal for Ontario, 45 OSGOODE HALL L.J. 315, 319 (2007). 35. Bryna Bogoch, Courtroom Discourse and the Gendered Construction of Professional Identity, 24 LAW & SOC. INQUIRY 329, 367 (1999). 36. Kay & Gorman, supra note 9, at 315 (discussing Bogoch’s study).

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perceived. Research has posited that political ideology has a stronger 38 influence than gender on behavior, and that “gender differences can only be understood when looking at conditional effects within other demographic 39 factors or attitudes.” Supporting this, researchers have discovered that litigation teams with higher proportions of women are less likely to earn the vote of conservative justices versus liberal justices on the U. S. Supreme 40 Court. On the other hand, much scholarship has found little to no influence of gender on behavior in court settings. A recent study looked at gender and judicial decisions in thirteen different areas, and only found evidence of a 41 small effect for gender in one: sex discrimination. Another study discovered that a judge’s gender had no significant influence in voting in sex 42 discrimination cases above and beyond the impact of political ideology. Looking more broadly at women’s issues, Walker and Barrow found a judge’s gender to make little difference in federal district court decisions regarding sexual harassment, maternity rights, reproductive freedom, gender 43 discrimination, equal employment rights, and affirmative action. Likewise, a fair amount of scholarship has come to the conclusion that gender does not

37. E.g., Susan W. Johnson, Ronald Stidham, Robert A. Carp & Kenneth L. Manning, The Gender Influence on US District Court Decisions: Updating the Traditional Judge Attribute Model, 29 J. WOMEN, POL. & POL’Y 497, 499 (2008). 38. Michele L. Swers, Are Women More Likely to Vote for Women’s Issue Bills Than Their Male Colleagues?, 23 LEGIS. STUD. Q. 435, 440, 445 (1998). 39. Johnson et al., supra note 37, at 498–99 (citations omitted). For a discussion regarding the relationship between gender and other demographic facts, see Rosalee A. Clawson & John A. Clark, The Attitudinal Structure of African American Women Party Activists: The Impact of Race, Gender, and Religion, 56 POL. RES. Q. 211 (2003) (discussing the impact of race and gender on African American women party activists) and Margaret C. Trevor, Political Socialization, Party Identification, and the Gender Gap, 63 PUB. OPINION Q. 62 (1999) (analyzing the effect of “socialization patterns” on a woman’s party identification). For a discussion of the relationship between gender and political attitudes of women, see Pamela Johnston Conover, Feminists and the Gender Gap, 50 J. POL. 985 (1988) and Elizabeth Adell Cook & Clyde Wilcox, Feminism and the Gender Gap—A Second Look, 53 J. POL. 1111 (1991). 40. Szmer et al., supra note 18, at 27, 34. 41. Boyd et al., supra note 11, at 389–90. 42. Sarah Westergren, Note, Gender Effects in the Courts of Appeals Revisited: The Data Since 1994, 92 GEO. L.J. 689, 690 (2004). 43. Thomas G. Walker & Deborah J. Barrow, The Diversification of the Federal Bench: Policy and Process Ramifications, 47 J. POL. 596, 607 (1985).

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have much of an impact on judicial decision-making or interpretation. Davis ascertained no distinctions in moral reasoning between male and female judges of the Court of Appeals for the Ninth Circuit in opinions for cases related to race discrimination, sex discrimination, and constitutional 45 rights. Hence it is unclear how gender may impact U. S. Supreme Court oral argument. Will male justices treat female attorneys differently than female justices, and vice versa? How will the interaction of ideology and gender play out? Does gender even matter for oral argument? III. DATA MEASUREMENT AND COLLECTION

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A. Measuring Information-seeking In order to create a replicable and relevant measurement of information 47 seeking, we analyzed scholarship relating to questioning from law, rhetoric, sociology, psychology, interpersonal communication and 48 linguistics. Based on this research on questioning, interrogations can be 44. See Gruhl et al., supra note 27, at 319–20 (finding that female judges had the same likelihood of convicting and incarcerating criminal defendants as male judges); Peter McCormick & Twyla Job, Do Women Judges Make a Difference? An Analysis by Appeal Court Data, 8 CAN. J.L. & SOC. 135, 146 (1993) (finding that the gender of a judge does not “make a great deal of difference” in the adjudication of criminal appeals to the Alberta Court of Appeal); Sisk et al., supra note 26, at 1453 (finding that a judge’s gender had no statistical impact on judicial interpretation of the 1988 Sentencing Reform Act). 45. See Sue Davis, Do Women Judges Speak “In a Difference Voice?”: Carol Gilligan, Feminist Legal Theory, and the Ninth Circuit, 8 WIS. WOMEN’S L.J. 143, 171–72 (1992– 1993). 46. The methodology described here is very similar to methodology described in a related article in which we examine an overall picture of oral argument in the Roberts Court. See James C. Phillips & Edward L. Carter, Oral Argument in the Roberts Court: A Qualitative and Quantitative Analysis of Individual Justice Behavior, 12 J. APP. PRAC. & PROCESS (forthcoming 2011), available at http://papers.ssrn.com/sol3/ papers.cfm?abstract_id=1472489. 47. While research from the field of law was dominated by courtroom settings, which some may argue are irrelevant to the proceedings of an appellate case, comments by the Justices as well as findings by Court observers indicate that an appellate trial has remarkable similarities to a traditional courtroom trial. For example, a Justice who is questioning an attorney acts much like an attorney questioning a witness, the questioning Justices’ colleagues function as a jury that the questioning Justice is attempting to persuade, and the attorneys involved in Supreme Court oral argument act as witnesses. 48. For a more in depth survey of questioning, see James C. Phillips & Edward L. Carter, Source of Information or “Dog and Pony Show”?: Judicial Information Seeking

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first categorized into three types that form a continuum of informationseeking: genuine or sincere questions, counterfeit or pseudo-questions, and 49 non-questions or declarations. Further partitioning these question types, 50 genuine questions include open-ended questions (“wh”- questions), which have the greatest amount of information seeking, close-ended or bipolar 51 questions, which have the least amount of information seeking, and disjunctive questions, which are a cross between open- and closed-ended 52 questions. Pseudo-questions are also partitioned into two types: leading questions and rhetorical questions. Leading questions possess slightly more information seeking qualities than rhetorical questions since they can still be answered in the affirmative or the negative. Rhetorical questions, on the other hand, do not really seek a response, though if misinterpreted, they 53 might be responded to. Finally, non-questions, if excluding pseudoquestions, would consist of declarations (see Table 1 for examples).

During U.S. Supreme Court Oral Argument, 1963–1965 & 2004–2009, 50 SANTA CLARA L. REV. 79 (2010). 49. RONALD B. ADLER, LAWRENCE B. ROSENFELD, & RUSSELL F. PROCTOR II, INTERPLAY: THE PROCESS OF INTERPERSONAL COMMUNICATION 200 (8th ed. 2001). 50. J.T. DILLON, THE PRACTICE OF QUESTIONING 20 (1990). 51. Id. 52. More specifically, a disjunctive question is a question that starts off having only two possible answers, such as a yes/no question, but a phrase is added to the end of the question that opens up the possible answers (i.e., “or something else”). Anne Graffam Walker, Linguistic Manipulation, Power, and the Legal Setting, in POWER THROUGH DISCOURSE 57, 73 (Leah Kedar ed., 1987); see also Sandra Harris, Questions as a Mode of Control in Magistrates’ Courts, 49 INT’L J. OF THE SOC. OF LANGUAGE 5, 9–17 (1984) (providing an elaborate classification scheme for the different types of questions); MARK V. REDMOND, COMMUNICATION: THEORIES AND APPLICATIONS 220 (2000). 53. IRENE KOSHIK, BEYOND RHETORICAL QUESTIONS: ASSERTIVE QUESTIONS IN EVERYDAY FUNCTION 1 (2005).

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Table 1: Explanations and Examples of Information-seeking Scale Level’s Value 1

Name

Explanation

Example

Wh- question

An open-ended question using who, what, when, where, why or how

2

Disjunctive question

A closed question with an add-on that allows room to answer more openly

3

Bipolar question

4

Tag or Leading question

5

Rhetorical question

A question with only two answer options, such as yes/no, true/false, etc. A leading question, usually framed in the negative, that implies a certain answer A question that does not have an answer or where an answer is not sought

6

Declaration

In what way are you claiming the First Amendment applies to this case? Are you claiming the First Amendment applies to this case, or are you claiming something else? Are you claiming the First Amendment applies to this case? You are claiming the First Amendment applies to this case, are you not? How in the world am I supposed to believe your claim that the First Amendment applies to this case? The First Amendment does not apply to this case.

A statement question mark

without

a

From these question types and their relative degrees of information seeking, a six-point scale was created (see Figure 1). With this ordinal-type scale every sentence spoken in oral argument by a Justice is assigned a numeric score so that an average information seeking score can be generated per Justice for each side to whom the Justice speaks. The higher the information-seeking score (ISS) a Justice receives, the more information 54 seeking he or she is engaging in.

54. In previously published research we have had the information-seeking scale reversed such that a 1 would represent a wh- question and a 6 would represent a declaration. However, due to the unintuitive nature of having higher numbers indicate lower information seeking, we subsequently reversed the scale.

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Figure 1: Degree of Information-seeking Scale Less information seeking

Non-question

More information seeking

Pseudo-question

Close-ended question

Open-ended question

1

2

3

4

5

6

Declaration

Rhetorical

Leading

Bipolar

Disjunctive

Wh-

Examples and explanations of each question type (or level of the scale) can be found in Table 1.

B. Case Selection The cases examined in this study were selected using random stratified sampling to ensure cases with varying scenarios. The five case types sampled for were (1) woman attorney arguing, (2) solicitor general as main party, (3) solicitor general as amicus party, (4) non-solicitor general amicus party, and (5) no amicus or solicitor general attorneys. For each of the four terms spanning 2005 to 2008, two cases were randomly sampled from each of the 55 five categories. Normally this would result in ten cases for each year (two cases multiplied by five categories), but in both the 2005 and 2008 terms there was only one case that fell into the “non-solicitor general amicus party” category, resulting in nine cases selected for those two terms. Thus a total of thirty-eight cases were randomly selected for analysis from the four terms. Additionally, cases from the 2005 term were only selected if they were argued after the date that Justice Alito joined the Court. Furthermore, data from nineteen cases related to the freedoms of speech and press from the 2004 to 2007 terms used in a previous study were compared to the data collected from the thirty-eight randomly selected cases. Since a difference of means test showed the data from the two samples to not differ in a statistically significant way, those nineteen cases were added to the initial thirty-eight, bringing the total number of cases included in the study to fiftyseven (see Appendix II for a complete list). Some may feel that sampling cases such that only approximately 20% will include female attorneys will result in a disproportionately low number of female attorneys in the dataset. However, previous research noted that between 1993 and 2001, only 13.91% 55. Each case in a term was assigned a number, and then each of the five case types were color-coded. Two cases were then randomly selected from each case type using a random number generator that can be found at http://www.randomizer.org/form.htm.

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of attorneys arguing in the United States Supreme Court oral arguments were 56 female. A look at Table 2 shows the percentage of women litigators in oral argument for each term from which our sample was drawn is in line with previous findings, indicating our dataset is not skewed toward under57 representing the proportion of attorneys that are women. Table 2: Percentage of Attorneys that are Women Percentage of attorneys that are women among all cases Percentage of attorneys that are women among sampled cases

2005 11.11%

2006 14.67%

2007 16.19%

2008 15.54%

16.00%

14.81%

28.00%

20.83%

C. Coding Procedures Every sentence spoken by a Justice during oral argument was given an information-seeking score ranging from 1 to 6. From this an average score per side was created for each Justice. If a Justices failed to speak to a side in oral argument he or she received a zero for his or her information-seeking score. If a Justice did not engage either side in a case, then no score was given for that case due to the possibility the Justice may not have even attended oral argument. Additionally, the number of words a Justice uttered to each side was counted. Similar to information-seeking scores, a zero was given if a Justice did not speak to one side, and nothing recorded if the Justice did not speak to either side. Six coders were used in the analysis, with some overlap of case coding in 58 order to ensure reliability. Each coder had to achieve a high degree of intercoder reliability on practice material before being allowed to score the 59 actual cases. Coders were instructed that in instances where it was not clear 56. Tammy A. Sarver, Erin B. Kaheny & John J. Szmer, The Attorney Gender Gap in U. S. Supreme Court Litigation, 91 JUDICATURE 238, 241 (2008). 57. For 2005, only the cases argued after Justice Alito took the court were looked at for computing the 2005 term’s percentage of women attorneys in oral argument. 58. The authors wish to thank Zach Anderson, Megan Moench, Rob Cook, Anesha Brown, and Josh Guest for their invaluable coding assistance. 59. All coders achieved a .90 or better measured with Krippendorff’s alpha. Krippendorff’s alpha can be used to measure the intercoder reliability of nominal, ordinal, interval and ratio-level data, and corrects some of the deficiencies of other well-known measures, such as percent agreement, Scott’s pi, Cohen’s kappa, Pearson’s r, and Holsti’s cr. Klaus Krippendorff, Reliability in Content Analysis: Some Common Misconceptions and Recommendations, 30 HUM. COMM. RES. 411, 428–29 (2004); Andrew F. Hayes & Klaus

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which of two categories a sentence should be placed in, the category higher on the scale (meaning more information seeking) should be chosen. From the thirty-eight randomly selected cases 7817 sentences were analyzed, and from the nineteen freedom of speech or press cases 5512 sentences were analyzed, totaling 13,329 sentences from the fifty-seven cases included in the study. Additionally, since it may not be the quality of the verbal interaction between Justices and counsel that matters, but instead just the sheer quantity of words spoken by a Justice, the average word count for each Justice for each side he or she interacted with during oral argument was recorded. Some may argue that information-seeking scores and word counts are measuring the same phenomenon. However, when excluding instances where a Justice 60 does not speak since both the ISS and word count would be zero, 61 correlation is low, and when including non-speaking observations 62 correlation is practically non-existent, indicating that information-seeking scores and word counts are distinct constructs. D. Control Variables Because it may be other factors besides gender that are driving judicial behavior during oral argument, several other variables were included in the study. As Justices may interact differently with more experienced attorneys, a variable was included that represented a particular lawyer’s total number of 63 prior appearances before the Supreme Court. Attorneys who have

Krippendorff, Answering the Call for a Standard Reliability Measure for Coding Data, 1 COMM. METHODS & MEASURES 77 (2007) (outlining different methods of measuring an intercoder and recommending Krippendorff’s alpha as the standard measure). Krippendorff’s alpha was measured in SPSS 16.0 using a macro that can be found at http://www.comm.ohiostate.edu/ahayes/SPSSpercent20programs/kalpha.htm. 60. Such instances will sometimes be termed non-speaking observations hereafter. The “observation” is from the point of view of the researcher indicating we observed no speaking, and should not be confused with a Justice making a verbal observation during oral argument, which cannot happen if he or she does not speak. 61. Spearman’s Rho = -.326, p < .001, N = 762. 62. Spearman’s Rho = .009, p = .009, N = 864. 63. This variable was logged in order to account for the effect of diminishing returns wherein additional experience at the low end may make a difference. However, note that once experience levels reach a certain point little impact is gained from further appearances before the Court. For the influence of attorney experience on judicial decision-making, see Kevin T. McGuire, Repeat Players in the Supreme Court: The Role of Experienced Lawyers in Litigation Success, 57 J. POL. 187 (1995); Paul J. Wahlbeck, The Life of the Law: Judicial Politics and Legal Change, 59 J. POL. 778, 794 (1997); Paul J. Wahlbeck, The Development of

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previously clerked for the Court may be treated differently than attorneys 64 who have not, so a dichotomous variable was created with 1 indicating Supreme Court clerkship experience and 0 representing no such experience. Being the petitioner in the case may result in different treatment compared to being the respondent, so a petitioner dichotomous variable was created with a 1 representing the attorney was arguing for the petitioner and a 0 indicating the attorney was arguing for the respondent. Attorneys for amicus parties may receive different treatment during oral argument than attorneys for the main parties to a case, so an amicus party dichotomous variable was included with a 1 indicating the attorney represented an amicus party and a 0 meaning the attorney represented the main party in a case. Since the Solicitor General has traditionally been referred to as the “Tenth Justice,” a dichotomous variable was created with a 1 indicating the attorney was from the Solicitor General’s office and a 0 indicating the attorney was not. While having to share time with another attorney during oral argument may not impact information-seeking by the Justices, it will surely limit the amount of words uttered by Justices to attorneys, so a dichotomous variable was included with a 1 representing an attorney who did not have the full thirty minutes to argue and a 0 meaning that the attorney did not have to share his or her time with anyone else. As previous research has shown that many of the Justices tend to treat attorneys representing ideological positions similar to their own differently 65 than attorneys for opposing ideological positions, a dichotomous variable was created in which a 1 meant that the attorney’s side was of the opposite ideology of the Justice’s (i.e., conservative or liberal), and a 0 indicating the 66 attorney represented the same ideology as the Justice’s. Other researchers a Legal Rule: The Federal Common Law of Public Nuisance, 32 L. & SOC. REV. 613, 623, 630–31 (1998). 64. For an overview of the effect of clerkship experience on judicial decision-making, see Kevin T. McGuire, Lobbyists, Revolving Doors and the U. S. Supreme Court, 16 J.L & POL. 113 (2000). 65. See Phillips & Carter, supra note 46. 66. The ideological position of a party in a case was determined using the Spaeth Database, wherein each party is coded as liberal or conservative. The Supreme Court Database, http://scdb.wustl.edu/ (last visited Jan. 25, 2011). The ideological position of each Justice was determined using Martin-Quinn scores with a negative score meaning the Justice was liberal and a positive score representing a conservative Justice. Andrew D. Martin & Kevin M. Quinn, Dynamic Ideal Point Estimation via Markov Chain Monte Carlo for the U.S. Supreme Court, 1953–1999, 10 POL. ANALYSIS 134, 146 tbl.1 (2002). The Martin-Quinn scores were lagged one year to avoid reverse causality issues since the scores for a particular year are created from that Justice’s voting on cases in that year.

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have found that Justices treat parties differently based on their capability or power, with government or big corporations receiving different treatment 67 than individuals or non-profit organizations. To control for this, a 68 capability scale was adopted from the Szmer article, with a 1 for individual persons, a 2 for non-Fortune 500 corporations, a 3 for interest groups, a 4 for sub-national governments, a 5 for Fortune 500 corporations, and a 6 for the 69 United States. A dichotomous gender variable was created with a 1 meaning the attorney was a woman and a 0 representing male attorneys. Finally, there may be an interaction between the gender of the attorney and 70 whether the ideologies of a Justice and a party match, a dichotomous variable was created with a 1 indicating a female attorney of the opposite ideology as the Justice, and a 0 representing all other instances. IV. FINDINGS This section of the paper consists of two parts. First, the oral argument behavior of each Justice will be individually examined. Then, patterns that emerge looking at all of the Justices simultaneously will be shown and discussed. A. Chief Justice Roberts For information seeking, Chief Justice Roberts’ average ISS per attorney in oral argument is 2.11. When not including a possible interaction of gender and ideology, two variables reach statistical significance (p < .05) and one variable approaches significance (p < .10; see Appendix I for regression tables). For petitioners, Chief Justice Roberts’ ISS increases by .431, which indicates that his questions to those parties sought more information. While this might not appear to be a very substantial increase, compared to his average ISS, a petitioner receives 20.4% more information seeking questions from the Chief Justice. As higher information seeking indicates more leeway 67. Donald R. Songer & Reginald S. Sheehan, Who Wins on Appeal? Upperdogs and Underdogs in the United States Courts of Appeals, 36 AM. J. POL. SCI. 235, 254–57 (1992); Donald R. Songer, Reginald S. Sheehan & Susan Brodie Haire, Do the “Haves” Come Out Ahead Over Time? Applying Galanter’s Framework to Decisions of the U. S. Courts of Appeals, 1925–1988, in IN LITIGATION: DO THE “HAVES” STILL COME OUT AHEAD? 85, 103– 04 (Herbert M. Kritzer & Susan S. Silbey eds., 2003). 68. Szmer et al., supra note 18. 69. Id. at 22–23. 70. For further discussion of the interplay of gender and ideology, see id.

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for the questioned attorney to answer, and one can think of information seeking as a corollary of courtroom control, Chief Justice Roberts appears to be giving more control to petitioners. When including the gender-ideology interaction variable, the petitioner variable remains statistically significant and slightly increases to .444. Gender is the other statistically significant variable predicting the Chief Justice’s information seeking scores. When the gender-ideology interaction variable is excluded, being a woman attorney is associated with a statistically significant decrease in the Chief Justice’s information-seeking score by .609. Thus, controlling for other factors that might influence information-seeking, Chief Justice Roberts appears to be allowing less leeway to female attorneys in oral argument by engaging in lower information seeking with them. One caveat is that lower levels of information-seeking cannot be normatively termed “good” or “bad.” For example, a Justice could be making hostile comments that do not allow attorney rebuttal, or the Justice could be making helpful comments that allow an attorney to get out of sticky questioning by another Justice. By including the gender-ideology interaction variable in the regression model, being a female attorney is no longer statistically significant, though it approaches statistical significance, decreasing ISS by .458. The only other variable to approach statistical significance in the two ISS regression models for Chief Justice Roberts was the party capability variable; increasing party capability decreased ISS by .149 (without gender-ideology interaction variable, p = .053) and .148 (with the interaction variable, p = .058). Thus Chief Justice Roberts engaged in less information seeking (or more control) with more powerful or capable parties. The included variables only explained about 9% of the variation in the Chief Justice’s informationseeking scores. Turning to the quantity of verbal activity (measured by word counts) as compared to the quality of verbal activity (information-seeking scores), Chief Justice Roberts spoke, on average, 241 words to every attorney that argued before him, or the equivalent of one double-spaced page of text. The only variable to achieve statistical significance was ideological 71 incompatibility. In the model that did not include the gender-ideology 71. Because the variables measuring whether an attorney represented an amicus party and whether an attorney had to share his or her oral argument time with another attorney were so highly correlated, they did not individually show up as statistically significant. However, a test of joint significance did reveal that together the variables achieved statistical significance. This finding is of little interest and these variables were mainly included to control for the fact that Justices will speak less to attorneys who have less time during oral argument.

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interaction variable, Chief Justice Roberts averaged speaking 154.2 words less to lawyers with a political ideology opposing his; in the model including the gender-ideology interaction variable, Chief Justice Roberts averaged 158.1 words less. Hence, in this sample of cases, Chief Justice Roberts speaks less to attorneys representing “liberal” parties. The gender of the attorney was irrelevant regarding the Chief Justice’s amount of verbal engagement, either by itself or interacting with ideology. Finally, the variables included in the word count regression models explained 22% to 23% of the variations in Chief Justice Roberts’ word count levels. B. Justice Stevens Justice Stevens averaged a 1.80 for information seeking, which includes instances where he did not speak to an attorney and therefore received a 0 for the attorney he did not engage. Both models (with and without genderideology interaction) had two statistically significant predictors of information seeking and one predictor that approached statistical significance. As the experience of an attorney before the Court increased by 1% (or one additional time having argued before the Court), Justice Stevens’ information seeking increased by either .288 or .287—an increase of 16%. Furthermore, Justice Stevens’ ISS decreased .932 and .927 for attorneys representing parties opposite of Justice Stevens’ ideology (or conservative parties). This 52% decrease is substantial, indicating that Justice Stevens exercises greater verbal control in his engagements with parties that oppose his ideological leanings. Finally, attorneys from the Solicitor General’s office also experienced less information seeking from Justice Stevens (p < .10). However, the fact that the Bush Administration tended to side with the conservative party in a case (though not always) likely influenced this result, and therefore it may not be a function of anything peculiar to an attorney being from the Solicitor General’s office beyond ideology. The variables included in the word count regression models explained about 15% to 16% of Justice Stevens’ information seeking. Justice Stevens averaged 109 words uttered per attorney in oral argument, with the included variables explaining between 16% and 18% of his word count levels. In both models, three variables achieved statistical significance: whether or not the attorney was the petitioner, whether or not the attorney represented an amicus party, and whether or not the attorney represented an ideological position in contrast to Justice Stevens. All three of these variables resulted in Justice Stevens speaking less. It is hardly surprising that Justice Stevens (or any Justice) would speak less to an amicus party. It is interesting, though, that Justice Stevens averaged 61 fewer words

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to petitioner attorneys in the model without the gender-ideology interaction variable and 56 fewer words to such attorneys in the model with the genderideology interaction variable. This may be because the very fact the Court grants certiorari may reflect a higher probability of overturning a lower court, indicating respondents have a more difficult case to make. Similar to the Chief Justice, Justice Stevens speaks between 77 and 103 fewer words to attorneys who represent parties opposite the Justice’s regarding ideology (i.e., conservative parties). This represents a substantial 71% to 94% decrease in verbal activity. In addition, while the gender of the attorney did not matter in the first model regarding word counts, when including the gender-ideology interaction variable, both gender and the interaction term achieved statistical significance. More specifically, Justice Stevens speaks nearly 93 fewer words to female attorneys (an 85% drop from his average activity level), but when interacting with an attorney of an opposing ideology he averages 114 more words spoken, a 105% increase over his normal word count level. C. Justice Scalia Justice Scalia, currently the second longest serving Justice on the Court, had an average information seeking score of 1.69 in the cases sampled for this study, one of the lowest of the Court’s present members. The investigation of predictors of Justice Scalia’s information seeking revealed no significant factors. In contrast, the word count models did turn up several significant predictors of the quantity of Justice Scalia’s verbal activity during oral argument, with the variables in totality explaining 27% to 28% of the variance in his word count levels. Understandably, Justice Scalia spoke less to amicus party attorneys and attorneys who had to split their time with other attorneys. Also, the experience level of an attorney was statistically significant with Justice Scalia, who spoke 40.6 and 36.6 fewer words for every 1 percentage increase in experience an attorney had arguing before the Supreme Court. Given that Justice Scalia averaged speaking 290 words to every attorney he saw in oral argument, the decrease in words spoken to more experienced attorneys equates to a 10% to 14% drop in verbal activity. Moreover, while attorney gender was not a significant variable in either model, the gender-ideology interaction term did approach statistical significance (p = .08), as Justice Scalia averaged speaking almost 156 fewer words to female attorneys representing liberal positions, a decrease of about 54%.

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D. Justice Kennedy Justice Kennedy had an average information seeking score of 1.96. Of the two regression models looking at predictors of his ISS, only one variable—whether or not an attorney represented a petitioner—mattered, achieving statistical significance in the model without the gender-ideology interaction term, and approaching statistical significance (p = .059) in the model with the interaction term. Thus, Justice Kennedy recorded the higher information seeking scores of .451 and .469 for petitioner attorneys, an increase in information seeking of 23% to 24%. Regarding word counts, Justice Kennedy averaged 148 words per side. No variable reached statistical significance in either model, though several approached significance and two variables were jointly significant (party capability and amicus party). Most important to this study, the gender of the attorney was one of the variables that approached statistical significance in both the model without the gender-ideology interaction (p = .055) and the model with the interaction term (p = .081). Hence, Justice Kennedy speaks, on average, 58 to 73 more words to female attorneys versus male attorneys, an increase of 39% to 49%, All of the variables combined explained 12% to 13% of the variance in Justice Kennedy’s word count levels. E. Justice Souter Justice Souter had an average information-seeking score identical to Justice Scalia’s: 1.69. No variable predicted Justice Souter’s information seeking in a statistically significant manner, though several approached significance. In the model without the gender-ideology interaction variable, both ideological compatibility (p = .074) and party capability (p = .052) decreased Justice Souter’s information seeking by .639 (38%) and .232 (14%) respectively. Therefore, Justice Souter was more likely to seek less information (or engage in more verbal control) with attorneys for parties that ideologically opposed him and had greater capability. However, when adding the gender-ideology interaction term, these variables no longer approach significance. Instead both the gender (p = .068) and gender-ideology interaction (p = .073) variables mattered. When speaking to female attorneys, Justice Souter engaged in about 50% more information seeking (ISS increase of .839). However, when dealing with female attorneys representing ideologically opposing (or conservative) parties, Justice Souter engaged in 61% less information seeking (ISS decrease of 1.025). Because ideological incompatibility was separately controlled for, it was not just that the female attorneys are on the opposite side of the ideological spectrum that explains

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Justice Souter’s change in behavior, but instead the combination of being female and conservative that leads to his increased verbal control during oral argument. Looking at word counts, Justice Souter averaged speaking 248 words to every attorney he saw during oral argument, with the included variables explaining 12% to 13% of the variation in his word count totals. Only one variable—amicus party—reached statistical significance, but the party capability and attorney experience, as well as the attorney experience and Solicitor General’s office attorney variables jointly approached statistical significance. Gender, either by itself or interacting with ideology, did not matter in predicting Justice Souter’s word count levels in oral argument. F. Justice Thomas Of the 57 cases analyzed in the study, Justice Thomas only spoke in one of them: Holmes v. South Carolina. In that case he spoke to just one of the three attorneys, uttering a total of 129 words with an ISS of 1.29. Thus, analysis was unable to be performed on Justice Thomas given the scarcity of 72 data. G. Justice Ginsburg Justice Ginsburg averaged 2.03 in information seeking scores, with the included variables explaining 14% to15% of the variance in her scores. Two variables—amicus party and Solicitor General’s office attorney—reached statistical significance. For attorneys representing an amicus party Justice Ginsburg had an average decrease in ISS of 1.555, or a 77%, in model one and a decrease of 1.564, or 77% in model two. On the other hand, Justice Ginsburg engaged in higher information seeking with attorneys from the Solicitor General’s office with information seeking scores increasing by 1.019, or 50%, in model one, and 1.035, or 51%, in model two. Examining word counts, Justice Ginsburg averaged speaking 167 words to each attorney she saw, with the included variable explaining 24% to 26% of the variation in her word count totals. Attorneys representing an amicus party (p < .08) and attorneys sharing time with another attorney (p < .05) both heard less from Justice Ginsburg by 60 to 64 and 92 to 106 words respectively. In the regression model without the gender-ideology 72 For a discussion of why Justice Thomas does not speak much during oral argument, see Phillips & Carter, supra note 48, at 159 n.248 and the articles cited therein.

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interaction, representing a party of the opposing ideology resulted in 66 more words from Justice Ginsburg, an increase of 40%. However, when including the interaction term, ideological incompatibility ceased to matter, and instead being a female attorney did matter with Justice Ginsburg speaking an average of 74 fewer words to female attorneys than male attorneys, a decrease of 44%. Previous research has shown that the more Justice 73 Ginsburg speaks to a side, the less likely she is to vote for that side. Thus, speaking less to female attorneys may in fact reflect that Justice Ginsburg favors the sides that those attorneys represent, though further research would be needed to definitively make that argument. H. Justice Breyer Justice Breyer, with an ISS of 1.52, had the lowest information seeking scores of any of the Justices excepting the taciturn Justice Thomas. The included variables could only explain 10% to 11% of the variance in his ISS. For Justice Breyer, an attorney having clerked for the Supreme Court mattered regarding information seeking, increasing his ISS by .427 to 440 for such attorneys, an increase of 28% to 29%. The only other variable that mattered in predicting Justice Breyer’s information seeking scores was whether an attorney had to split time with someone else. That variable decreased Justice Breyer’s ISS by .506 to .550, or 33% to 36%. This data could reflect that Justice Breyer is more controlling of such attorneys because he realizes they have less time and he wants to get quickly and directly to items of most interest to him. Another possible explanation is that Justice Breyer feels he has less time to make a point to his fellow Justices via his questioning, and so gives the attorney less leeway in his verbal remarks. Justice Breyer also had the highest word count of all of the Justices, averaging 297 words per attorney. The variables in this study explained 39% of the variation in his word count levels. Only two variables reached statistical significance in the two word count regression models. Being a petitioner resulted in Justice Breyer speaking 245 to 246 fewer words, a substantial reduction of 83%. Also, not surprisingly, Justice Breyer spoke between 204 and 212 fewer words to attorneys who had to share their 30 minutes of allotted oral argument time with another attorney. Neither the gender of the attorneys, nor the ideology of the parties they represented, mattered in predicting Justice Breyer’s oral argument behavior.

73 Phillips & Carter, supra note 46, at 60.

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I. Justice Alito Justice Alito’s average information seeking score was 1.93, though this number was somewhat deflated by the fact that more than any other Justice (except Justice Thomas) Justice Alito will refrain from speaking to an attorney. The included variables explained 12% to 13% of the fluctuation in Justice Alito’s information-seeking scores. Only the ideological incompatibility variable reached statistical significance, decreasing Justice Alito’s ISS by .980 to 1.057, or 51% to 55% for attorneys representing liberal positions. Three other variables, however, approached statistical significance. For each additional case an attorney had previously argued before the Supreme Court, Justice Alito engaged in .238 to 249 more information seeking, an increase of 12% to 13% (model 1: p = .098; model 2: p = .079). With attorneys representing petitioners Justice Alito had information-seeking scores .594 to .606 higher, an increase of 31% (model 1: p = .074; model 2: p = .085). Finally, Justice Alito’s ISS were lower with attorneys from amicus parties by 1.135-1.141, a drop of 59% (model 1: p = .061; model 2: p = .061). Turning to verbal quantity, Justice Alito averaged speaking about 73 words to each attorney that stood before him in oral argument, by far the lowest of all the current Justices except for Justice Thomas. The included variables could only explain about 10% to 11% of the variance in Justice Alito’s word count totals. In addition, only one variable—splitting time with another attorney—reached statistical significance in predicting Justice Alito’s word counts. However, two other variables approached statistical significance. If an attorney had clerked for the Supreme Court, Justice Alito spoke, on average, 31 fewer words to them than to attorneys who had not clerked at the Supreme Court, a decrease of 42% (model 1: p = .076; model 2: p = .080). If Justice Alito and an attorney’s party were ideologically incompatible, Justice Alito spoke 46 to 48 more words to that attorney, an increase of 63% to 66% (model 1: p = .055; model 2: p = .064). J. The Court Overall Evaluating the Justices individually makes it more difficult to discern patterns across the Court. This section first analyzes the significance of the included variables on all of the Justice’s simultaneously, and then turns to patterns of gender and gender-ideology interaction. As can be seen in Table 3, it is difficult to pigeonhole all of the Justices into one explanatory model

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given that there is so much variation between which variables predict their information seeking and word counts. Table 3: Predictors of Individual Justices’ Oral Argument Behavior ISS Model 1 AlitoStevens+ Breyer+

ISS Model 2 AlitoStevens+ Breyer+

Alito+ Kennedy+ Roberts+ AlitoGinsburg-

Alito+ Kennedy+ Roberts+ AlitoGinsburg-

Sol. Gen. Office Att. Split Side

Ginsburg+ StevensBreyer-

Ginsburg+ StevensBreyer-

Ideological Incompatibility

Alito+ SouterStevens-

Alito+ Stevens-

Capable Party Scale Female Attorney

RobertsSouterRoberts-

Roberts-

Logged Att. Experience SCOTUS Clerk Experience Petitioner Amicus Party

RobertsSouter+

WC Model 1 Scalia-

WC Model 2 Scalia-

Alito-

Alito-

BreyerStevens-

BreyerStevens-

GinsburgScaliaSouterStevens-

GinsburgScaliaSouterStevens-

AlitoBreyerGinsburgKennedyScaliaAlito+ Ginsburg+ RobertsStevens-

AlitoBreyerGinsburgRobertsScaliaAlito+ RobertsStevens-

Kennedy+

GinsburgKennedy+ StevensFemale*Ideology SouterScalia+ Stevens+ Bold = statistically significant predictor (p < .05); Italics = predictor approaching statistical significance (p < .10).

Only three variables, all in the word count models, reached or approached statistical significance in predicting half or more of the Justices’ behavior. And two of those variables—amicus party and split side—while having the same effect across all of the Justices of depressing word counts, are rather uninteresting in that Justices should speak fewer words to attorneys representing amicus parties or parties that have to share their time with another attorney. The only variable of interest of the three—whether or not a Justice and a party have ideological compatibility—does not produce consistent results with ideological incompatibility increasing some Justices’

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word counts and decreasing others. Thus a catchall model of judicial behavior is difficult to build based on this data, providing support for the 74 behavioralist model of judicial behavior. More important to this study, for six of the eight (or 75%) of the Justices analyzed, gender matters, resulting in significant differences in information seeking or word counts. Furthermore, when breaking down the three genderrelated variables by information seeking and word counts, a pattern emerges wherein conservative and liberal Justices are affected differently by gender. For example, the four liberal Justices all engage in higher levels of information seeking with female attorneys than male attorneys, whereas all but one of the conservative Justices have lower information seeking scores with female attorneys versus male attorneys (and the one conservative Justice with an increase in information seeking has only a minimal increase; see Figure 2). Thus the average difference for information seeking scores for a liberal Justice is a 20.4% increase, while the average difference for conservative Justices is a 13.8% decrease.

74. The behavioralist model posits that it is factors specific to the individual Justices, such as their gender, race, ethnicity, experience, beliefs, etc., that influence their behavior and decision making. Such Justice-specific factors are less or non-significant in other major models (legal, attitudinal, and strategic/rational choice). See LAWRENCE S. WRIGHTSMAN, THE PSYCHOLOGY OF THE SUPREME COURT 109–32 (2006) (detailing the legal, attitudinal, and strategic models of judicial decision-making); Joel B. Grossman, Social Background and Judicial Decision-Making, 79 HARV. L. REV. 1551 (1966).

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Figure 2: Average Percent Change in ISS for a Female Attorney Compared to a Male Attorney

A similar, though not as clean, partisan divide occurs when examining the impact of engaging with a woman attorney on Justices’ word counts (see Figure 3). All of the conservative Justices spoke more to female attorneys than to male attorneys, averaging 15% more words spoken to female lawyers in oral argument. On the other hand, three of the four liberal Justices spoke less to female attorneys, averaging 9% fewer words to female lawyers.

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Figure 3: Average Percent Change in WC for a Female Attorney Compared to a Male Attorney Effect of Female Attorney on Word Counts

However, given the high probability that women attorneys are more likely to represent liberal parties compared to conservative ones, much of the apparent effect of gender on judicial behavior might actually be the influence of ideology. Therefore, examining the impact of female attorneys on the Justices’ information seeking and word counts after controlling for ideological incompatibility will show a more accurate picture of how an attorney’s gender may be influencing Supreme Court oral argument (see Figure 4).

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Figure 4: Average Percent Change in ISS for a Female Attorney Compared to a Male Attorney after Controlling for Ideological Incompatibility Effect of Female Attorney on ISS after Controlling for Ideological Incompatibility

A pattern of partisan differences in behavior still emerges after controlling for ideology, though the directions are still the same, with liberal Justices increasing information seeking with female attorneys by an average of 23.9% and conservative Justices decreasing information seeking with female attorneys by an average of 3.3%. The main difference between the female attorney variable’s influence before and after controlling for ideology was that both liberal and conservative Justices engaged in more information seeking than when not controlling for ideology. Looking at gender’s impact on word counts after controlling for ideology’s influence still shows a general trend of partisan distinctions, as conservative Justices spoke on average 25.9% more words to female attorneys compared to male attorneys and liberal Justices spoke on average 3% more to female versus to male attorneys (see Figure 5). Looking at this information graphically indicates all of the four conservative Justices spoke more to female attorneys after controlling for ideology, and three of the four liberal Justices spoke less to female attorneys after controlling for ideology. The reason that the liberal Justices overall average a slight increase in word counts to female attorneys is the rather large effect of Justice Stevens’ behavior on the liberal cohort of Justices.

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Figure 5: Average Percent Change in Word Counts for a Female Attorney Compared to a Male Attorney after Controlling for Ideological Incompatibility Effect of Female Attorney on Word Count after Controlling for Ideological Incompatibility

Investigating the impact of gender and ideology leads to a variable representing a female attorney of the opposite ideological persuasion as the Justice with whom she is interacting. Again a partisan split is evident as liberal Justices averaged a 25.5% increase in information seeking with conservative female attorneys, whereas conservative Justices averaged a 20.1% decrease in information seeking with liberal female attorneys (see 75 Figure 6). These findings are similar to the investigation of just gender and gender after controlling for ideology in that liberal Justices have higher information-seeking scores and conservative Justices have lower information-seeking scores for female attorneys under all circumstances.

75. To be clear, the attorney herself may or may not be conservative or liberal, but the party she is representing stands for a liberal or conservative position, and thus the ideology is transferred to her as that party’s spokesperson in Court.

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Figure 6: Average Percent Change in ISS for a Female Attorney of Opposing Ideology Effect of Female Attorney of Opposite Ideology on ISS

Contrarily, examining word counts presents a different picture. Whereas conservative Justices spoke more and liberal Justices spoke less to female attorneys both when controlling and not controlling for the influence of ideological incompatibility, the findings are reversed when examining female attorneys representing a party of an opposing ideological position (see Figure 7). Thus, liberal Justices spoke an average of 60.4% more words to female attorneys arguing for conservative positions, and conservative Justices on average uttered 21.7% fewer words to female attorneys representing liberal positions.

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Figure 7: Average Percent Change in Word Counts for a Female Attorney of Opposing Ideology Effect of Female Attorney of Opposite Ideology on Word Count

It has been previously noted that for five of the Justices—Chief Justice Roberts and Justices Stevens, Scalia, Souter and Ginsburg—the more they speak to one side the less likely they are to vote for that side. However, this study did not include the possible impact of attorney gender on an individual Justice’s voting, so it would be purely speculative to posit the implications for voting based on these findings regarding word counts. V. CONCLUSION The findings of this study of gender and judicial behavior during oral argument are twofold. First, gender does matter, but not the gender of the Justice. Justice Ginsburg behaved no differently than her male colleagues who shared her liberal ideology. However, the gender of the attorney did matter, and interestingly its effects can be parsed based along a fairly consistent partisan divide. With a few exceptions, conservative Justices tend to engage in less information seeking (or more verbal control) with female attorneys overall after controlling for ideology, and female attorneys representing a liberal position. Likewise, with a few exceptions, liberal Justices tend to engage in more information seeking (or less verbal control) with female attorneys overall after controlling for ideology, as well as female attorneys representing a conservative position. Another partisan picture materializes with regards to word counts, though it is more complicated than the one presented by information seeking scores. Both conservative and liberal Justices tend to speak more to female

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attorneys overall and female attorneys after controlling for ideology. However, when evaluating just female attorneys representing a position in opposition to a Justice’s ideology, the findings are reversed, with liberal Justices speaking more to female attorneys arguing a conservative position, and conservative Justices speaking less to female attorneys representing a liberal perspective. The second main finding is that looking at the individual Justices reveals varying patterns and nuances such that a one-size-fits-all model of judicial behavior is likely inaccurate. The factors that influenced one Justice’s oral argument behavior were different enough from other Justices, even those of his or her own ideological bent, that scholars of the Court should be wary of neglecting individual differences when attempting to study and predict judicial behavior. This study is not without limitations. While 57 cases and over 13,000 sentences were analyzed, a larger sample size would guard against possible biasing effects prone to sample research. While random sampling was used in selecting two-thirds of the cases, and the data from the remaining third was not statistically different from the randomly sampled cases, there is always the potential that the cases selected somehow deviated from the norm such that the findings of this study cannot be fully generalized to the Court overall. Additionally, a larger number of observations would obtain more statistical power, allowing for more precision in calculating effects and avoiding the possibility of not finding an effect where one really exists, or vice versa. Future research might even attempt analyzing every case starting with the 2004 term when changes in the transcripts allow for the analysis of individual Justices. Also, by expanding the number of cases examined, Justices O’Connor and Sotomayor could also be investigated to determine if Justice Ginsburg is an anomaly and the gender of Justices matters as well. Finally, future research might attempt to link the influence of gender via oral argument behavior to voting on the merits. Gender is little more than an item of interest if it influences judicial behavior during oral argument, but does not ultimately affect the Justices’ voting patterns. While others have found a nexus between gender and voting, it is not clear what the mediating factors are. This study begins to fill in that gap, but the full link needs to be explored further. Notwithstanding the above criticisms, this study is still the first to explore the potential influence of gender on judicial behavior during oral argument. As such it adds to current knowledge of judicial behavior and gender and society, and points the way for future exploration of these topics. It also provides practical insights for female attorneys who actually argue before the Supreme Court as to what they might realistically expect from the

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Justices they will face. Gender does matter during Supreme Court oral argument—just not for every Justice and in the same way.

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APPENDIX I: STATISTICAL TABLES Table 4: OLS Regression Models for Chief Justice Roberts Logged Att. Experience SCOTUS Clerk Experience Petitioner Amicus Party Sol. Gen. Office Att. Split Side Justice-Side Ideology Capable Party Scale Gender Gender*J-S Ideology F-test of Split Side, Amicus Constant

ISS Model 1 .084 (.074) .268 (.228) .431* (.203) .094 (.336) .417 (.385) .211 (.189) .155 (.212) -.149+ (.076) -.609* (.240) ---

ISS Model 2 .093 (.077) .262 (.228) .444* (.205) .099 (.337) .401 (.392) .177 (.186) .224 (.219) -.148+ (.077) -.458+ (.263) -.329 (.521) --

WC Model 1 -15.72 (17.00) -24.42 (36.20) 57.21 (39.04) -83.86 (52.26) -.64 (79.34) -67.23 (41.33) -154.16** (52.49) .46 (20.72) 16.80 (52.12) -4.37*

WC Model 2 -16.21 (17.34) -24.08 (36.55) 56.49 (39.57) -84.16 (52.69) .28 (80.73) -65.27+ (38.65) -158.12** (49.69) .39 (20.85) 8.18 (64.93) 18.88 (94.59) 4.58*

2.016*** 1.977*** 369.49*** 371.72*** (.208) (.218) (53.80) (58.40) Observations 101 101 101 101 F-statistic 2.18* 2.05* 6.02*** 5.36*** Adj. R2 .091 .085 .231 .222 Root MSE .987 .990 187.86 188.86 +p < .10; * p < .05; ** p < .01; *** p < .001; robust standard errors in parentheses below coefficients

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Table 5: OLS Regression Models for Justice Stevens ISS Model 2 WC Model 1 WC Model 2 .287* -1.62 1.17 (.123) (9.55) (9.01) -.103 25.76 24.40 (.297) (31.46) (31.36) .078 -61.48* -56.45* (.275) (27.02) (26.21) Amicus Party .218 -111.80** -110.46** (.485) (40.88) (40.67) Sol. Gen. Office -.913+ -17.22 -20.52 Att. (.508) (43.84) (42.91) Split Side -.035 -3.31 -15.66 (.316) (31.59) (31.06) Justice-Side -.927** -77.25* -103.12** Ideology (.333) (30.20) (33.42) Capable Party .009 9.65 9.56 Scale (.123) (10.12) (9.97) Gender .569 -30.63 -92.66** (.555) (26.21) (34.60) Gender*J-S -.023 -114.14* Ideology (.730) (47.26) Constant 1.885*** 1.882*** 171.81*** 184.48*** (.521) (.522) (47.48) (47.72) Observations 97 97 97 97 F-statistic 3.33** 3.28** 2.45* 2.50* Adj. R2 .159 .149 .158 .179 Root MSE 1.269 1.276 123.6 122.06 +p < .10; * p < .05; ** p < .01; *** p < .001; robust standard errors in parentheses below coefficients Logged Att. Experience SCOTUS Clerk Experience Petitioner

ISS Model 1 .288* (.123) -.104 (.296) .079 (.272) .219 (.482) -.913+ (.506) -.038 (.300) -.932** (.321) .009 (.122) .557 (.360) --

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Table 6: OLS Regression Models for Justice Scalia ISS Model 2 WC Model 1 WC Model 2 -.028 -40.64* -36.60* (.080) (17.89) (19.97) -.235 27.39 24.64 (.234) (50.27) (49.25) .075 -44.00 -38.11 (.175) (39.49) (39.24) Amicus Party -.390 -129.90* -127.40* (.371) (60.84) (60.60) Sol. Gen. Office -.115 95.93 88.35 Att. (.423) (85.63) (84.93) Split Side -.169 -169.45*** -185.65*** (.221) (46.30) (48.94) Justice-Side -.057 -49.79 -17.13 Ideology (.254) (57.46) (63.25) Capable Party .036 -9.02 -8.47 Scale (.080) (18.47) (18.27) Gender .148 12.29 83.44 (.223) (45.46) (66.17) Gender*J-S -.312 --155.72+ Ideology (.391) (88.09) Constant 1.897*** 1.860*** 499.38*** 480.96*** (.204) (.215) (53.81) (57.34) Observations 101 101 101 101 F-statistic .94 .87 6.17*** 6.58*** Adj. R2 .000 .000 .273 .282 Root MSE .884 .886 203.21 201.86 +p < .10; * p < .05; ** p < .01; *** p < .001; robust standard errors in parentheses below coefficients Logged Att. Experience SCOTUS Clerk Experience Petitioner

ISS Model 1 -.036 (.077) -.229 (.234) .063 (.173) -.395 (.370) -.100 (.419) -.137 (.207) -.122 (.219) .035 (.079) .005 (.174) --

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Table 7: OLS Regression Models for Justice Kennedy Logged Att. Experience SCOTUS Clerk Experience Petitioner Amicus Party Sol. Gen. Office Att. Split Side Justice-Side Ideology Capable Party Scale Gender Gender*J-S Ideology F-test of Capable, Amicus Constant

ISS Model 1 -.022 (.105) .290 (.238) .469* (.235) -.208 (.411) .268 (.629) -.184 (.270) -.058 (.283) -.094 (.126) -.259 (.222) ---

ISS Model 2 -.035 (.109) .299 (.240) .451+ (.236) -.216 (.410) .293 (.637) -.134 (.279) .045 (.316) -.096 (.127) .005 (.280) -.487 (.409) --

WC Model 1 4.26 (11.20) 43.62 (26.64) 27.15 (26.79) -45.91 (33.92) -22.96 (55.62) -47.32+ (27.95) -.88 (34.64) -6.63 (11.59) 57.88+ (29.77) ---

WC Model 2 3.51 (11.07) 44.09 (27.03) 26.12 (26.57) -46.33 (33.56) -21.54 (55.26) -44.44 (29.74) 5.00 (39.10) -6.74 (11.56) 73.04+ (41.34) -27.98 (59.21) 3.26*

2.125*** 2.082*** 161.89** 159.41** (.439) (.442) (54.42) (55.81) Observations 98 98 98 98 F-statistic .95 .89 3.95*** 3.64*** Adj. R2 .000 .000 .125 .117 Root MSE 1.140 1.143 119.55 120.09 +p < .10; * p < .05; ** p < .01; *** p < .001; robust standard errors in parentheses below coefficients

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Table 8: OLS Regression Models for Justice Souter Logged Att. Experience SCOTUS Clerk Experience Petitioner Amicus Party Sol. Gen. Office Att. Split Side Justice-Side Ideology Capable Party Scale Gender Gender*J-S Ideology Constant

ISS Model 1 .001 (.104) -.249 (.244) -.203 (.250) .343 (.455) .282 (.484) -.221 (.263) -.639+ (.353) -.232+ (.117) .282 (.310) -2.886*** (.541) --

ISS Model 2 -.026 (.099) -.231 (.245) -.241 (.255) .327 (.446) .332 (.472) -.115 (.263) -.424 (.359) -.235 (.115) .839+ (.454) -1.025+ (.565) 2.792*** (.512) --

WC Model 1 -30.58 (19.11) 66.31 (52.38) 33.71 (45.58) -190.15** (68.05) -90.17 (100.85) -52.06 (53.32) -35.20 (55.93) 31.33 (22.87) 38.74 (64.68) -237.64* (92.50) 2.37+

WC Model 2 -28.04 (19.04) 64.58 (52.95) 37.41 (46.61) -188.58** (68.04) -94.94 (100.92) -62.25 (54.78) -55.74 (59.51) 31.68 (22.81) -14.43 (91.76) 97.91 (133.61) 246.59** (93.42) --

F-test Capable, Exp. F-test Exp., S. 2.91+ 2.65+ G. Attorney Observations 101 101 101 101 F-statistic .94 1.08 3.66*** 3.51*** Adj. R2 .019 .039 .126 .123 Root MSE 1.175 1.163 222.07 222.41 +p < .10; * p < .05; ** p < .01; *** p < .001; robust standard errors in parentheses below coefficients

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Table 9: OLS Regression Models for Justice Ginsburg ISS Model 2 WC Model 1 WC Model 2 -.061 -2.59 -5.71 (.067) (9.74) (9.92) -.074 19.40 21.57 (.246) (29.61) (29.56) .107 33.80 29.75 (.233) (25.24) (24.30) Amicus Party -1.564*** -59.79+ -63.71+ (.394) (33.55) (34.70) Sol. Gen. Office 1.035* -30.85 -23.98 Att. (.430) (55.51) (55.73) Split Side .268 -105.99*** -91.83*** (.300) (26.20) (25.78) Justice-Side -.233 66.15* 42.34 Ideology (.306) (29.80) (33.06) Capable Party -.065 .71 .23 Scale (.101) (13.51) (13.12) Gender .224 -21.24 -73.62* (.590) (36.81) (33.22) Gender*J-S .279 -115.89 Ideology (.633) (73.13) Constant 2.248*** 2.280*** 183.57*** 196.46*** (.309) (.303) (33.89) (32.88) Observations 101 101 101 101 F-statistic 3.67*** 4.05*** 5.31*** 4.81*** Adj. R2 .152 .144 .238 .257 Root MSE 1.101 1.06 122.66 121.1 +p < .10; * p < .05; ** p < .01; *** p < .001; robust standard errors in parentheses below coefficients Logged Att. Experience SCOTUS Clerk Experience Petitioner

ISS Model 1 -.054 (.068) -.079 (.241) .117 (.228) -1.555*** (.427) 1.019* (.427) .234 (.287) -.176 (.273) -.064 (.102) .350 (.324) --

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Table 10: OLS Regression Models for Justice Breyer ISS Model 2 WC Model 1 WC Model 2 .063 28.72 26.91 (.090) (18.84) (19.34) .440* 9.95 12.37 (.192) (46.03) (45.71) -.244 -244.88*** -245.86*** (.194) (43.67) (43.63) Amicus Party -.290 -70.84 -71.92 (.338) (63.05) (62.43) Sol. Gen. Office -.241 -89.05 -86.55 Att. (.464) (88.98) (87.99) Split Side -.506* -211.52*** -203.60*** (.205) (46.13) (46.73) Justice-Side .107 33.69 15.39 Ideology (.255) (61.85) (67.53) Capable Party -.021 6.23 6.55 Scale (.088) (21.07) (21.15) Gender .053 -31.69 -68.38 (.322) (53.55) (68.74) Gender*J-S .440 -80.01 Ideology (.563) (111.27) Constant 1.698*** 1.738*** 484.40*** 491.76*** (.282) (.286) (62.38) (63.32) Observations 95 95 95 95 F-statistic 2.73** 2.37** 8.47*** 7.76*** Adj. R2 .106 .103 .391 .388 Root MSE .949 .950 205.22 205.8 +p < .10; * p < .05; ** p < .01; *** p < .001; robust standard errors in parentheses below coefficients Logged Att. Experience SCOTUS Clerk Experience Petitioner

ISS Model 1 .073 (.087) .427* (.188) -.239 (.194) -.284 (.345) -.255 (.476) -.550** (.204) .207 (.272) -.023 (.091) .254 (.276) --

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Table 11: OLS Regression Models for Justice Alito ISS Model 2 WC Model 1 WC Model 2 -.249+ -1.36 -1.80 (.140) (6.83) (6.93) -.291 -30.86+ -30.58+ (.394) (17.18) (17.26) .594+ 1.03 .57 (.340) (18.44) (18.69) Amicus Party -1.141+ 6.63 6.43 (.601) (25.91) (26.03) Sol. Gen. Office .329 -11.81 -10.47 Att. (.881) (35.75) (35.09) Split Side -.352 -47.66* -46.14* (.446) (19.21) (19.72) Justice-Side 1.057* 48.59+ 51.55+ Ideology (.522) (24.92) (27.42) Capable Party .158 2.76 2.53 Scale (.190) (8.78) (8.72) Gender -.010 7.04 16.14 (.666) (21.74) (25.35) Gender*J-S -.417 --15.95 Ideology (.830) (40.70) Constant 1.436+ 1.414+ 76.78* 75.93* (.748) (.759) (30.71) (31.11) Observations 94 94 94 94 F-statistic 4.29*** 3.86*** 2.14* 1.88+ Adj. R2 .130 .121 .108 .099 Root MSE 1.686 1.694 86.51 86.97 +p < .10; * p < .05; ** p < .01; *** p < .001; robust standard errors in parentheses below coefficients Logged Att. Experience SCOTUS Clerk Experience Petitioner

ISS Model 1 -.238+ (.142) -.299 (.392) .606+ (.335) -1.135+ (.598) .294 (.878) -.392 (.435) .980* (.477) .164 (.188) -.248 (.417) --

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Appendix II: Case Transcripts Analyzed in Study Term

Case

Number

Oral Argument Date

2008 2008

Forest Grove Sch. Dist. v. T.A. United States ex rel. Eisenstein v. City of New York Nken v. Mukasey Coeur Alaska, Inc. v. Se. Alaska Conservation Council Cone v. Bell Pac. Bell Tel. Co. v. Linkline Comm’ns, Inc. Haywood v. Drown Pleasant Grove City v. Summum Jimenez v. Quarterman Meacham v. Knolls Atomic Power Lab. Metr. Life Ins. Co. v. Glenn Davis v. Fed. Election Comm’n. Irizarry v. United States Greenlaw v. United States United States v. Clintwood Elkhorn Mining Co. Chamber of Commerce of United States v. Brown Rothgery v. Gillespie County Crawford v. Marion County Election Bd. Kentucky Ret. Sys. v. EEOC Rowe v. New Hampshire Motor Transp. Ass’n. Danforth v. Minnesota United States v. Williams New York State Bd. of Elections v. Torres Gall v. United States Washington State Grange v. Washington State Republican Party Fed. Election Comm’n. v. Wisconsin Right to Life, Inc. Office of Sen. Mark Dayton v. Hanson Hinck v. United States Brendlin v. California Tennessee Secondary Sch Athletic Ass’n v. Brentwood Acad. Leegin Creative Leather Prods., Inc. v. PSKS, Inc. Wilkie v. Robbins Morse v. Frederick Smith v. Texas Davenport v. Washington Educ. Ass’n. Rockwell Int’l Corp. v. United States Burton v. Stewart

08-305 08-660

April 28, 2009 April 21, 2009

08-681 07-984

January 21, 2009 January 12, 2009

07-1114 07-512

December 9, 2008 December 8, 2008

07-10374 07-665 07-6984 06-1505 06-923 07-320 06-7517 07-330 07-308

December 3, 2008 November 12, 2008 November 4, 2008 April 23, 2008 April 23, 2008 April 22, 2008 April 15, 2008 April 15, 2008 March 24, 2008

06-939

March 19, 2008

07-440 07-21 06-1037 06-457

March 17, 2008 January 9, 2008 January 9, 2008 November 28, 2007

06-8273 06-694 06-766 06-7949 06-713

October 31, 2007 October 30, 2007 October 3, 2007 October 2, 2007 October 1, 2007

06-969

April 25, 2007

06-618 06-376 06-8120 06-427

April 24, 2007 April 23, 2007 April 23, 2007 April 18, 2007

06-480

March 26, 2007

06-219 06-278 05-11304 05-1589 05-1272 05-9222

March 19, 2007 March 19, 2007 January 17, 2007 January 10, 2007 December 5, 2006 November 7, 2006

2008 2008 2008 2008 2008 2008 2008 2007 2007 2007 2007 2007 2007 2007 2007 2007 2007 2007 2007 2007 2007 2007 2007 2006 2006 2006 2006 2006 2006 2006 2006 2006 2006 2006 2006

2010] 2006 2005 2005 2005 2005 2005 2005 2005 2005 2005 2005 2005 2005 2005 2005 2004 2004 2004 2004 2004

GENDER INFLUENCE ON THE SUPREME COURT Carey v. Musladin Kansas v. Marsh (Reargued) Empire HealthChoice Assurance, Inc. v. McVeigh Dixon v. United States Brigham City v. Stuart Beard v. Banks Garcetti v. Ceballos (Reargued) Howard Delivery Serv., Inc. v. Zurich Am. Ins. League of United Latin Am. Citizens v. Perry Randall v. Sorrell Holmes v. South Carolina Rapanos v. United States Wisconsin Right to Life, Inc. v. Fed. Election Comm’n. Rumsfeld v. Forum for Academic and Inst. Rights, Inc. Scheidler v. Nat’l Org. for Women, Inc. Tory v. Cochran Metro-Goldwyn-Mayer Studios Inc. v. Grokster, Ltd. Clingman v. Beaver Veneman v. Livestock Mktg. Ass’n. Jackson v. Birmingham Bd of Educ.

655

05-785 04-1170 05-200

October 11, 2006 April 25, 2006 April 25, 2006

05-7053 05-502 04-1739 04-473 05-128

April 25, 2006 April 24, 2006 March 27, 2006 March 21, 2006 March 21, 2006

05-204

March 1, 2006

04-1528 04-1327 04-1034 04-1581

February 28, 2006 February 22, 2006 February 21, 2006 January 17, 2006

04-1152

December 6, 2005

04-1244 03-1488 04-480

November 30, 2005 March 22, 2005 March 29, 2005

04-37 03-1164 02-1672

January 19, 2005 December 8, 2004 November 30, 2004