Emory Law Journal

Sonia Sotomayor and the Construction of Merit
Guy-Uriel Charles,
Daniel L. Chen,
Mitu Gulati Professor of Law and Co-Director of the Center for the Study of Law, Race, and Politics, Duke University School of Law.Daniel L. Chen is Assistant Professor of Law, Duke University School of Law.Mitu Gulati is Professor of Law and Co-Director of the Center for the Study of Law, Race, and Politics, Duke University School of Law.

Abstract

The appointment of Sonia Sotomayor to the Supreme Court in 2009 was criticized as sacrificing merit on the altar of identity politics. According to critics, Sotomayor was simply “not that smart.” For some conservative critics, her selection illustrated the costs of affirmative action policies, in that this particular choice was going to produce a lower quality Supreme Court. For liberal critics, many were concerned that the President, by selecting Sotomayor, was squandering an opportunity to appoint an intellectual counterweight to conservative Justices like Antonin Scalia, Samuel Alito, and John Roberts. Using a set of basic measures of judicial merit, such as publication and citation rates for the years 2004 to 2006, when Sotomayor was on the Court of Appeals for the Second Circuit, we compare her performance to that of her colleagues on the federal appeals courts. Sotomayor matches up well. She might turn out to be more of a force on the Court than the naysayers predicted.

I. “Not Nearly as Smart as She Seems to Think She Is”

When President Barack Obama was considering whether to nominate to the Supreme Court Sonia Sotomayor, then a judge on the United States Court of Appeals for the Second Circuit, a prominent law professor, Laurence Tribe, wrote a letter to the President opposing Sotomayor’s potential nomination on the ground that “she’s not nearly as smart as she seems to think she is.” 1Letter from Laurence H. Tribe, Carl M. Loeb University Professor, Harvard Law Sch., to Barack Obama, U.S. President (May 4, 2009), available at http://www.eppc.org/docLib/20101028_tribeletter.pdf. For a discussion of the Tribe letter, see Ed Whelan, Tribe to Obama: Sotomayor Is “Not Nearly as Smart as She Seems to Think She Is,Nat’l Rev. Online (Oct. 28, 2010, 9:42 AM), http://www.nationalreview.com/bench-memos/251301/tribe-obama-sotomayor-not-nearly-smart-she-seems-think-she-ed-whelan. While Tribe’s assessment was intended as a private communication, others were saying something similar in public. 2 See Countdown with Keith Olberman (MSNBC television broadcast May 26, 2009), available at http://www.msnbc.msn.com/id/3036677/vp/30950928#30950928 (interviewing Jonathan Turley, Professor, George Washington University); P.J. Gladnick, Liberal Jonathan Turley: Sotomayor Lacks Intellectual Depth, NewsBusters (May 27, 2009), http://newsbusters.org/blogs/p-j-gladnick/2009/05/27/liberal-jonathan-turley-sotomayor-lacks-intellectual-depth (quoting Turley as characterizing Sotomayor as lacking “intellectual depth” but describing Diane Wood as “blazingly brilliant”). Jeffrey Rosen, another legal academic, wrote an article in the New Republic questioning Sotomayor’s merit. 3Jeffrey Rosen, The Case Against Sotomayor: Indictments of Obama’s Front-Runner to Replace Souter, New Republic (May 4, 2009, 12:00 AM), http://www.tnr.com/article/politics/the-case-against-sotomayor. Based on anonymous sources, Rosen reported that there was widespread skepticism among the judges and academics familiar with Sotomayor’s work regarding her capabilities for the job. 4 Id. The consistent theme was a concern that Sotomayor was simply “not that smart.” 5 Id. (quoting a former Second Circuit clerk) (internal quotation mark omitted). Even those on the Democratic side of the aisle, Rosen noted, appeared to have misgivings about Sotomayor’s intellectual capabilities. 6 Id.

It was not long before the conventional narrative became that Sotomayor was a mediocre legal mind. 7 See, e.g., Richard Cohen, Op-Ed., The So-So Sotomayor, Wash. Post, July 21, 2009, at A17. Commentators accused President Obama of having sacrificed merit for identity politics (“biography over brain,” in the words of Washington Post commentator, Dana Milbank). 8 See Dana Milbank, Op-Ed., Washington Sketch: But Will She Suit Up with the Washington Nine?, Wash. Post, May 27, 2009, at A2; see also Ilya Shapiro, Commentary: Sotomayor Pick Not Based on Merit, CNN (May 27, 2009), http://articles.cnn.com/2009-05-27/politics/shapiro.scotus.identity_1_judge-sotomayor-hispanic-supreme-court-sonia-sotomayor?_s=PM:POLITICS. For many, she was not in the pool of the best qualified candidates, even if it was the case that Obama wanted to pick a female Justice. 9 See Milbank, supra note 8. There were others, such as Diane Wood, a former law professor at the University of Chicago and judge on the Seventh Circuit, and Elena Kagan, the former dean of the Harvard Law School and, at the time, Solicitor General of the United States, whom they thought were smarter and more deserving. 10 Sharon Johnson, Wood, Kagan Are on High Court Short List, Again, Women’s eNews (Apr. 25, 2010), http://womensenews.org/story/in-the-courts/100423/wood-kagan-are-high-court-short-list-again; see also Milbank, supra note 8; Shapiro, supra note 8. While supporters of Wood and Kagan often depicted them as brainy or brilliant, some of Sotomayor’s supporters described her as workmanlike and competent. 11 See Kristina Moore, Over 1000 Law Professors Join Letter Endorsing Sotomayor, SCOTUSblog (July 8, 2009, 1:18 PM), http://www.scotusblog.com/2009/07/over-1000-law-professors-join-letter-endorsing-sotomayor/; see also Cohen, supra note 7; Milbank, supra note 8.

To us, a striking aspect of Sotomayor’s nomination was that this public and negative assessment of her merit was made without much factual support. One might even argue that the initial presumption should have been in her favor. After all, she graduated with honors from Princeton University, graduated from Yale Law School, and spent more than a decade on the court of appeals, following stints as a trial judge and a federal prosecutor. 12Press Release, White House, Background on Judge Sonia Sotomayor (May 26, 2009), http://www.whitehouse.gov/the_press_office/Background-on-Judge-Sonia-Sotomayor/. It is hard to look at her credentials and conclude reflexively that she was unqualified for the Supreme Court—that is, unless one applied a high discount to her achievements on the theory that her success was largely attributable to affirmative action. 13 See Joe Conason, Sonia Sotomayor Is Not Clarence Thomas, Salon (May 29, 2009, 6:24 AM), http://www.salon.com/2009/05/29/clarence_thomas_2/. A theme running through much of the public discussion of her candidacy was that this appointment, more than most, represented the triumph of identity politics over merit. 14 See Shapiro, supra note 8. One could not escape the fact that she was going be the first Latina on the Supreme Court or that President Obama had considered and nominated her in part because she was Latina. 15 See id.

Our goal in this Essay is to provide some data against which to test the claims of Sotomayor’s mediocrity. Prior to being nominated to the Court, she had been a judge on the Court of Appeals for the Second Circuit for roughly a decade. 16Press Release, White House, supra note 12. The pool of judges on the courts of appeals is the primary one from which Supreme Court Justices are chosen these days. 17Lee Epstein et al., The Norm of Prior Judicial Experience and Its Consequences for Career Diversity on the U.S. Supreme Court, 91 Calif. L. Rev. 903, 908–17 (2003). That means that we should be able to compare Sotomayor’s performance to that of her peers to get a rough sense of just how she matches up.

We use two categories of measures to evaluate Sotomayor’s performance relative to that of all the other active judges on the courts of appeals over the period from 2004 to 2006. The categories are publications and citations. As we explain in the next section, the thirteen different measures we use within those categories should give us a rough sense of the skill and effort that Judge Sotomayor brought to her job, in comparison to her peers.

In constructing these comparisons to test claims that were made about Sotomayor during her nomination, we are not writing on a blank slate. Other scholars have subjected the repeated claims that were made about Sotomayor being a “judicial activist” to empirical testing. 18 See Monica Youn, Brennan Ctr. for Justice, Judge Sotomayor’s Record in Constitutional Cases, at v–vi (2009); Corey Rayburn Yung, Flexing Judicial Muscle: An Empirical Study of Judicial Activism in the Federal Courts, 105 Nw. U. L. Rev. 1, 42–43 (2011); Marcia Coyle, No Activist Judge, Says New Book, Nat’l L.J. (June 8, 2009), http://www.law.com/jsp/nlj/legaltimes/PubArticleFriendlyLT.jsp?id=1202431249312&slreturn=1. The claims were found wanting. 19 See Youn, supra note 18, at v–vi; Yung, supra note 18, at 42–43; Coyle, supra note 18. And our analysis builds on a preliminary examination reported by Professor Eric Posner in two blog posts in 2009. 20 See Eric Posner, Judge Sonia Sotomayor: What the Data Show, Volokh Conspiracy (May 13, 2009, 11:40 AM), http://volokh.com/posts/1242229209.shtml [hereinafter Posner, Judge Sonia Sotomayor]; Eric Posner, Judge Sotomayor: More Data, and a New Conclusion, Volokh Conspiracy (May 27, 2009, 11:50 PM), http://volokh.com/archives/archive_2009_05_24-2009_05_30.shtml#1243482653 [hereinafter Posner, Judge Sotomayor]. He compared Sotomayor’s performance on the appeals court to that of the ten other judges whose names had been mentioned as potential candidates for the Court and found that she did well. 21 See Posner, Judge Sonia Sotomayor, supra note 20; Posner, Judge Sotomayor, supra note 20. Posner’s analysis was done on the basis of data that were collected jointly with Stephen Choi and one of us, G. Mitu Gulati. See Posner, Judge Sonia Sotomayor, supra note 20; Posner, Judge Sotomayor, supra note 20. For a report on that analysis, see Assessing Sotomayor’s Influence, N.Y. Times, http://www.nytimes.com/interactive/2009/05/28/us/politics/0529-judge-graphic.html (last visited July 5, 2012). We expand on that analysis in three ways: (1) by comparing Sotomayor’s numbers to the full set of 136 judges who were active during the years from 2004 to 2006, (2) by using additional measures, and (3) by controlling for structural differences across the federal circuits.

The question of how best to construct objective measures of judicial performance has been the topic of considerable debate in recent years. 22For interested readers, these measures have been debated in a number of symposia. See, e.g., Symposium, Empirical Measures of Judicial Performance, 32 Fla. St. U. L. Rev. 1001 (2005); Symposium, Measuring Judges and Justices, 58 Duke L.J. 1173 (2009); Symposium, The Impact of Direct Democracy, 78 S. Cal. L. Rev. 835 (2005). The measures we use, citations and publications, are among the more familiar ones in the literature. 23 See Scott Baker, Should We Pay Federal Judges More?, 88 B.U. L. Rev. 63, 77–85 (2008); Stephen J. Choi & G. Mitu Gulati, Choosing the Next Supreme Court Justice: An Empirical Ranking of Judge Performance, 78 S. Cal. L. Rev. 23, 32–34 (2004); Jake Dear & Edward W. Jessen, “Followed Rates” and Leading State Cases, 1940–2005, 41 U.C. Davis L. Rev. 683, 685–89 (2007); William M. Landes et al., Judicial Influence: A Citation Analysis of Federal Courts of Appeals Judges, 27 J. Legal Stud. 271, 271–76 (1998); Russell Smyth & Mita Bhattacharya, What Determines Judicial Prestige? An Empirical Analysis for Judges of the Federal Court of Australia, 5 Am. L. & Econ. Rev. 233, 233–34 (2003). We should note, though, that these measures have come in for their share of criticism and been subjected to testing. 24 See, e.g., Marin K. Levy et al., The Costs of Judging Judges by the Numbers, 28 Yale L. & Pol’y Rev. 313, 314–15 (2010); William P. Marshall, Be Careful What You Wish for: The Problems with Using Empirical Rankings to Select Supreme Court Justices, 78 S. Cal. L. Rev. 119 (2004). For tests of the measures, see Stephen J. Choi & G. Mitu Gulati, Bias in Judicial Citations: A Window into the Behavior of Judges?, 37 J. Legal Stud. 87 (2008); and Stephen J. Choi, G. Mitu Gulati & Eric A. Posner, How Well Do Measures of Ability Predict Judicial Performance?: A Case Study Using Securities Class Actions (Univ. of Chi. Law Sch., Olin Research Paper No. 519, 2011), available at http://papers.ssrn.com/sol3/papers.cfm?abstract_id=1596910. In addition, commentators have proposed and utilized other measures as well. 25 See Frank B. Cross & Stefanie Lindquist, Judging the Judges, 58 Duke L.J. 1383 (2009); Dear & Jessen, supra note 23; Daniel A. Farber, Supreme Court Selection and Measures of Past Judicial Performance, 32 Fla. St. U. L. Rev. 1175 (2005); Smyth & Bhattacharya, supra note 23. We will not rehash the debate here.

If Sotomayor’s performance, while on the appeals court, had been mediocre, we would expect to find that, in comparison to her peers, she would have published few opinions and that those opinions would have had little impact because they would not have often been cited by other judges and commentators. If, on the other hand, she had performed with distinction, we would expect to find that she does better than most of her colleagues in terms of output and citations. The results suggest that Sotomayor compares well with her peers. She is above the mean on all of our measures, in the top quarter of all judges in the comparison pool on eleven of the thirteen measures, and in the top 10% on seven of those thirteen measures.

II. A Hierarchy of Measures

Before proceeding, it may help to clarify what we are, and are not, claiming to show. We are not challenging the merits of the reviews of Sotomayor by Tribe, Rosen, or any of the others who either reviewed her opinions or collected anonymous reports. We are offering a different measure by which Sotomayor’s merit might have been judged, one that we concede has value primarily in terms of raising questions about the more sophisticated evaluations done by others, such as Tribe and Rosen.

Our starting premise is that there are multiple methods by which to measure an appellate judge’s merit, vis-à-vis a possible elevation to the High Court. The possible methods of evaluation all contain tradeoffs. Tribe’s evaluation, Rosen’s evaluation, and our evaluation all fall into different boxes in terms of using different methods to answer the same question.

The analogy to movie reviews may help. Someone interested in knowing whether to go to a particular movie has a variety of sources of information on that movie. One option is to look to the evaluations by Anthony Lane, 26 Contributors: Anthony Lane, New Yorker, http://www.newyorker.com/magazine/bios/anthony_lane/search?contributorName=anthony%20lane (last visited July 5, 2012). Manhola Dargis, 27 Manohla Dargis, N.Y. Times, http://movies.nytimes.com/movies/critics/Manohla-Dargis (last visited July 5, 2012). or one of the other critics for the New Yorker or the New York Times. Here, the reviewers themselves are typically famous and conduct nuanced and erudite reviews. Readers looking at these reviews know ahead of time that what they are getting is likely to be idiosyncratic—indeed, that is part of the value. Laurence Tribe’s review of Sotomayor might be thought of as falling into this category. It is a review done by a superstar academic who likely brings his idiosyncratic preferences to the table. At least a portion of those reading his review (and certainly, his former student, Barack Obama) are going to be able to read it in the context of who he is, what his preferences and motives are, and so on.

For a different category of views, our potential moviegoer might look online at Rotten Tomatoes 28 Rotten Tomatoes, http://www.rottentomatoes.com/ (last visited July 5, 2012). or Fandango 29 Fandango, http://www.fandango.com/ (last visited July 5, 2012). for aggregations of what are likely pseudonymous and perhaps less expert movie reviews. Here, one often will not have any idea who the reviewers are, what their motivations are, and so on (they could be jealous competitors, fawning acolytes, or seven-year-olds from Kazakhstan). The fact of the reviewers’ anonymity has upsides and downsides. On the one hand, it allows for more honesty (no fear of repercussion from the author or her friends), and on the other hand, it allows for more dishonesty (no fear of reputational loss if it turns out that there is widespread disagreement with the content of the review). Rosen’s review, relying on anonymous sources, might be thought of as falling into this category. It provides a different type of information than the superstar review, but one that is just as legitimate and perhaps more relevant to some audiences.

Third, and perhaps less sophisticated, is market information. The potential moviegoer may want to know whether the movie is popular—whether this is a movie that appeals to the broader public. If one is interested, one could even break down the market statistics in terms of which specific markets the movie has done well in. The fact that a movie has done well in Madison, Wisconsin, but terribly in Cochin, India, conveys more information (if one knows anything about the audience preferences in those two locations) than simply knowing that the movie did well in Madison.

Our data on Sotomayor is like the market information about her performance. It is less nuanced than the above-mentioned sources, but it has a greater level of objectivity and can be more easily verified. To the extent our findings point in the same direction as those of Tribe and Rosen, that should add to the level of confidence that one has in any of the evaluations. However, if the three sources do not line up as pointing in the same direction, that should raise questions. Whatever we find though, we cannot claim to be proving the others wrong. We are simply adding more information to the mix.

III. The Data

To examine Sotomayor’s performance relative to her colleagues on the federal appeals courts, we collected data from roughly the middle of her tenure on the Second Circuit. Her full first year on the Second Circuit was in 1999, and her last full year on the Second Circuit, prior to nomination, was in 2008. 30 See Press Release, White House, supra note 12. We examine her performance during three years falling roughly within the middle of that period, from 2004 until 2006. Our reasons for selecting these years were simple. We did not wish to look too early in her tenure, when she might have been learning the job and building a reputation. During this period, her numbers might have been biased downwards as a result of her inexperience and lack of a reputation. We also did not want to look too late in her tenure, when her name had begun surfacing as a possible candidate for elevation to the Supreme Court by President Obama. During this latter period, her citation numbers may have been biased upwards by an anticipatory Supreme Court halo effect. That is, others citing her to invoke the extra authority that comes from citing a possible Supreme Court Justice.

For the period from 2004 until 2006, we collected information at the individual case level on every case that was published for twelve circuit courts of general jurisdiction. We skipped the Federal Circuit because of its specialized caseload. We should note at the outset, though, that there is variation among the circuits in terms of caseloads and case types. For example, the D.C. Circuit’s diet of cases is much higher in administrative law than the Fifth Circuit. 31M. Wood, D.C. Circuit Has Special History Among Appeals Courts, Roberts Says, Va. L. (Apr. 26, 2005), http://www.law.virginia.edu/html/news/2005_spr/roberts.htm. Similarly, the Ninth Circuit likely sees many more immigration cases than the Eighth Circuit. 32 See Anna O. Law, The Immigration Battle in American Courts 28 (2010). Despite the variation in case types and caseloads across circuits, there is reason to think that judicial performances can be compared across the different federal courts. This is because our primary comparison metric derives from the choice made by individual judges to publish opinions. Two facts are important here. First, federal appellate judges, regardless of circuit, face hundreds, if not thousands, of cases every year. Many are easy and do not raise important legal issues. But there is also an abundance of cases that potentially do raise important legal issues, and judges do not have enough time to deal with all of them with published opinions (there is now a large literature discussing this problem). Second, and relatedly, judges tend to publish only a small fraction of their cases. Some judges publish no more than a dozen opinions a year out of the hundreds that come before them. Therefore, if one assumes that every judge, regardless of circuit, gets more than enough cases that have issues that could be publication worthy, one can compare judges in terms of their published opinions.

To make adjustments for variations in case types, we also collected information for every case on the subject area that it fit under. The estimation of whether a case fell within a given subject area was necessarily a subjective one. The designation was made based on a combination of reading the Westlaw summary of the case and examining the Westlaw KeyCites that categorize every case as a function of the various subject areas that it covers. In total, we coded the cases as falling into twenty-one distinct subject areas, plus one general category for “other” cases. 33The list of subject areas is reported infra Appendix B.

We report on data for 136 circuit court judges for the twelve circuits mentioned above. 34There are 179 active positions on the federal courts of appeals. All of those positions, however, are not necessarily filled at any given time. How the Federal Courts Are Organized, Fed. Jud. Center, http://www.fjc.gov/federal/courts.nsf/autoframe?OpenForm&nav=menu3c&page=/federal/courts.nsf/page/A783011AF949B6BF85256B35004AD214?opendocument (last visited July 5, 2012). These were all the judges who were on active status for the three years for which we collected data. Judges who were active for only a subset of the period did not get counted. The “active” designation means that the judge was taking a full caseload and had full administrative responsibilities (the alternative is senior status, where the judge can reduce his caseload to as low as 25% of the full load). 35The assumption that senior judges do less work does not hold uniformly (in the course of this study, we found indications that a few senior judges were producing as much, if not more, than some of their active colleagues). Our reason for focusing on the active judges is that our numbers are most illustrative in a relative, rather than absolute, sense because what we are interested in is Sotomayor’s performance relative to that of her competitors for the top spot. We restrict the comparison to her active peers because that presumably constitutes a significant fraction of the pool of competitors for the slot on the Supreme Court. The comparison pool we have constructed is both under- and over-inclusive in terms of capturing the true pool of Sotomayor’s competitors vis-à-vis President Obama. On the minus side, Obama’s pool likely did not include most Republican-appointed judges and judges above a certain age. On the plus side, Obama’s pool surely included some who were not federal appeals court judges (senior government officials, academics, state judges, etc.). Our goal, though, is not to test whether Obama picked the best candidate but rather to examine the hypothesis that his desire to further diversity goals led him to pick a mediocre candidate. For purposes of that hypothesis, comparing Sotomayor’s performance to a pool of candidates within which the candidates range from mediocre to exceptional should suffice. Recent history suggests that most nominations to the Court tend to be from the federal appeals courts, making it a reasonable comparison pool. 36On the trend toward appointing federal appeals judges to the High Court, see Epstein et al., supra note 17, at 908–17.

Our analysis has little to say about an individual judge’s absolute merit. What we have are measures of relative performance. For example, saying that a judge publishes one hundred opinions a year does not tell us much about her effort levels unless one also sees that 25% of the appellate judges publish fewer than ten opinions a year.

Authorship: Here, we collected information on the identity of the writing judge and the identities of the two other judges on the panel. These variables allow us to determine both how many opinions Sotomayor authored and published herself and how many “for publication” opinions she was on the panel for. Prior research has tended to focus only on the primary author of the opinion. And that may be reasonable, given that the primary author is the one who generally puts in the major portion of the effort on any given opinion. However, the end product is supposed to be the joint product of three judges. Hence, the argument can be made that, when one observes that an opinion was published or garnered a lot of citations, it is a team rather than individual effort that one is observing. To take this team-production effect into account, we attempt to estimate what the impact of Sotomayor sitting on a panel is, even when she is not the primary author.

In terms of the specific characteristics of individual opinions, we also measured the number of pages for each published opinion. The number of pages provides a different measure of judicial effort than just a count of the number of published opinions. Certain judges designate a large fraction of their opinions as worthy of publication, and others are very judicious about such a designation. The number of pages could simply indicate a long-winded style of writing or may indicate how complex the issues were that the judge addressed. Thus, this measure provides us with an additional, though different, measure of judicial effort than the count of published opinions.

Citations: Citations to an opinion can come from a variety of different audiences or users. Potentially, there is valuable information to be mined from the fact that a certain judge is more or less popular with certain audiences. Different audiences are likely to value different characteristics of a judicial opinion. The fact that one audience likes an opinion a great deal and another audience does not might provide information about the likely characteristics of that opinion.

Take, for example, the complaint that judges and legal academics have grown increasingly further apart in recent years. 37 See Harry T. Edwards, The Growing Disjunction Between Legal Education and the Legal Profession, 91 Mich. L. Rev. 34, 34–57 (1992). In this story, academics are more interested in interdisciplinary work that explores radical ideas, whereas judges are more interested in careful doctrinal analyses. 38 See id. Assuming the foregoing, one would expect judges whose opinions are found more popular by academics to be making more radical arguments, whereas judges whose opinions are popular among other judges may be producing careful and nuanced doctrinal syntheses. Finding out that Judge Sotomayor’s opinions are popular with academics but unpopular with her fellow judges might suggest that her opinions are innovative but weak in terms of careful doctrinal parsing.

Along those lines, one might expect state judiciaries to be more interested in opinions that tackle basic issues in areas that are more the province of state laws—subjects such as torts, contracts, family law, and corporate law. A judge who finds herself more cited by the state courts may be writing high-quality opinions in the types of cases that fall under the purview of the local state courts. One might also distinguish local citations (from courts that are required to follow the decision as precedent) from outside circuit citations. A lot of local citations probably mean that the judge writes opinions that state the local law clearly. A lot of external citations may suggest something different—that the opinions are helpful to other judges in their analyses.

As described above, we look to four separate audiences to count citations. First, we examine citations by federal courts outside the circuit. Those are federal courts where the opinion would have no precedential value but is presumably cited because it helps the analysis. Second, we aggregate citations within the circuit, where the citations are often going to be used, because the opinion has precedential value. Third, we report citations from the state courts. These are likely to be citations unrelated to the precedential effects of the case because the state courts are not obligated to follow the federal courts in most matters, especially those relating to state law. Fourth, we display citations by legal academics in law journals and treatises.

For each of these citation measures, we used reports from the Shepard’s Citation Service. We counted citations for every published opinion issued during the period from 2004 until 2006. The citations were tallied from the date of publication until January 1, 2009. To avoid running into the halo effect that might have impacted Sotomayor’s circuit court opinions once her name became actively discussed in the debates about whom President Obama might nominate, we did not collect citations beyond that point. 39We are making an approximation here because Sotomayor’s name was being actively discussed as a possible candidate for the Court at least as early as October 2008. See Sarah Johnson, Granholm Placed on Short List for Supreme Court Nomination, Cent. Mich. Life (Oct. 17, 2008, 12:00 AM), http://www.cm-life.com/2008/10/17/granholmplacedonshortlistforsupremecourtnomination/ (discussing Sonia Sotomayor as a potential Supreme Court candidate); Justin Jouvenal, Ten Picks for Obama’s Supreme Court, Salon (Nov. 19, 2008, 12:50 AM), http://www.salon.com/news/feature/2008/11/18/supreme_court.

One frequently discussed measure that we do not use is the rate at which the Supreme Court reverses a judge. 40 See Dave Hoffman, Reversal Rates, Reconsidered, Concurring Opinions, (Sept. 30, 2011, 12:21 PM), http://www.concurringopinions.com/archives/2011/09/reversal-rates-reconsidered.html; Dave Hoffman, What Should a Judge’s Reversal Rate Be? Concurring Opinions, (May 26, 2009, 3:20 PM), http://www.concurringopinions.com/archives/2009/05/what-should-a-judges-reversal-rate-be.html. We do not use this measure for a couple of reasons. First, the numbers on this measure tend to be quite small for any given appeals court judge because the Supreme Court takes certiorari on only a few cases from each federal circuit every year. For the three-year window of cases for which we collected data, we would have been comparing a lot of zeroes and ones for the 136 judges in our pool. Second, this was the one quantitative measure regarding Sotomayor’s performance on the lower court that did receive attention during her nomination process. Some initially claimed that her reversal rate was unacceptably high. For example, the Washington Times ran a headline titled Supreme Court Overturned 60% of Sotomayor’s Rulings. 41 See Stephen Dinan, Supreme Court Overturned 60% of Sotomayor’s Rulings, Wash. Times, May 27, 2009, at A1. Wendy Long, counsel to the Judicial Confirmation Network, said that Sotomayor “has an extremely high rate of her decisions being reversed, indicating that she is far more of a liberal activist than even the current liberal activist Supreme Court.” 42Wash. Times, CQ Uncritically Report Criticism that Sotomayor’s Supreme Court Reversal Rate Is “High,Media Matters for Am. (May 27, 2009, 4:09 PM), http://mediamatters.org/research/200905270038 (quoting Wendy Long in an excerpt from an article in Congressional Quarterly Today) (internal quotation marks omitted). Others countered that Sotomayor’s rate of reversal (reversed on three out of the five cases that were appealed) was quite acceptable when compared to the overall reversal rate of the High Court during the period in question (roughly in the region of 75%). 43 See, e.g., Sam Stein, Sotomayor’s Reversals No Different than Souter or Alito, Huffington Post (May 25, 2011, 2:25 PM), http://www.huffingtonpost.com/2009/05/27/sotomayors-reversals-no-d_n_208362.html.

IV. Analysis

As a starting point, it helps to put the numbers that we are going to see within the context of the debate over Sotomayor’s merit. Her detractors characterized her as having a mediocre record as a lower court judge and therefore unqualified on her merits to sit on the Supreme Court. 44 See Rosen, supra note 3. Of those other candidates, the federal judge whose name came up most often and who was thought to have unimpeachable intellectual stature was Diane Wood, of the Seventh Circuit. 45 See Milbank, supra note 8; Shapiro, supra note 8.

Where would the Sotomayor skeptics expect her to rank vis-à-vis the pool of possible alternative candidates for elevation to the High Court? Given the rhetoric described at the outset from scholars such as Tribe, Turley, and Rosen, we assume that the critics would predict Sotomayor to be in the bottom quarter of the distribution of all circuit court judges or at best somewhere around the mean.

A. Publications

We propose publication numbers as a rough proxy for judicial effort. Judges themselves talk about how published opinions take greater effort than unpublished ones. 46 See, e.g., Erica S. Weisgerber, Note, Unpublished Opinions: A Convenient Means to an Unconstitutional End, 97 Geo. L.J. 621, 625 (2009). Given that the judges have discretion in terms of which opinions they choose to designate “for publication” and which they dispose with a short memorandum or maybe even a couple of words (e.g., “affirmed”), the relative numbers of publications for a judge gives us a rough measure of effort. There are numerous caveats that are in order here though, including the fact that the circuit rules generally tell judges that they are to publish important and precedent-creating opinions. 47See generally Mitu Gulati & C.M.A. McCauliff, On Not Making Law, Law & Contemp. Probs., Summer 1998, at 157 (detailing the considerations that may effect a judge’s decision to publish an opinion). So, judges in circuits that have a greater diversity in terms of disputes may get a lot more cases worthy of precedent-creating opinions. That said, only a small fraction of the cases that show up before judges result in published opinions. 48 Id. In other words, each judge has plenty of opportunities to publish. Some judges choose to avail themselves of more of these opportunities than others.

A different caveat is that effort exerted in producing a published opinion may be taking away effort from other judicial tasks. This, while perhaps a concern at the district level, where judges need to do things like run trials and decide preliminary motions, is less of a concern at the appellate level, where the primary task is deciding appeals and explaining the reasons for those decisions. On the other hand, appellate judges may spend less time doing due diligence on the opinions of their fellow judges if the bulk of their time is taken up working on their own opinions.

B. Published Opinions

Here, we examine the number of opinions each judge authored that were sent to Westlaw with a “for publication” designation. We first look to see whether Sotomayor is in the bottom quarter of judges. For those judges in the bottom 25%, the highest number of opinions published is 53. Sotomayor, with 90 opinions, is well above that.

The mean number of published opinions is 86. As for the 75% level, the range starts at 109 opinions. At 90 opinions, Sotomayor is above the mean but not in the top 25%. Table I reports the top ten judges by publications. The Seventh Circuit’s Posner and Easterbrook show up at the top.

Table I. Top Ten Judges; Published Opinions

Judge

Circuit

Gender

Publications

Posner

7

Male

276

Easterbrook

7

Male

240

Lynch

1

Female

215

Riley

8

Male

198

Smith

8

Male

196

Melloy

8

Male

195

Kanne

7

Male

189

Bye

8

Male

189

Colloton

8

Male

171

Wollman

8

Male

170

Histogram I. Distribution of Publication Rates 49Density scales the height of the bars so that the sum of their areas equals 1.

Histogram I. Distribution of Publication Rates

Given the President’s interest in diversity and in appointing a female Justice, 50 See Jouvenal, supra note 39. along with the empirical reality that most Justices in recent years have been selected from the ranks of the sitting circuit judges, one might argue that the most relevant comparison set of judges for Sotomayor is the set of top-performing female judges. When we break the data down in terms of the top ten female publishers, Sotomayor is number seven on that list. Diane Wood, of the Seventh Circuit, is number three.

C. Published Pages

Raw publication numbers standing alone may not tell us enough about judicial effort. Some circuits may simply have cultures of sending all of their opinions, important or not, to be published. Or there might be individual judges who, for reasons of vanity, simply like seeing their opinions appear in print (judges sometimes refer to the West publications as the “vanity press for judges” 51 See Stephen J. Choi, Mitu Gulati & Eric A. Posner, What Do Federal District Judges Want? an Analysis of Publications, Citations, and Reversals, J.L. Econ. & Org. 1, 7 n.13 (Jan. 31, 2011), http://jleo.oxfordjournals.org/content/early/2011/01/31/jleo.ewq020.full?sid=400f5b79-da6f-404a-9af7-2b32af327af9. ). Sotomayor, therefore, may have simply been choosing to publish a lot of her very short opinions that others would not deign to publish. To test for this, we examine the number of pages she published vis-à-vis her competitors.

We begin with the distributional cutoffs. The bottom 25% tops out at 455 pages over three years. The mean is 713 pages, and the 75% level begins at 769 pages. Sotomayor published 888 pages from 2004 until 2006, putting her in the top quarter of judges in terms of published pages. Table II reports the numbers for the top ten judges overall (two female judges, Rovner and Lynch, are in this group). Sotomayor, with 888 pages, along with Wood, is in the group of top ten female judges.

Table II. Top Ten Judges; Published Opinion Pages

Judge

Court

Sex

Pages

Lynch

1

Female

2010

Ripple

7

Male

1649

Lipez

1

Male

1431

Clay

6

Male

1379

Posner

7

Male

1335

Rovner

7

Female

1315

Kanne

7

Male

1296

Selya

1

Male

1206

Torruella

1

Male

1172

Gilman

6

Male

1153

Histogram II. Distribution of Published Pages

Histogram II. Distribution of Published Pages

D. Citations

For citations, we look to four measures: (1) citations by federal courts outside the circuit (that is, in regions where we are confident that the cases would not constitute binding precedent); (2) citations by courts within the circuit; (3) citations by the state courts; and (4) citations in law reviews. As described earlier, each audience here is likely using the citation for different purposes, and therefore, the fact of a citation reveals different information about the judge being cited.

If the accounts by Tribe, Rosen, and Turley have descriptive value in this domain, we would have little reason to expect Sotomayor to do well with any of the audiences mentioned above. Her judicial opinions have at best been described as workmanlike and at worst been characterized as politically biased. Either way, one would not expect these to be the cases that other judges would cite to when looking for sources of authority. If possible, instead of citing to a Sotomayor opinion, they are more likely to cite to someone eminent, whose name carries weight, like Guido Calabresi or Richard Posner. Moreover, to the extent that citation counts measure a jurist’s impact, we expect undistinguished jurists to be at the bottom of the distribution of this measure.

In discussing the citation counts, as we did above, we begin in each case with a description of the distributions.

E. Law Journal Citations

This is the measure where we most expected to see Sotomayor scoring near the bottom. Even if her opinions were not as bad as characterized, the fact that many academics appeared to have a low opinion of her work at the outset should have resulted in her scores being low.

The distributional cutoff for the bottom 25% of judges on this measure is 175 citations. The mean number of citations, in turn, is 261. Sotomayor’s law journal citation count is 396—more than twice the number at the top of the twenty-fifth percentile. She not only slots in well above the 75% level (the bottom number being 323 for the top quarter) but also makes it into the top 10% (where the bottom score is 394).

Table III reports the top ten judges in terms of law journal citations. Sotomayor does not make the top ten overall. At the top, Easterbrook and Posner are ahead of the others. Two female judges make the top ten: Lynch of the First Circuit and Wood of the Seventh Circuit. Sotomayor is the third-most-cited female judge. The histogram illustrates where she ranks vis-à-vis the rest of the active federal appellate bench.

Table III. Top Ten Judges; Law Journal Citations

Judge

Circuit

Sex

Citations

Posner

7

Male

1054

Easterbrook

7

Male

832

Randolph

DC

Male

675

Lynch

1

Female

575

Birch

11

Male

553

Lipez

1

Male

534

Selya

1

Male

502

Wood

7

Female

482

Thomas

9

Male

459

Reinhardt

9

Male

458

Histogram III. Distribution Pattern of Law Journal Citations

Historgram III. Distribution Pattern of Law Journal Citations

F. Outside Citations

Of the various citation measures used by scholars as proxies for quality or influence, outside-jurisdiction (nonprecedential) cites are the most commonly used ones. For the most part, courts tend to cite opinions from within their jurisdictions. Citations to courts in other jurisdictions are less common and given out primarily when, so we presume, the opinion in question helps analyze a difficult question. Outside citations, therefore, provide a measure of how useful the analysis in an opinion is, divorced from precedential value. 52 E.g., Landes et al., supra note 23.

In the numbers we report, we add the numbers of citations from outside appeals courts to those from outside district courts. 53We also add in citations from bankruptcy and tax courts. The distributional cutoff at the bottom end of the distribution for outside citations (for the bottom 25%) is 180. The mean number of citations is 310. Sotomayor’s number of citations is 538. Those with more than 372 citations fall in the top quarter. That puts her at more than 150 citations above the cutoff for the top 25% of judges.

Table IV reports the top ten judges by outside-circuit citations. Posner and Easterbrook are at the top. Among the female judges, Lynch and Wood also show up again in the top ten overall. Sotomayor makes the top ten for female judges, slotting in at the third spot after Wood and Lynch.

Table IV. Top Ten Judges; Outside-Circuit Citations

Judge

Circuit

Sex

Citations

Easterbrook

7

Male

1873

Posner

7

Male

1489

Lynch

1

Female

890

Melloy

8

Male

848

Lipez

1

Male

778

Jacobs

2

Male

734

Wood

7

Female

716

Selya

1

Male

692

Calabresi

2

Male

635

Kanne

7

Male

584

Given that our outside-citations measure combines citations for both outside circuit courts and district courts, one might wonder about the breakdown between the two. Arguably, different information is revealed from the fact that a judge has a high district court citation count than from the fact that her high citation count is largely driven by appeals court citations. Below, we report separate histograms on the distributions of outside citations, as broken down in terms of level of court. Sotomayor is on the high side of the distribution in both cases, but she does significantly better on citations from other appeals courts.

Histograms IV & V. Outside-Circuit and Outside-District Citations

Histogram IV. Outside-Circuit Citations

Histogram V. Outside-District Citations

G. Inside Citations

A relatively underused citation measure is the number of inside-circuit citations. Here, the citations are primarily by lower courts within the circuit, for which the opinions by the circuit are precedential. This does not mean, however, that the sole reason for the citations is that the circuit’s opinion constituted precedent. Courts within the circuit will often have a wide range of cases from various judges that they can choose from to cite. The fact that one judge is consistently cited much more than others, therefore, potentially reveals something about the kinds of opinions that that judge is writing, as compared to his peers. A caveat here is that this measure is going to be significantly biased both in favor of and against judges from bigger circuits. In the bigger circuits, because there are many more appeals court decisions and many more district judges, the favored judges will get more cites. But, on the flip side, because the lower court judges have a greater degree of choice in terms of whom to cite, they can show more favoritism and more easily ignore the appellate judges they disfavor. Sotomayor, being on the Second Circuit, is on one of the larger circuits.

Once again, we begin with the distributional characteristics of the variable. At the bottom, at the 0–25% level, the highest number of citations is 349. The mean number of inside citations is 628. And, at the 75–100% level, the bottom number is 852.

Sotomayor’s number of inside citations is 6182. That puts her at the top for all judges and in the top ten for female judges (along with, yet again, Wood and Lynch).

Table V. Top Ten Judges; Inside-Circuit Citations

Judge

Circuit

Sex

Citations

Sotomayor

2

Female

6182

Posner

7

Male

5098

Raggi

2

Female

5095

Gould

9

Male

4827

Kanne

7

Male

4670

Cabranes

2

Male

4519

Easterbrook

7

Male

4329

Wood

7

Female

4296

Calabresi

2

Male

4170

Ripple

7

Male

4158

To show the split in Sotomayor’s inside citations between citations from the lower courts and by other panels of the Second Circuit, we report the histograms for inside-circuit and inside-district citations separately. As with the outside citations reported earlier, Sotomayor does better on the inside-circuit citations than with the district citations.

Histograms VI & VII. Inside-Circuit and Inside-District Citations

Histogram VI. Inside-Circuit Citations

Histogram VII. Inside-District Citations

H. State Court Citations

The state-court-citation measure is also a relatively underused measure. Like the inside-circuit-citation measure, it also has a built-in bias in that federal courts that sit in more densely populated states are likely to have more state court decisions citing them (because many of the issues are likely similar, particularly with diversity jurisdiction cases). With that caveat, the bottom quarter of judges, in terms of citations from the state courts, tops out at 31 citations for the three-year period that we use. The mean number of citations is roughly 53 for the three years, and the cutoff for the 75% range is 67.

Sotomayor has 158 cites from the state courts for the 2004 to 2006 period. That puts her not only in the top quarter of all judges (that is, above the 75% cutoff) but also at the very top of all judges. The only judge who does better than she does is Judge O’Scannlain, who has one cite more than she does. Table VI reports on the top ten judges in terms of state citations. Sotomayor is the only female judge to make the top-ten list for state court citations.

Table VI. Top Ten Judges; State Court Citations

Judge

Circuit

Sex

Citations

O’Scannlain

9

Male

159

Sotomayor

2

Female

158

Posner

7

Male

157

Howard

1

Male

129

Easterbrook

7

Male

127

Selya

1

Male

118

Gilman

6

Male

116

Lipez

1

Male

115

Colloton

8

Male

111

Torruella

1

Male

103

In terms of the female judges, Sotomayor has the highest score. Histogram VIII provides a graphical illustration of state court citations.

Histogram VIII. Distribution of State Citations

Histogram VIII. Distribution of State Citations

I. The Team-Player Effect

A criticism that could be leveled against the prior measures is that they treat appellate judging as an individual act. But appeals court judges almost always operate in panels (typically three-judge panels, unless there is a rare en banc panel). To fully evaluate the amount a judge contributes in terms of quality, therefore, one should take into account not only the performance of the opinions where the judge was the primary author but also the performance of opinions where she was a secondary player. To estimate this secondary-author effect, we construct a measure that compares each of our 136 judges, for the three years for which we have data, in terms of citation counts to opinions where they were secondary actors in producing the opinion.

A caveat here is that, at least as a matter of anecdote, overburdened federal judges in the modern era typically spend the vast majority of their time on the opinions for which they are the primary author and a small amount of time on those for which they are secondary authors. Moreover, the measure does not distinguish between potential ways of contributing to a team. A judge could do more due diligence or threaten to whistle-blow, i.e., dissent from a poorly constructed majority opinion. A judge could also simply contribute by being present as a diverse input. Or a judge could do nothing and let the primary author be solely responsible for the opinion. From our perspective, it is not necessary to be able to unpack the precise fashion in which an individual judge contributes to the team product. Because the question being asked involves estimating merit for elevation to the High Court and because the High Court is more team-production oriented than the lower appeals courts (nine Justices, as opposed to three judges), a judge who contributes positively to the team at the lower level may contribute similarly on the High Court.

In theory, we could generate these secondary-author effects for all of our citation measures. However, because of space constraints, we only report it for the primary-citation measure used in the literature—outside citations (the sum of citations from federal appeals courts in other circuits and outside federal district courts). 54Other measures are available on request.

The top of the range for the bottom 25% is 212 citations. And the mean number of citations is 363. Sotomayor has a count of 615, which is well outside the range of the bottom 25% and much above the mean. The cutoff for the top 25% on this measure is 410.5. Sotomayor has a count of 615, which makes the cutoff for the top 10%.

Histogram IX. Distribution of Team Citations

Histogram IX. Distribution of Team Citations

Table VII. Top Ten Judges; Team-Citation Effect

Judge

Circuit

Sex

Citations

Rovner

7

Female

1436

Williams

7

Female

1433

Wood

7

Female

1394

Howard

1

Male

1113

Kanne

7

Male

1096

Ripple

7

Male

1014

Posner

7

Male

1004

Evans

7

Male

976

Manion

7

Male

908

Riley

8

Male

852

As the table for the top ten judges illustrates though, the problem with the team analysis is that it basically picks up strong-circuit effects. That is, circuits that have cultures of high levels of productivity will have their judges show up as high performers (of course, because we are measuring team effects). Also, there is likely a Posner–Easterbrook–Wood effect on the Seventh Circuit. The other judges on their circuit may have high team numbers because they are inevitably sitting with one or two of the triumvirate of Posner–Easterbrook–Wood. The top-ten table here, therefore, is dominated by Seventh Circuit judges.

In the top-ten list for females, Sotomayor shows up as number four. Wood (who was also in the top-ten-overall list) and Lynch also show up here. 55One might expect that these measures should be roughly twice the citation count for when judges are authors of the opinions (after all, judges write opinions on only about a third of the cases that they decide). They are not. The reason has to do with the fact that we restrict our analysis to the 136 active judges who authored opinions throughout the period from 2004 to 2006. Many of the panels also have nonwriting judges, such as judges from district courts, senior judges, and judges who were promoted during the timeframe. See generally William M. Richman & William L. Reynolds, Elitism, Expediency, and the New Certiorari: Requiem for the Learned Hand Tradition, 81 Cornell L. Rev. 273, 287 (1996) (discussing the use of visiting judges on appellate court panels).

J. Circuit and Subject-Area Controls

As others have noted, the various circuits can differ in terms of culture. 56 See James J. Brudney et al., Judicial Hostility Toward Labor Unions? Applying the Social Background Model to a Celebrated Concern, 60 Ohio St. L.J. 1675, 1680 (1999) (explaining that prior studies have failed to address significant differences in circuit court cultures); Choi & Gulati, supra note 23, at 44–45. For example, some might develop cultures of publication, where the judges are under peer pressure to publish, and others might, for whatever reason, disfavor publication. 57 See Choi & Gulati, supra note 23, at 44–45. The Seventh Circuit, for example, has long had a culture of publishing many more opinions (and garnering many more cites) than the other circuits. 58 See John R. Lott, Jr., Op-Ed., Pulling Rank, N.Y. Times, Jan. 25, 2006, at A1; Orin Kerr, Rates of Unpublished Opinions in the Different Circuits—and Especially the Fourth Circuit, Volokh Conspiracy (Sept. 8, 2011, 12:53 PM), http://volokh.com/2011/09/08/rates-of-unpublished-opinions-in-the-different-circuits-and-especially-the-fourth-circuit/ (listing the Seventh Circuit with the lowest rate of unpublished opinions). Circuits can also differ in terms of the types of cases that they receive. The cases that show up in front of a federal court in Montana are going to be quite different than those that show up in New York City. The former, for example, is unlikely to see a case involving the resolution of the debt crisis in Argentina. 59 E.g., NML Capital v. Republic of Argentina, 621 F.3d 230 (2d Cir. 2010). Individual judges also will differ in terms of the types of cases they take on—judges, because of their backgrounds and the relative expertise levels of their colleagues, may choose to take on opinions in particular subject areas and defer to their colleagues in others.

The measures presented thus far have not controlled for these effects. And whether they should is a complicated matter. Most of these circuits tend to be small, and that means that the culture is, in significant part, likely to be the product of the preferences and collaborative instincts of the judges on that circuit. Put differently, having developed a culture of high productivity in a circuit is arguably an indication of merit in and of itself. The same argument can be made for subject areas. If a judge goes out of her way to pick her writing assignments for cases in subject areas that produce high levels of citations, that fact is itself arguably an indicator of merit. Those caveats aside though, circuit cultures can be a function of long-past historical events, and the subject areas in which a judge receives cases can be determined by location.

In this final section, therefore, we report on the rankings of judges on the outside-citation measure and law-journal-citation measure, where we control for both circuit and subject-area effects. We also control for year effects because the date of publication is likely an important determinant of the number of citations accrued by our cutoff date. 60Because citations are calculated for all opinions from the period from 2004 until 2006, tallied from the date of publication up to January 1, 2009, opinions written in 2004 will garner more citations than those written in 2006, other things equal.

Formally, our specification is:

Outcomeijscy = ßj*Judgej + Yeary + Subjects + εijscy

In this equation, i denotes case, j denotes judge, c denotes circuit, y denotes year, and s denotes subject. We consider two outcomes: total outside citations and citations from law reviews and treatises. 61Other regressions are available on request. The coefficients of interest are ßj, the fixed-effect coefficients on the dummy indicators for each judge. 62A dummy indicator is equal to one if the observation belongs to that judge and zero otherwise. The error term is represented by εijscy. These coefficients give us an average citation count per published opinion written by the judges.

In all of these regressions, we omit the dummy indicator for Sotomayor. Consequently, the judge-fixed effects indicate each judge’s performance in comparison to Sotomayor’s and whether the comparison is statistically significantly different.

Column 1 of Table A in Appendix A reports unadjusted judge-fixed effects without adjusting for year, subject, or circuit. To situate the reader and make these results comparable to the previous descriptive statistics, Histogram X shows the distribution of per capita outside citations, and Histogram XII shows the distribution of law review citations. Column 2 controls for year-fixed effects, and Column 3 controls for year- and subject-fixed effects. Column 4 standardizes by the mean and standard deviation for the outcomes within each circuit and also controls for year- and subject-fixed effects. We could not directly include circuit-fixed effects because our primary interest is in the judge-fixed effects, and if we included the circuit-fixed effects, eleven judges would drop out due to collinearity. Histograms XI and XIII show the distribution of these standardized fixed effects.

We find that Sotomayor ranks twelfth in outside citations per case among all judges (as seen in Table A of Appendix A). Only five judges have statistically significant (at the 10% level) more outside citations per case than her. Sixty-six judges have statistically significant fewer outside citations per case than her, and this number increases slightly when adjusting for year- and subject-fixed effects. When the citations are normalized by the mean and standard deviation of citations within each circuit, Sotomayor still does better than most judges, as indicated by Histogram XI. None of the judge-fixed effects are statistically significant in Column 4 of Table A.

On law reviews also, Sotomayor performs well. Only five judges have statistically significant more law review citations per case than her (as seen in Table B of Appendix A), while forty judges have statistically significant fewer law review citations per case than her.

Histogram X. Distribution of Outside Citations per Case

Histogram X. Distribution of Outside Citations per Case

Histogram XI. Distribution of Normalized Outside Citations per Case

Histogram XI. Distribution of Normalized Outside Citations per Case

Histogram XII. Distribution of Law Review Citations per Case

Histogram XII. Distribution of Law Review Citations per Case

Histogram XIII. Distribution of Normalized Law Review Citations per Case

Histogram XIII. Distribution of Normalized Law Review Citations per Case

V. Outliers

A final test is to examine whether Sotomayor’s scores are being driven by outliers. For example, perhaps a large fraction of her citations come from just one or two big opinions. Further, what if those one or two opinions were in cases where her assignment to those cases was purely by random chance? Maybe those were cases addressing topics of first impression that then got cited everywhere simply because those were the first cases of those types. 63The issue of outliers obviously does not apply to the measure of published opinions. To test for the outlier effect, we winsorize our citation data to address the possibility that outliers are driving the results. Specifically, we replace the top 0.5% extreme values with the 99.5 percentile value and replace the bottom 0.5% extreme values with the 0.5 percentile. We restrict our attention to the two primary forms of citation measures: outside citations and law review citations.

The results indicate that Sotomayor’s relative performance against the other judges is not being driven by the presence of outliers. Indeed, she performs slightly better against her colleagues when the data are adjusted for outliers. On the winsorized measures, Sotomayor is in the top ten among all judges for outside citations. She is still at the 90.44 percentile for law review citations. Posner, Easterbrook, Wood, and Lynch all show up again in both top-ten tables.

Table VIII. Top Ten Judges; Outside Citations (Winsorized)

Judge

Circuit

Sex

Citations

Posner

7

Male

1310

Easterbrook

7

Male

1270

Lynch

1

Female

883

Selya

1

Male

674

Wood

7

Female

674

Ripple

7

Male

576

Kanne

7

Male

568

Lipez

1

Male

559

Sotomayor

2

Female

498

McConnell

10

Male

492

Histogram XIV. Distribution of Outside Citations (Winsorized)

Histogram XIV. Distribution of Outside Citations (Winsorized)

Table IX. Top Ten Judges; Law Review & Periodical Citations (Winsorized)

Judge

Circuit

Sex

Citations

Posner

7

Male

946

Easterbrook

7

Male

768

Lynch

1

Female

575

Selya

1

Male

502

Wood

7

Female

457

Lipez

1

Male

440

Ripple

7

Male

394

Reinhardt

9

Male

389

Cabranes

2

Male

383

Smith

5

Male

381

Histogram XV. Distribution of Law Review & Periodical Citations (Winsorized)

Histogram XV. Distribution of Law Review & Periodical Citations (Winsorized)

Unreported here, we also examined the winsorized outside-citation regressions (where, as described earlier, we control for matters such as circuit-, year-, and subject-area effects). 64These results are available from the authors. Once again, Sotomayor performs better with the winsorizing process. Previously, in the raw data, six judges performed statistically significantly better than Sotomayor. Now, in the winsorized data, no judge performs statistically significantly better than Sotomayor, and forty additional judges perform statistically significantly worse than her.

Conclusion

Sotomayor’s critics described her as a mediocre judge, one unworthy to take a place on the High Court. Our data do not support that conclusion. According to our measures, she was one of the best judges on the courts of appeals. We compared her performance whilst on the Second Circuit against that of all the other active federal appeals court judges over a three-year period. She was easily in the top 25% of all of the judges on the courts of appeals in almost all of the categories that we examined. Moreover, in more than half the categories, she was in the top 10%. These results should at least bring into question the claims of her mediocrity. Indeed, based on our results, there is the strong possibility that she was, during her tenure on the Second Circuit, among the most capable and influential appeals court judges in the country.

Among the responses we have received from our academic colleagues so far, one that we have heard a few times is that demonstrating that Sotomayor shows up in the top 25% or top 10% of all judges does not in fact challenge claims of her mediocrity. 65To be specific, we were told that we were “damning her with faint praise” and were doing more harm than good by bringing up the issue of her merit again. That, for promotion to the High Court, an appeals court judge should show up in the top 1% or 2% of all judges. Maybe so. But then that same standard should be applied across the board. And if so, the subset of names we would be considering for elevation would be rather small.

Table X sets out a summary of Sotomayor’s performance on the various measures.

Table X. Sotomayor’s Performance Vis-à-Vis Thirteen Measures

Measure

Bottom 25%

Above the Mean

Top 25%

Top Ten (Female)

Top Ten (Overall)

Percentile

Publications

N

Y

N

Y

N

70.6%

Pages

N

Y

Y

Y

N

83.1%

Law Journal Cites

N

Y

Y

Y

N

90.4%

Outside-Circuit Cites

N

Y

Y

Y

N

95.6%

Inside-Circuit Cites

N

Y

Y

Y

Y

99.6%

State Court Cites

N

Y

Y

Y

Y

99.2%

Secondary-Author Effect: Outside Cites

N

Y

Y

Y

N

89.7%

Controlling for Subject-Area Effects

N

Y

Y

Y

N

Outside Cites: 91.2%

Law Rev. Cites: 83.8%

Normalizing for Circuit Effects

N

Y

Y

N

N

Outside Cites: 82.4%

Law Rev. Cites: 55.9%

Winsorized Outside Cites and

Law Journal Cites

N

N

Y

Y

Y

Y

Y

Y

Y

N

Outside Cites: 93.38%

Law Rev. Cites: 90.44%

A related question is whether the treatment Sotomayor received was any different from what other candidates from the appeals courts would have received. We cannot do an effective comparison here because so few appeals court judges get promoted to the High Court. But a couple of casual comparisons do suggest that the treatment Sotomayor received, in terms of questions about her intellectual capabilities as a judge, was different. One contemporaneous comparison is to Diane Wood, who performed at roughly the same level as Sotomayor and was a serious contender for the Court at least twice in recent years. 66Wood also performed at a high level in a prior study examining a time period roughly five years prior. See Choi & Gulati, supra note 23, at 68–69. Wood’s intellectual capabilities were generally lauded 67 See John McCormick & Jeff Coe, Driven Judge Has Music in Her Heart, Chi. Trib., May 24, 2009, at C6; David Savage, Obama Speaks with Diane Wood Ahead of Supreme Court Pick, Chi. Trib., May 5, 2010, at C10. and not challenged in anywhere near the fashion as Sotomayor’s were.

Justice Alito, who was elevated to the High Court some years prior, provides another imperfect comparison. In a prior study, done before Alito’s nomination, his performance was ranked against that of his colleagues. 68 See Choi & Gulati, supra note 23, at 83. Like we did for Sotomayor, we examined the data on him for a three-year period that came roughly from the middle of his tenure on the bench. 69 See id. at 31 (narrowing the period to the years from 1998 until 2000). Unlike in our current study though, Justice Alito’s performance was not the primary subject of the prior study. See id. Overall, he was sixteenth out of a sample of roughly one hundred federal appellate judges who were under the age of sixty-five—to our minds, a high level of performance. 70 See id. at 113–15. Our current sample looks at a broader set of judges than the prior study did, because we look at all active judges and not just the ones under the age of sixty-five. If we were to assume that the additional judges would have all performed in the bottom half of the distribution, then Alito would be roughly near the top 10% of all judges (16 out of 136). Another issue to note in the Alito comparison is that Alito’s scores were particularly high on a category that we did not estimate for this project: independence. Id. at 69. Independence in the prior study was measured as a function of dissents against other judges with the same party affiliation (the overall measure being normalized for the relative numbers of judges from each party on the circuit in question). See id. at 64. The nomination was contentious, and Alito was attacked from many directions. 71 See David D. Kirkpatrick, Conservatives Scrambling to Prepare for a Tough Fight, N.Y. Times, Nov. 1, 2005, at A23 (noting that Alito’s record on abortion and other contentious issues made for a tough fight in the Senate). But his intellectual capabilities did not receive serious challenge—if anything, there seemed to be general agreement regarding his high level of intellect. With Sotomayor, however, things were different.

Our point, though, is not to complain about the treatment Sotomayor received. It is to raise the question of whether, in cases like this, where there is a risk of bias with the subjective measures, more attention should be paid to objective measures. 72We should point out that our analysis cannot completely separate individual merit from a possible diversity effect. Perhaps being on the Second Circuit, Sotomayor got highly cited because of her “different” perspective vis-à-vis her colleagues. Nevertheless, a clean measure of individual merit is not necessary to ask whether Sotomayor was as meritorious as other candidate judges, because she would bring her diversity effect to the Supreme Court as well. When there is a disconnect between the subjective conclusions and the objective measures, it may be worth looking deeper.

Ultimately, do our data tell us anything about Sotomayor’s future performance as a Supreme Court Justice? Presumably, those who opposed her nomination on the ground that she was not that smart were also making a prediction with respect to her impact on the Supreme Court. On the basis of our measures, we are willing to wager that she surprises her critics by outperforming the majority of her colleagues on the Court.

Appendix A

Column 1 of Table A reports unadjusted judge-fixed effects, i.e., without adjusting for year, subject, or circuit. Column 2 controls for year-fixed effects. Column 3 controls for year- and subject-fixed effects. Column 4 standardizes by the mean and standard deviation for the outcomes within each circuit and also controls for year- and subject-fixed effects. Coefficients are displayed in the first row, and standard errors in brackets are displayed in the second row. Each pair of rows represents the fixed effect for the judge listed. Each judge is identified by last name and his or her circuit. Year- and subject-matter-fixed-effect coefficients are displayed at the bottom.

Table A. Outside Citations per Case

(1)

(2)

(3)

(4)

Outside Citations

Normalized Outside Citations

Barry (3)

8.594

8.817

8.855

0.0253

[2.431]***

[2.426]***

[2.425]***

[0.240]

Scirica (3)

4.308

3.986

3.799

-0.0863

[1.998]**

[1.994]**

[1.996]*

[0.198]

Batchelder (6)

4.258

4.149

4.192

-0.00702

[1.758]**

[1.754]**

[1.753]**

[0.174]

Anderson (11)

3.701

3.677

3.606

-0.0264

[2.171]*

[2.166]*

[2.166]*

[0.215]

Calabresi (2)

2.966

2.958

3.074

0.0000161

[1.592]*

[1.589]*

[1.588]*

[0.158]

Hull (11)

2.244

2.271

2.276

-0.00317

[1.978]

[1.974]

[1.976]

[0.196]

Jacobs (2)

2.178

2.161

2.127

-0.018

[1.495]

[1.492]

[1.492]

[0.148]

Easterbrook (7)

1.826

1.719

1.566

-0.0442

[1.240]

[1.237]

[1.238]

[0.123]

Marcus (11)

1.28

1.304

1.485

0.0304

[1.626]

[1.622]

[1.631]

[0.162]

King (5)

1.238

1.123

1.173

-0.00997

[1.633]

[1.629]

[1.629]

[0.162]

Wilkins (4)

0.815

0.59

0.464

-0.0326

[1.737]

[1.733]

[1.734]

[0.172]

Raggi (2)

-0.204

-0.344

-0.48

-0.0344

[1.737]

[1.733]

[1.732]

[0.172]

Wilson (11)

-0.248

-0.245

-0.0762

0.0281

[1.959]

[1.955]

[1.960]

[0.194]

Lipez (1)

-0.257

-0.337

-0.49

-0.0344

[1.363]

[1.360]

[1.360]

[0.135]

Paez (9)

-0.382

-0.571

-0.543

-0.0377

[1.805]

[1.802]

[1.802]

[0.179]

Traxler (4)

-0.503

-0.582

-0.769

-0.0285

[1.906]

[1.902]

[1.902]

[0.189]

Katzmann (2)

-0.539

-0.582

-0.579

-0.018

[1.890]

[1.886]

[1.887]

[0.187]

Posner (7)

-0.583

-0.654

-0.586

-0.0154

[1.218]

[1.215]

[1.216]

[0.121]

Carnes (11)

-0.589

-0.544

-0.598

0.00422

[1.586]

[1.583]

[1.584]

[0.157]

Birch (11)

-0.621

-0.758

-0.816

-0.0537

[1.707]

[1.704]

[1.706]

[0.169]

Wilkinson (4)

-0.657

-0.757

-0.804

-0.0367

[1.536]

[1.533]

[1.534]

[0.152]

Sack (2)

-0.937

-0.924

-1.101

-0.0293

[1.580]

[1.577]

[1.575]

[0.156]

Shedd (4)

-0.955

-1.091

-1.219

-0.0267

[1.860]

[1.856]

[1.855]

[0.184]

Duncan (4)

-1.01

-1.222

-1.334

-0.0472

[2.089]

[2.085]

[2.085]

[0.207]

Reinhardt (9)

-1.043

-1.148

-1.324

-0.0619

[1.557]

[1.554]

[1.555]

[0.154]

McKeown (9)

-1.175

-1.216

-1.356

-0.0484

[1.626]

[1.622]

[1.624]

[0.161]

Cabranes (2)

-1.26

-1.403

-1.504

-0.0388

[1.487]

[1.484]

[1.484]

[0.147]

Williams (4)

-1.272

-1.208

-1.203

0.0064

[1.758]

[1.754]

[1.755]

[0.174]

Graber (9)

-1.281

-1.384

-1.538

-0.0456

[1.626]

[1.622]

[1.622]

[0.161]

Tjoflat (11)

-1.422

-1.65

-1.672

-0.0383

[1.586]

[1.583]

[1.587]

[0.157]

Sloviter (3)

-1.503

-1.635

-1.892

-0.0514

[1.552]

[1.549]

[1.548]

[0.154]

Davis (5)

-1.526

-1.594

-1.473

0.00784

[1.656]

[1.652]

[1.654]

[0.164]

Selya (1)

-1.598

-1.736

-1.858

-0.0402

[1.325]

[1.322]

[1.321]

[0.131]

Smith (3)

-1.608

-1.62

-1.693

-0.015

[1.818]

[1.814]

[1.814]

[0.180]

Wood (7)

-1.612

-1.75

-1.852

-0.0413

[1.316]

[1.313]

[1.313]

[0.130]

Melloy (8)

-1.629

-1.747

-1.81

-0.0226

[1.278]

[1.276]

[1.277]

[0.127]

Rendell (3)

-1.63

-1.764

-1.884

-0.0583

[1.818]

[1.814]

[1.815]

[0.180]

Thomas (9)

-1.705

-1.86

-1.871

-0.0516

[1.717]

[1.714]

[1.716]

[0.170]

Dubina (11)

-1.728

-1.74

-1.755

-0.0156

[1.793]

[1.789]

[1.789]

[0.177]

McConnell (10)

-1.773

-1.714

-1.754

0.0139

[1.406]

[1.403]

[1.405]

[0.139]

Tymkovich (10)

-1.809

-1.829

-1.988

-0.0107

[1.499]

[1.496]

[1.496]

[0.148]

Lynch (1)

-1.838

-1.973

-2.028

-0.0425

[1.259]

[1.257]

[1.256]

[0.125]

Sutton (6)

-1.893

-1.881

-1.978

-0.0159

[1.527]

[1.523]

[1.523]

[0.151]

Fisher (3)

-1.931

-1.786

-1.992

-0.0213

[1.860]

[1.856]

[1.855]

[0.184]

Black (11)

-1.978

-2.075

-2.029

0.00709

[1.874]

[1.871]

[1.871]

[0.186]

Ambro (3)

-2.023

-1.95

-2.071

-0.0176

[1.499]

[1.496]

[1.496]

[0.148]

Wiener (5)

-2.026

-2.139

-2

-0.000305

[1.656]

[1.652]

[1.652]

[0.164]

Boudin (1)

-2.064

-2.153

-2.159

-0.00979

[1.382]

[1.379]

[1.379]

[0.137]

Michael (4)

-2.069

-2.2

-2.238

-0.0301

[1.717]

[1.713]

[1.714]

[0.170]

Moore (6)

-2.088

-2.029

-2.224

-0.00775

[1.429]

[1.426]

[1.426]

[0.141]

Murphy (10)

-2.101

-2.166

-2.331

-0.024

[1.536]

[1.533]

[1.535]

[0.152]

Fletcher (9)

-2.167

-2.315

-2.401

-0.0573

[1.574]

[1.571]

[1.572]

[0.156]

Fuentes (3)

-2.182

-2.138

-2.257

-0.0127

[1.781]

[1.777]

[1.776]

[0.176]

Pooler (2)

-2.228

-2.266

-2.319

-0.0292

[1.586]

[1.583]

[1.582]

[0.157]

Gibbons (6)

-2.249

-2.248

-2.416

-0.0204

[1.599]

[1.595]

[1.594]

[0.158]

Hartz (10)

-2.282

-2.382

-2.425

-0.00494

[1.380]*

[1.377]*

[1.378]*

[0.137]

Cook (6)

-2.364

-2.487

-2.49

-0.0166

[1.845]

[1.841]

[1.841]

[0.183]

Fisher (9)

-2.369

-2.523

-2.622

-0.0424

[1.605]

[1.602]

[1.602]

[0.159]

Garland (DC)

-2.39

-2.512

-2.258

0.02

[1.648]

[1.644]

[1.651]

[0.164]

Bybee (9)

-2.416

-2.426

-2.491

-0.00806

[1.698]

[1.694]

[1.694]

[0.168]

Ripple (7)

-2.426

-2.522

-2.523

-0.0198

[1.317]*

[1.315]*

[1.317]*

[0.131]

Berzon (9)

-2.437

-2.508

-2.595

-0.0344

[1.517]

[1.514]*

[1.514]*

[0.150]

Smith (5)

-2.443

-2.401

-2.566

-0.00933

[1.409]*

[1.406]*

[1.406]*

[0.139]

Parker (2)

-2.444

-2.467

-2.546

-0.0199

[1.672]

[1.668]

[1.668]

[0.165]

Jones (5)

-2.497

-2.668

-2.819

-0.0502

[1.557]

[1.554]*

[1.554]*

[0.154]

Hawkins (9)

-2.521

-2.8

-2.865

-0.0748

[1.998]

[1.994]

[1.996]

[0.198]

Wesley (2)

-2.528

-2.56

-2.588

-0.0122

[1.906]

[1.902]

[1.903]

[0.189]

Boggs (6)

-2.557

-2.739

-2.918

-0.0414

[1.605]

[1.602]*

[1.602]*

[0.159]

Kelly (10)

-2.581

-2.683

-2.67

-0.00763

[1.580]

[1.577]*

[1.578]*

[0.157]

Higginbotham (5)

-2.615

-2.596

-2.549

0.0196

[1.541]*

[1.538]*

[1.538]*

[0.152]

Motz (4)

-2.69

-2.803

-2.775

-0.0148

[1.580]*

[1.577]*

[1.581]*

[0.157]

Straub (2)

-2.717

-2.811

-2.738

-0.012

[1.818]

[1.814]

[1.813]

[0.180]

Ginsburg (DC)

-2.745

-2.912

-2.653

0.00539

[1.580]*

[1.577]*

[1.585]*

[0.157]

Gould (9)

-2.761

-2.917

-2.979

-0.0297

[1.468]*

[1.465]**

[1.467]**

[0.145]

Howard (1)

-2.765

-2.821

-2.886

-0.00756

[1.394]**

[1.391]**

[1.390]**

[0.138]

Pregerson (9)

-2.781

-2.789

-2.946

-0.042

[1.592]*

[1.589]*

[1.589]*

[0.158]

Lucero (10)

-2.793

-2.901

-2.74

0.0098

[1.487]*

[1.484]*

[1.484]*

[0.147]

Henry (10)

-2.884

-3.075

-3.025

-0.0249

[1.640]*

[1.637]*

[1.639]*

[0.163]

Clifton (9)

-2.887

-3.082

-3.214

-0.0554

[1.845]

[1.842]*

[1.841]*

[0.183]

Kanne (7)

-2.888

-2.953

-3.1

-0.0305

[1.285]**

[1.282]**

[1.284]**

[0.127]

Daughtrey (6)

-2.947

-2.954

-2.911

0.00073

[2.041]

[2.037]

[2.037]

[0.202]

O’Scannlain (9)

-3.001

-3.011

-3.031

-0.0111

[1.504]**

[1.501]**

[1.501]**

[0.149]

Manion (7)

-3.03

-3.108

-3.123

-0.0209

[1.409]**

[1.406]**

[1.408]**

[0.140]

Wardlaw (9)

-3.037

-3.024

-3.259

-0.052

[1.758]*

[1.755]*

[1.756]*

[0.174]

Luttig (4)

-3.079

-3.285

-3.219

-0.0239

[1.680]*

[1.677]*

[1.678]*

[0.166]

Rovner (7)

-3.106

-3.284

-3.338

-0.0389

[1.316]**

[1.313]**

[1.314]**

[0.130]

Flaum (7)

-3.123

-3.251

-3.28

-0.0326

[1.346]**

[1.343]**

[1.346]**

[0.133]

Briscoe (10)

-3.212

-3.259

-3.266

-0.00406

[1.536]**

[1.533]**

[1.533]**

[0.152]

Tacha (10)

-3.238

-3.361

-3.524

-0.0212

[1.580]**

[1.577]**

[1.577]**

[0.156]

Kleinfeld (9)

-3.258

-3.392

-3.601

-0.0424

[1.698]*

[1.695]**

[1.694]**

[0.168]

O’Brien (10)

-3.263

-3.219

-3.458

-0.0164

[1.874]*

[1.870]*

[1.872]*

[0.186]

Niemeyer (4)

-3.289

-3.365

-3.41

-0.0357

[1.557]**

[1.554]**

[1.555]**

[0.154]

Williams (7)

-3.308

-3.495

-3.57

-0.0413

[1.389]**

[1.386]**

[1.387]**

[0.138]

Clay (6)

-3.311

-3.327

-3.367

-0.000371

[1.371]**

[1.368]**

[1.368]**

[0.136]

Cole (6)

-3.32

-3.484

-3.455

-0.0159

[1.580]**

[1.577]**

[1.576]**

[0.156]

Jolly (5)

-3.378

-3.528

-3.496

-0.0225

[1.568]**

[1.565]**

[1.565]**

[0.155]

Sentelle (DC)

-3.386

-3.568

-3.246

0.0204

[1.592]**

[1.589]**

[1.605]**

[0.159]

Gilman (6)

-3.393

-3.401

-3.52

-0.00464

[1.323]**

[1.320]**

[1.320]***

[0.131]

Randolph (DC)

-3.411

-3.519

-3.474

-0.0122

[1.619]**

[1.615]**

[1.622]**

[0.161]

Murphy (8)

-3.444

-3.494

-3.637

-0.0172

[1.365]**

[1.362]**

[1.364]***

[0.135]

Silverman (9)

-3.448

-3.623

-3.857

-0.0778

[2.019]*

[2.015]*

[2.015]*

[0.200]

Rawlinson (9)

-3.457

-3.71

-4.048

-0.0888

[1.793]*

[1.789]**

[1.789]**

[0.177]

Loken (8)

-3.472

-3.493

-3.589

-0.0147

[1.322]***

[1.319]***

[1.320]***

[0.131]

Colloton (8)

-3.51

-3.543

-3.566

0.00315

[1.306]***

[1.304]***

[1.305]***

[0.129]

McKee (3)

-3.51

-3.957

-4.086

-0.0846

[1.805]*

[1.802]**

[1.802]**

[0.179]

Barkett (11)

-3.522

-3.704

-3.828

-0.0467

[1.698]**

[1.695]**

[1.695]**

[0.168]

Benavides (5)

-3.544

-3.446

-3.411

0.0182

[1.527]**

[1.523]**

[1.522]**

[0.151]

Tatel (DC)

-3.545

-3.752

-3.365

0.0148

[1.574]**

[1.571]**

[1.579]**

[0.157]

King (4)

-3.549

-3.612

-3.666

-0.023

[1.599]**

[1.595]**

[1.596]**

[0.158]

Kozinski (9)

-3.568

-3.647

-3.824

-0.0379

[1.664]**

[1.660]**

[1.661]**

[0.165]

Tallman (9)

-3.594

-3.823

-3.95

-0.0581

[1.672]**

[1.669]**

[1.668]**

[0.165]

Schroeder (9)

-3.599

-3.828

-3.767

-0.0397

[1.959]*

[1.955]*

[1.958]*

[0.194]

Rogers (6)

-3.641

-3.736

-3.733

-0.0059

[1.426]**

[1.423]***

[1.423]***

[0.141]

Clement (5)

-3.657

-3.773

-3.948

-0.0333

[1.536]**

[1.533]**

[1.533]**

[0.152]

Torruella (1)

-3.663

-3.733

-3.775

-0.0154

[1.314]***

[1.312]***

[1.311]***

[0.130]

DeMoss (5)

-3.675

-3.957

-3.765

-0.02

[1.563]**

[1.560]**

[1.561]**

[0.155]

Prado (5)

-3.692

-3.773

-3.846

-0.026

[1.557]**

[1.554]**

[1.554]**

[0.154]

Barksdale (5)

-3.728

-3.796

-4.026

-0.0334

[1.845]**

[1.841]**

[1.844]**

[0.183]

Martin (6)

-3.731

-3.82

-3.727

0.00292

[1.351]***

[1.349]***

[1.348]***

[0.134]

Wollman (8)

-3.754

-3.845

-3.91

-0.0131

[1.308]***

[1.305]***

[1.306]***

[0.130]

Rymer (9)

-3.811

-4.058

-4.221

-0.0721

[1.727]**

[1.723]**

[1.724]**

[0.171]

Evans (7)

-3.815

-3.862

-3.904

-0.0185

[1.378]***

[1.375]***

[1.376]***

[0.136]

Henderson (DC)

-3.819

-3.921

-3.578

0.0306

[1.504]**

[1.501]***

[1.517]**

[0.151]

Riley (8)

-3.892

-4.025

-4.09

-0.0223

[1.275]***

[1.273]***

[1.276]***

[0.127]

Arnold (8)

-4.028

-4.081

-4.145

-0.00373

[1.323]***

[1.320]***

[1.323]***

[0.131]

Gregory (4)

-4.072

-4.274

-4.361

-0.0542

[1.640]**

[1.637]***

[1.637]***

[0.162]

Edmondson (11)

-4.078

-4.493

-4.576

-0.0333

[3.344]

[3.337]

[3.334]

[0.331]

Smith (8)

-4.08

-4.18

-4.279

-0.0199

[1.277]***

[1.275]***

[1.277]***

[0.127]

Dennis (5)

-4.122

-4.08

-4.15

0.00593

[1.527]***

[1.524]***

[1.523]***

[0.151]

Bea (9)

-4.166

-4.222

-4.264

-0.0112

[1.737]**

[1.733]**

[1.733]**

[0.172]

Bye (8)

-4.348

-4.509

-4.444

-0.0133

[1.285]***

[1.282]***

[1.283]***

[0.127]

Garza (5)

-4.362

-4.332

-4.324

-0.00327

[1.420]***

[1.417]***

[1.422]***

[0.141]

Stewart (5)

-4.417

-4.348

-4.301

0.0131

[1.464]***

[1.461]***

[1.462]***

[0.145]

Rogers (DC)

-4.506

-4.58

-4.306

0.0309

[1.499]***

[1.496]***

[1.511]***

[0.150]

Callahan (9)

-5.053

-5.133

-5.223

-0.0416

[1.737]***

[1.733]***

[1.733]***

[0.172]

Year 2005

-0.185

-0.232

-0.0658

[0.230]

[0.230]

[0.0228]***

Year 2006

-1.495

-1.514

-0.222

[0.230]***

[0.230]***

[0.0228]***

Subject Matter2

-1.919

-0.246

[1.433]

[0.142]*

Subject Matter3

0.129

0.0532

[1.128]

[0.112]

Subject Matter4

-0.0417

0.0418

[1.507]

[0.149]

Subject Matter5

1.243

0.142

[0.520]**

[0.0516]***

Subject Matter6

0.215

0.121

[0.851]

[0.0844]

Subject Matter7

1.875

0.368

[0.665]***

[0.0660]***

Subject Matter8

0.718

0.154

[1.549]

[0.154]

Subject Matter9

0.119

0.0466

[0.840]

[0.0833]

Subject Matter10

1.782

0.369

[1.210]

[0.120]***

Subject Matter11

0.879

0.209

[0.593]

[0.0589]***

Subject Matter12

1.988

0.382

[0.932]**

[0.0925]***

Subject Matter13

0.636

0.141

[0.557]

[0.0553]**

Subject Matter14

0.564

0.11

[0.881]

[0.0874]

Subject Matter15

-0.544

-0.026

[0.614]

[0.0609]

Subject Matter16

0.743

0.0865

[0.588]

[0.0583]

Subject Matter17

-0.683

-0.067

[1.183]

[0.117]

Subject Matter18

-0.849

-0.0783

[0.951]

[0.0944]

Subject Matter19

-0.0995

-0.00151

[0.697]

[0.0691]

Subject Matter20

1.006

0.106

[0.641]

[0.0636]*

Subject Matter21

3.582

0.528

[0.980]***

[0.0972]***

Constant

5.978

6.635

5.892

-0.01

[1.057]***

[1.065]***

[1.174]***

[0.116]

N

11679

11679

11674

11674

R-sq

0.028

0.032

0.037

0.02

Standard errors in brackets

* p < 0.10

** p < 0.05

*** p < 0.01

Table B. Law Review Citations per Case

(1)

(2)

(3)

(4)

Law Reviews

Normalized Law Reviews

Randolph (DC)

5.675

5.559

5.611

-0.0114

[1.194]***

[1.190]***

[1.184]***

[0.159]

Birch (11)

5.475

5.344

5.411

-0.0175

[1.260]***

[1.255]***

[1.245]***

[0.167]

Thomas (9)

3.945

3.75

3.592

-0.0556

[1.267]***

[1.263]***

[1.252]***

[0.168]

Katzmann (2)

2.99

2.96

2.525

-0.0843

[1.395]**

[1.390]**

[1.377]*

[0.184]

Wilkins (4)

2.958

2.737

2.837

-0.048

[1.282]**

[1.277]**

[1.265]**

[0.170]

Wesley (2)

2.1

2.076

2.076

-0.0135

[1.407]

[1.401]

[1.388]

[0.186]

Scirica (3)

2.057

1.758

1.58

-0.0966

[1.475]

[1.469]

[1.456]

[0.195]

Reinhardt (9)

1.548

1.453

1.622

0.0125

[1.149]

[1.145]

[1.135]

[0.152]

Hull (11)

1.517

1.548

1.688

0.0133

[1.460]

[1.454]

[1.442]

[0.193]

Fisher (9)

1.165

0.985

1.008

-0.0312

[1.184]

[1.180]

[1.169]

[0.157]

Schroeder (9)

0.87

0.642

0.1

-0.128

[1.446]

[1.440]

[1.428]

[0.191]

Paez (9)

0.409

0.26

0.357

-0.0116

[1.332]

[1.327]

[1.315]

[0.176]

Ambro (3)

0.353

0.426

0.635

0.0469

[1.107]

[1.103]

[1.091]

[0.146]

Sack (2)

0.271

0.277

0.215

-0.0124

[1.166]

[1.162]

[1.149]

[0.154]

Ginsburg (DC)

0.244

0.0729

0.581

0.0559

[1.166]

[1.162]

[1.156]

[0.155]

Sentelle (DC)

0.22

0.0594

0.688

0.0809

[1.175]

[1.171]

[1.171]

[0.157]

Straub (2)

0.209

0.142

0.135

-0.019

[1.342]

[1.337]

[1.323]

[0.177]

King (5)

0.138

0.0195

0.15

-0.00312

[1.205]

[1.201]

[1.189]

[0.159]

Luttig (4)

0.0746

-0.161

-0.0869

-0.0335

[1.240]

[1.236]

[1.224]

[0.164]

Anderson (11)

0.0643

0.0154

-0.136

-0.0344

[1.602]

[1.596]

[1.580]

[0.212]

Sutton (6)

0.0217

0.0319

-0.1

-0.0231

[1.126]

[1.122]

[1.111]

[0.149]

Cabranes (2)

-0.0739

-0.22

-0.0279

-0.00743

[1.097]

[1.094]

[1.082]

[0.145]

Edmondson (11)

-0.2

-0.572

-0.482

-0.0647

[2.467]

[2.459]

[2.433]

[0.326]

Marcus (11)

-0.203

-0.159

-0.0939

0.00438

[1.200]

[1.195]

[1.190]

[0.159]

Tjoflat (11)

-0.275

-0.517

-0.294

-0.0263

[1.170]

[1.166]

[1.158]

[0.155]

Raggi (2)

-0.343

-0.477

-0.394

-0.0268

[1.282]

[1.277]

[1.264]

[0.169]

Motz (4)

-0.4

-0.529

-0.637

-0.0523

[1.166]

[1.162]

[1.153]

[0.155]

Wilkinson (4)

-0.4

-0.504

-0.309

0.00723

[1.134]

[1.130]

[1.119]

[0.150]

Calabresi (2)

-0.442

-0.45

-0.288

0.026

[1.175]

[1.171]

[1.159]

[0.155]

Lipez (1)

-0.474

-0.553

-0.425

0.00178

[1.006]

[1.002]

[0.992]

[0.133]

McKeown (9)

-0.491

-0.55

-1.302

-0.125

[1.200]

[1.195]

[1.185]

[0.159]

Wardlaw (9)

-0.498

-0.546

-0.479

0.0116

[1.297]

[1.293]

[1.281]

[0.172]

O’Scannlain (9)

-0.502

-0.526

-0.667

-0.0183

[1.110]

[1.106]

[1.095]

[0.147]

Smith (3)

-0.509

-0.52

-0.265

0.0384

[1.342]

[1.337]

[1.323]

[0.177]

Jones (5)

-0.543

-0.719

-0.728

-0.0448

[1.149]

[1.145]

[1.133]

[0.152]

Wilson (11)

-0.562

-0.567

-0.762

-0.05

[1.446]

[1.440]

[1.430]

[0.192]

Fuentes (3)

-0.563

-0.517

-0.465

0.000937

[1.314]

[1.309]

[1.296]

[0.174]

Posner (7)

-0.581

-0.672

-0.384

0.0288

[0.899]

[0.895]

[0.887]

[0.119]

Barry (3)

-0.638

-0.466

-0.111

0.0976

[1.794]

[1.788]

[1.769]

[0.237]

Carnes (11)

-0.65

-0.604

-0.605

-0.00965

[1.170]

[1.166]

[1.156]

[0.155]

Kleinfeld (9)

-0.716

-0.868

-1.071

-0.0611

[1.253]

[1.249]

[1.236]

[0.166]

Clement (5)

-0.733

-0.85

-0.761

-0.0146

[1.134]

[1.130]

[1.118]

[0.150]

Wiener (5)

-0.739

-0.85

-0.569

0.0263

[1.222]

[1.217]

[1.205]

[0.161]

Davis (5)

-0.819

-0.889

-0.659

0.00993

[1.222]

[1.217]

[1.207]

[0.162]

Michael (4)

-0.873

-1.002

-0.817

0.00769

[1.267]

[1.262]

[1.250]

[0.168]

Pregerson (9)

-0.907

-0.915

-1.154

-0.0293

[1.175]

[1.171]

[1.160]

[0.155]

Easterbrook (7)

-0.933

-1.035

-0.83

0.00521

[0.915]

[0.912]

[0.903]

[0.121]

Hawkins (9)

-0.943

-1.198

-1.039

-0.0281

[1.475]

[1.469]

[1.456]

[0.195]

Batchelder (6)

-0.949

-1.026

-1.042

-0.0251

[1.297]

[1.293]

[1.279]

[0.171]

Gibbons (6)

-0.971

-0.968

-1.125

-0.0276

[1.180]

[1.175]

[1.163]

[0.156]

Shedd (4)

-0.981

-1.107

-0.89

0.00101

[1.372]

[1.367]

[1.353]

[0.181]

Cole (6)

-1.003

-1.166

-1.281

-0.0536

[1.166]

[1.162]

[1.150]

[0.154]

Rogers (DC)

-1.018

-1.09

-0.564

0.0771

[1.107]

[1.103]

[1.102]

[0.148]

Dubina (11)

-1.046

-1.068

-1.093

-0.00119

[1.323]

[1.318]

[1.305]

[0.175]

Fletcher (9)

-1.049

-1.228

-1.629

-0.0896

[1.162]

[1.158]

[1.147]

[0.154]

Rendell (3)

-1.074

-1.198

-1.291

-0.0326

[1.342]

[1.337]

[1.324]

[0.177]

Tallman (9)

-1.083

-1.328

-1.469

-0.0719

[1.234]

[1.229]

[1.217]

[0.163]

Tacha (10)

-1.085

-1.206

-1.066

-0.0168

[1.166]

[1.162]

[1.151]

[0.154]

Black (11)

-1.09

-1.188

-1.123

0.000534

[1.383]

[1.378]

[1.365]

[0.183]

Pooler (2)

-1.094

-1.135

-0.894

0.0357

[1.170]

[1.166]

[1.154]

[0.155]

Daughtrey (6)

-1.097

-1.101

-1.02

0.0208

[1.506]

[1.501]

[1.486]

[0.199]

Smith (5)

-1.116

-1.078

-0.989

0.0167

[1.040]

[1.036]

[1.026]

[0.137]

Higginbotham (5)

-1.137

-1.084

-0.786

0.0547

[1.137]

[1.133]

[1.122]

[0.150]

Murphy (10)

-1.141

-1.213

-1.241

-0.0302

[1.134]

[1.130]

[1.120]

[0.150]

Jacobs (2)

-1.211

-1.228

-1.228

0.00745

[1.103]

[1.099]

[1.089]

[0.146]

Boggs (6)

-1.212

-1.392

-1.536

-0.0579

[1.184]

[1.180]

[1.169]

[0.157]

Selya (1)

-1.223

-1.355

-1.243

-0.00828

[0.978]

[0.974]

[0.964]

[0.129]

Berzon (9)

-1.235

-1.311

-1.455

-0.0375

[1.120]

[1.115]

[1.104]

[0.148]

Gould (9)

-1.235

-1.377

-1.529

-0.0636

[1.083]

[1.079]

[1.070]

[0.143]

Cook (6)

-1.286

-1.415

-1.118

0.014

[1.362]

[1.357]

[1.343]

[0.180]

Jolly (5)

-1.373

-1.547

-1.314

0.00384

[1.157]

[1.153]

[1.142]

[0.153]

Benavides (5)

-1.4

-1.309

-1.242

0.0225

[1.126]

[1.122]

[1.111]

[0.149]

Traxler (4)

-1.4

-1.489

-1.726

-0.0483

[1.407]

[1.401]

[1.387]

[0.186]

Graber (9)

-1.415

-1.529

-1.546

-0.0167

[1.200]

[1.195]

[1.183]

[0.159]

Wood (7)

-1.461

-1.563

-1.328

0.0137

[0.971]

[0.968]

[0.958]

[0.128]

Barkett (11)

-1.47

-1.668

-1.478

-0.0088

[1.253]

[1.249]

[1.236]

[0.166]

Boudin (1)

-1.494

-1.581

-1.501

-0.00609

[1.020]

[1.016]

[1.006]

[0.135]

Kozinski (9)

-1.498

-1.573

-1.408

0.00837

[1.228]

[1.223]

[1.211]

[0.162]

King (4)

-1.514

-1.577

-1.68

-0.0304

[1.180]

[1.175]

[1.164]

[0.156]

DeMoss (5)

-1.532

-1.822

-1.522

-0.0105

[1.153]

[1.149]

[1.139]

[0.153]

Bybee (9)

-1.558

-1.546

-1.704

-0.0225

[1.253]

[1.248]

[1.236]

[0.166]

Garza (5)

-1.561

-1.531

-1.263

0.0328

[1.048]

[1.044]

[1.037]

[0.139]

Williams (4)

-1.576

-1.533

-1.168

0.0614

[1.297]

[1.293]

[1.281]

[0.172]

Barksdale (5)

-1.605

-1.699

-1.631

-0.0299

[1.362]

[1.357]

[1.345]

[0.180]

Niemeyer (4)

-1.608

-1.69

-1.677

-0.00806

[1.149]

[1.145]

[1.134]

[0.152]

McConnell (10)

-1.639

-1.569

-1.489

0.0156

[1.038]

[1.034]

[1.025]

[0.137]

Rawlinson (9)

-1.65

-1.909

-2.345

-0.11

[1.323]

[1.318]

[1.306]*

[0.175]

Rymer (9)

-1.659

-1.881

-2.221

-0.0868

[1.274]

[1.270]

[1.258]*

[0.169]

Henry (10)

-1.666

-1.847

-1.875

-0.0475

[1.210]

[1.206]

[1.196]

[0.160]

Parker (2)

-1.7

-1.72

-1.587

0.00934

[1.234]

[1.229]

[1.217]

[0.163]

Lynch (1)

-1.726

-1.858

-1.715

0.00254

[0.929]*

[0.926]**

[0.917]*

[0.123]

Martin (6)

-1.745

-1.848

-1.825

-0.0137

[0.997]*

[0.994]*

[0.983]*

[0.132]

Sloviter (3)

-1.746

-1.87

-1.703

-0.00727

[1.145]

[1.141]

[1.129]

[0.151]

Clifton (9)

-1.855

-2.066

-2.067

-0.0396

[1.362]

[1.357]

[1.343]

[0.180]

Kelly (10)

-1.866

-1.966

-1.755

0.0065

[1.166]

[1.162]*

[1.151]

[0.154]

Clay (6)

-1.877

-1.885

-1.733

0.0121

[1.012]*

[1.008]*

[0.998]*

[0.134]

Moore (6)

-1.923

-1.866

-2.023

-0.0193

[1.054]*

[1.050]*

[1.040]*

[0.139]

Silverman (9)

-1.929

-2.139

-2.584

-0.0952

[1.490]

[1.485]

[1.470]*

[0.197]

Ripple (7)

-1.983

-2.072

-1.899

-0.00146

[0.972]**

[0.969]**

[0.961]**

[0.129]

Manion (7)

-1.986

-2.06

-1.742

0.0277

[1.040]*

[1.036]**

[1.027]*

[0.138]

Loken (8)

-1.987

-1.999

-1.997

-0.00145

[0.975]**

[0.972]**

[0.963]**

[0.129]

Tymkovich (10)

-2.007

-2.015

-1.968

-0.00444

[1.107]*

[1.102]*

[1.092]*

[0.146]

Arnold (8)

-2.016

-2.072

-1.947

0.000588

[0.976]**

[0.973]**

[0.966]**

[0.129]

Fisher (3)

-2.051

-1.876

-1.934

0.0277

[1.372]

[1.367]

[1.353]

[0.181]

Evans (7)

-2.082

-2.14

-1.947

0.00995

[1.017]**

[1.013]**

[1.004]*

[0.135]

Lucero (10)

-2.172

-2.279

-2.083

0.000919

[1.097]**

[1.093]**

[1.083]*

[0.145]

Garland (DC)

-2.178

-2.3

-1.63

0.0871

[1.216]*

[1.212]*

[1.204]

[0.161]

Murphy (8)

-2.23

-2.25

-2.107

0.00238

[1.007]**

[1.004]**

[0.995]**

[0.133]

Stewart (5)

-2.257

-2.195

-1.968

0.0474

[1.081]**

[1.077]**

[1.067]*

[0.143]

Duncan (4)

-2.271

-2.491

-2.612

-0.0542

[1.542]

[1.536]

[1.521]*

[0.204]

McKee (3)

-2.272

-2.696

-2.515

-0.054

[1.332]*

[1.328]**

[1.314]*

[0.176]

Gilman (6)

-2.274

-2.271

-2.117

0.0184

[0.976]**

[0.973]**

[0.963]**

[0.129]

O’Brien (10)

-2.281

-2.231

-2.214

0.00113

[1.383]*

[1.378]

[1.366]

[0.183]

Rogers (6)

-2.282

-2.378

-2.385

-0.0201

[1.052]**

[1.048]**

[1.038]**

[0.139]

Torruella (1)

-2.333

-2.403

-2.321

-0.0107

[0.970]**

[0.966]**

[0.957]**

[0.128]

Henderson (DC)

-2.343

-2.443

-2.016

0.0648

[1.110]**

[1.106]**

[1.107]*

[0.148]

Tatel (DC)

-2.373

-2.573

-2.211

0.0305

[1.162]**

[1.157]**

[1.152]*

[0.154]

Hartz (10)

-2.416

-2.504

-2.355

0.0000778

[1.018]**

[1.015]**

[1.005]**

[0.135]

Briscoe (10)

-2.449

-2.502

-2.438

-0.00251

[1.134]**

[1.130]**

[1.119]**

[0.150]

Williams (7)

-2.456

-2.605

-2.267

0.0177

[1.025]**

[1.022]**

[1.012]**

[0.136]

Colloton (8)

-2.476

-2.486

-2.241

0.0271

[0.964]**

[0.960]***

[0.952]**

[0.128]

Rovner (7)

-2.504

-2.689

-2.335

0.0126

[0.971]***

[0.968]***

[0.959]**

[0.129]

Prado (5)

-2.517

-2.613

-2.451

0.0133

[1.149]**

[1.145]**

[1.134]**

[0.152]

Howard (1)

-2.613

-2.667

-2.557

-0.0081

[1.029]**

[1.025]***

[1.014]**

[0.136]

Smith (8)

-2.624

-2.712

-2.536

-0.00221

[0.943]***

[0.939]***

[0.931]***

[0.125]

Flaum (7)

-2.662

-2.786

-2.47

0.0209

[0.993]***

[0.990]***

[0.982]**

[0.132]

Gregory (4)

-2.666

-2.879

-2.69

-0.00819

[1.210]**

[1.206]**

[1.194]**

[0.160]

Bye (8)

-2.691

-2.826

-2.74

-0.015

[0.948]***

[0.945]***

[0.936]***

[0.125]

Kanne (7)

-2.717

-2.793

-2.739

-0.0157

[0.948]***

[0.945]***

[0.936]***

[0.125]

Riley (8)

-2.718

-2.85

-2.64

0.0049

[0.941]***

[0.938]***

[0.931]***

[0.125]

Wollman (8)

-2.724

-2.792

-2.703

-0.00513

[0.965]***

[0.961]***

[0.953]***

[0.128]

Callahan (9)

-2.758

-2.823

-2.916

-0.0185

[1.282]**

[1.277]**

[1.265]**

[0.169]

Bea (9)

-2.796

-2.792

-2.885

-0.00788

[1.282]**

[1.277]**

[1.265]**

[0.169]

Melloy (8)

-2.949

-3.062

-2.848

0.00827

[0.943]***

[0.940]***

[0.932]***

[0.125]

Dennis (5)

-3.364

-3.367

-3.165

0.0295

[1.126]***

[1.123]***

[1.111]***

[0.149]

Year 2005

-0.524

-0.54

-0.0892

[0.169]***

[0.168]***

[0.0225]***

Year 2006

-1.552

-1.521

-0.289

[0.169]***

[0.168]***

[0.0225]***

SubjectMatter2

3.223

0.615

[1.045]***

[0.140]***

SubjectMatter3

1.495

0.379

[0.823]*

[0.110]***

SubjectMatter4

3.911

0.734

[1.100]***

[0.147]***

SubjectMatter5

1.395

0.296

[0.380]***

[0.0509]***

SubjectMatter6

3.998

0.674

[0.621]***

[0.0832]***

SubjectMatter7

1.13

0.231

[0.485]**

[0.0650]***

SubjectMatter8

3.191

0.49

[1.130]***

[0.151]***

SubjectMatter9

2.984

0.568

[0.613]***

[0.0821]***

SubjectMatter10

0.179

0.0643

[0.883]

[0.118]

SubjectMatter11

0.479

0.109

[0.433]

[0.0580]*

SubjectMatter12

8.388

1.214

[0.680]***

[0.0911]***

SubjectMatter13

0.637

0.124

[0.407]

[0.0545]**

SubjectMatter14

1.36

0.29

[0.643]**

[0.0861]***

SubjectMatter15

0.216

0.0352

[0.448]

[0.0601]

SubjectMatter16

2.142

0.317

[0.429]***

[0.0575]***

SubjectMatter17

-0.302

-0.0106

[0.863]

[0.116]

SubjectMatter18

0.901

0.187

[0.694]

[0.0930]**

SubjectMatter19

0.413

0.105

[0.508]

[0.0681]

SubjectMatter20

0.71

0.119

[0.468]

[0.0627]*

SubjectMatter21

2.406

0.419

[0.715]***

[0.0958]***

Constant

4.4

5.19

3.824

-0.106

[0.780]***

[0.785]***

[0.857]***

[0.115]

N

11679

11679

11674

11674

R-sq

0.032

0.039

0.063

0.047

Standard errors in brackets

* p < 0.10

** p < 0.05

*** p < 0.01

Appendix B

Subject-Matter Codings

Administrative Law—1

Review of agency decision making (not in another subject-matter category), Administrative Procedure Act, Federal Communications Commission rates, Federal Energy Regulatory Commission rates, Freedom of Information Act, Social Security entitlement, and Medicare.

Campaign Finance—2

Campaign finance and any election-related issue.

Capital Punishment—3

Capital-punishment-related actions.

Church and State—4

Establishment Clause; Pledge of Allegiance; funding for private, religious schools; prayer in school; Ten Commandments; etc.

Criminal*—5

Sentencing guidelines, prisoners’ rights, drugs/controlled substances, attorney–client privilege in criminal context, grand-jury-related, Racketeer Influenced and Corrupt Organizations, search and seizure (Fourth Amendment), Prison Litigation Reform Act, etc.

*Excludes capital punishment cases.

Environment—6

National Park Service; Clean Air Act; Comprehensive Environmental Response, Compensation, and Liability Act; Superfund; National Forest Management Act; Endangered Species Act; Environmental Protection Act; etc.

Federal Business Law—7

Bankruptcy, antitrust, federal banking laws, unfair trade practices, Federal Debt Collection Procedure Act, Fair Debt Collection Practices Act, Truth in Lending Act, deceptive advertising under the Lanham Act, Magnuson–Moss Warranty Act, etc.

Federalism—8

State rights, federal preemption, and Commerce Clause power.

First Amendment*—9

First Amendment-related issues.

*Excludes church and state issues.

Government Actions—10

Sovereign immunity, False Claims Act, and government forfeiture action.

Immigration—11

Immigration-related issues.

Intellectual Property—12

Patents, copyright, trademarks, and Lanham Act (trademark-related actions).

Labor—13

Employment issues (excluding employment contractual disputes), Employee Retirement Income Security Act, National Labor Relations Act, Occupational Safety and Health Act, Fair Labor Standards Act, wrongful discharge, Labor–Management Relations Act, Family and Medical Leave Act, employee benefits, worker’s compensation claims, retaliatory-discharge claims, etc.

Other—14

Indian law, maritime law, and implicit private rights of actions.

Private Law—15

Contracts, insurance, private arbitration, creditor v. debtor, lessor v. lessee, usury laws, franchisee v. franchisor, employment contractual disputes, corporate law, and piercing the corporate veil.

Rights*—16

Race discrimination, sex discrimination, affirmative action, civil rights, age discrimination, privacy, abortion, other individual rights, and writs of habeas corpus.

*Excludes employment and Eighth Amendment capital punishment.

Takings and Property—17

Takings claims, zoning issues, and property rights.

Tax—18

Internal Revenue Code and other tax-related matters.

Torts—19

Federal Tort Claims Act, medical malpractice, products liability, wrongful death, libel, etc.

Courts—20

Cases in which the court’s analysis is mostly or wholly absorbed with a discussion of civil procedure. Focus is on issues relating to summary judgment, removal, venue, etc.

Securities Law—21

Securities-related issues.

Footnotes

Professor of Law and Co-Director of the Center for the Study of Law, Race, and Politics, Duke University School of Law.Daniel L. Chen is Assistant Professor of Law, Duke University School of Law.Mitu Gulati is Professor of Law and Co-Director of the Center for the Study of Law, Race, and Politics, Duke University School of Law.

1Letter from Laurence H. Tribe, Carl M. Loeb University Professor, Harvard Law Sch., to Barack Obama, U.S. President (May 4, 2009), available at http://www.eppc.org/docLib/20101028_tribeletter.pdf. For a discussion of the Tribe letter, see Ed Whelan, Tribe to Obama: Sotomayor Is “Not Nearly as Smart as She Seems to Think She Is,Nat’l Rev. Online (Oct. 28, 2010, 9:42 AM), http://www.nationalreview.com/bench-memos/251301/tribe-obama-sotomayor-not-nearly-smart-she-seems-think-she-ed-whelan.

2 See Countdown with Keith Olberman (MSNBC television broadcast May 26, 2009), available at http://www.msnbc.msn.com/id/3036677/vp/30950928#30950928 (interviewing Jonathan Turley, Professor, George Washington University); P.J. Gladnick, Liberal Jonathan Turley: Sotomayor Lacks Intellectual Depth, NewsBusters (May 27, 2009), http://newsbusters.org/blogs/p-j-gladnick/2009/05/27/liberal-jonathan-turley-sotomayor-lacks-intellectual-depth (quoting Turley as characterizing Sotomayor as lacking “intellectual depth” but describing Diane Wood as “blazingly brilliant”).

3Jeffrey Rosen, The Case Against Sotomayor: Indictments of Obama’s Front-Runner to Replace Souter, New Republic (May 4, 2009, 12:00 AM), http://www.tnr.com/article/politics/the-case-against-sotomayor.

4 Id.

5 Id. (quoting a former Second Circuit clerk) (internal quotation mark omitted).

6 Id.

7 See, e.g., Richard Cohen, Op-Ed., The So-So Sotomayor, Wash. Post, July 21, 2009, at A17.

8 See Dana Milbank, Op-Ed., Washington Sketch: But Will She Suit Up with the Washington Nine?, Wash. Post, May 27, 2009, at A2; see also Ilya Shapiro, Commentary: Sotomayor Pick Not Based on Merit, CNN (May 27, 2009), http://articles.cnn.com/2009-05-27/politics/shapiro.scotus.identity_1_judge-sotomayor-hispanic-supreme-court-sonia-sotomayor?_s=PM:POLITICS.

9 See Milbank, supra note 8.

10 Sharon Johnson, Wood, Kagan Are on High Court Short List, Again, Women’s eNews (Apr. 25, 2010), http://womensenews.org/story/in-the-courts/100423/wood-kagan-are-high-court-short-list-again; see also Milbank, supra note 8; Shapiro, supra note 8.

11 See Kristina Moore, Over 1000 Law Professors Join Letter Endorsing Sotomayor, SCOTUSblog (July 8, 2009, 1:18 PM), http://www.scotusblog.com/2009/07/over-1000-law-professors-join-letter-endorsing-sotomayor/; see also Cohen, supra note 7; Milbank, supra note 8.

12Press Release, White House, Background on Judge Sonia Sotomayor (May 26, 2009), http://www.whitehouse.gov/the_press_office/Background-on-Judge-Sonia-Sotomayor/.

13 See Joe Conason, Sonia Sotomayor Is Not Clarence Thomas, Salon (May 29, 2009, 6:24 AM), http://www.salon.com/2009/05/29/clarence_thomas_2/.

14 See Shapiro, supra note 8.

15 See id.

16Press Release, White House, supra note 12.

17Lee Epstein et al., The Norm of Prior Judicial Experience and Its Consequences for Career Diversity on the U.S. Supreme Court, 91 Calif. L. Rev. 903, 908–17 (2003).

18 See Monica Youn, Brennan Ctr. for Justice, Judge Sotomayor’s Record in Constitutional Cases, at v–vi (2009); Corey Rayburn Yung, Flexing Judicial Muscle: An Empirical Study of Judicial Activism in the Federal Courts, 105 Nw. U. L. Rev. 1, 42–43 (2011); Marcia Coyle, No Activist Judge, Says New Book, Nat’l L.J. (June 8, 2009), http://www.law.com/jsp/nlj/legaltimes/PubArticleFriendlyLT.jsp?id=1202431249312&slreturn=1.

19 See Youn, supra note 18, at v–vi; Yung, supra note 18, at 42–43; Coyle, supra note 18.

20 See Eric Posner, Judge Sonia Sotomayor: What the Data Show, Volokh Conspiracy (May 13, 2009, 11:40 AM), http://volokh.com/posts/1242229209.shtml [hereinafter Posner, Judge Sonia Sotomayor]; Eric Posner, Judge Sotomayor: More Data, and a New Conclusion, Volokh Conspiracy (May 27, 2009, 11:50 PM), http://volokh.com/archives/archive_2009_05_24-2009_05_30.shtml#1243482653 [hereinafter Posner, Judge Sotomayor].

21 See Posner, Judge Sonia Sotomayor, supra note 20; Posner, Judge Sotomayor, supra note 20. Posner’s analysis was done on the basis of data that were collected jointly with Stephen Choi and one of us, G. Mitu Gulati. See Posner, Judge Sonia Sotomayor, supra note 20; Posner, Judge Sotomayor, supra note 20. For a report on that analysis, see Assessing Sotomayor’s Influence, N.Y. Times, http://www.nytimes.com/interactive/2009/05/28/us/politics/0529-judge-graphic.html (last visited July 5, 2012).

22For interested readers, these measures have been debated in a number of symposia. See, e.g., Symposium, Empirical Measures of Judicial Performance, 32 Fla. St. U. L. Rev. 1001 (2005); Symposium, Measuring Judges and Justices, 58 Duke L.J. 1173 (2009); Symposium, The Impact of Direct Democracy, 78 S. Cal. L. Rev. 835 (2005).

23 See Scott Baker, Should We Pay Federal Judges More?, 88 B.U. L. Rev. 63, 77–85 (2008); Stephen J. Choi & G. Mitu Gulati, Choosing the Next Supreme Court Justice: An Empirical Ranking of Judge Performance, 78 S. Cal. L. Rev. 23, 32–34 (2004); Jake Dear & Edward W. Jessen, “Followed Rates” and Leading State Cases, 1940–2005, 41 U.C. Davis L. Rev. 683, 685–89 (2007); William M. Landes et al., Judicial Influence: A Citation Analysis of Federal Courts of Appeals Judges, 27 J. Legal Stud. 271, 271–76 (1998); Russell Smyth & Mita Bhattacharya, What Determines Judicial Prestige? An Empirical Analysis for Judges of the Federal Court of Australia, 5 Am. L. & Econ. Rev. 233, 233–34 (2003).

24 See, e.g., Marin K. Levy et al., The Costs of Judging Judges by the Numbers, 28 Yale L. & Pol’y Rev. 313, 314–15 (2010); William P. Marshall, Be Careful What You Wish for: The Problems with Using Empirical Rankings to Select Supreme Court Justices, 78 S. Cal. L. Rev. 119 (2004). For tests of the measures, see Stephen J. Choi & G. Mitu Gulati, Bias in Judicial Citations: A Window into the Behavior of Judges?, 37 J. Legal Stud. 87 (2008); and Stephen J. Choi, G. Mitu Gulati & Eric A. Posner, How Well Do Measures of Ability Predict Judicial Performance?: A Case Study Using Securities Class Actions (Univ. of Chi. Law Sch., Olin Research Paper No. 519, 2011), available at http://papers.ssrn.com/sol3/papers.cfm?abstract_id=1596910.

25 See Frank B. Cross & Stefanie Lindquist, Judging the Judges, 58 Duke L.J. 1383 (2009); Dear & Jessen, supra note 23; Daniel A. Farber, Supreme Court Selection and Measures of Past Judicial Performance, 32 Fla. St. U. L. Rev. 1175 (2005); Smyth & Bhattacharya, supra note 23.

26 Contributors: Anthony Lane, New Yorker, http://www.newyorker.com/magazine/bios/anthony_lane/search?contributorName=anthony%20lane (last visited July 5, 2012).

27 Manohla Dargis, N.Y. Times, http://movies.nytimes.com/movies/critics/Manohla-Dargis (last visited July 5, 2012).

28 Rotten Tomatoes, http://www.rottentomatoes.com/ (last visited July 5, 2012).

29 Fandango, http://www.fandango.com/ (last visited July 5, 2012).

30 See Press Release, White House, supra note 12.

31M. Wood, D.C. Circuit Has Special History Among Appeals Courts, Roberts Says, Va. L. (Apr. 26, 2005), http://www.law.virginia.edu/html/news/2005_spr/roberts.htm.

32 See Anna O. Law, The Immigration Battle in American Courts 28 (2010).

33The list of subject areas is reported infra Appendix B.

34There are 179 active positions on the federal courts of appeals. All of those positions, however, are not necessarily filled at any given time. How the Federal Courts Are Organized, Fed. Jud. Center, http://www.fjc.gov/federal/courts.nsf/autoframe?OpenForm&nav=menu3c&page=/federal/courts.nsf/page/A783011AF949B6BF85256B35004AD214?opendocument (last visited July 5, 2012).

35The assumption that senior judges do less work does not hold uniformly (in the course of this study, we found indications that a few senior judges were producing as much, if not more, than some of their active colleagues).

36On the trend toward appointing federal appeals judges to the High Court, see Epstein et al., supra note 17, at 908–17.

37 See Harry T. Edwards, The Growing Disjunction Between Legal Education and the Legal Profession, 91 Mich. L. Rev. 34, 34–57 (1992).

38 See id.

39We are making an approximation here because Sotomayor’s name was being actively discussed as a possible candidate for the Court at least as early as October 2008. See Sarah Johnson, Granholm Placed on Short List for Supreme Court Nomination, Cent. Mich. Life (Oct. 17, 2008, 12:00 AM), http://www.cm-life.com/2008/10/17/granholmplacedonshortlistforsupremecourtnomination/ (discussing Sonia Sotomayor as a potential Supreme Court candidate); Justin Jouvenal, Ten Picks for Obama’s Supreme Court, Salon (Nov. 19, 2008, 12:50 AM), http://www.salon.com/news/feature/2008/11/18/supreme_court.

40 See Dave Hoffman, Reversal Rates, Reconsidered, Concurring Opinions, (Sept. 30, 2011, 12:21 PM), http://www.concurringopinions.com/archives/2011/09/reversal-rates-reconsidered.html; Dave Hoffman, What Should a Judge’s Reversal Rate Be? Concurring Opinions, (May 26, 2009, 3:20 PM), http://www.concurringopinions.com/archives/2009/05/what-should-a-judges-reversal-rate-be.html.

41 See Stephen Dinan, Supreme Court Overturned 60% of Sotomayor’s Rulings, Wash. Times, May 27, 2009, at A1.

42Wash. Times, CQ Uncritically Report Criticism that Sotomayor’s Supreme Court Reversal Rate Is “High,Media Matters for Am. (May 27, 2009, 4:09 PM), http://mediamatters.org/research/200905270038 (quoting Wendy Long in an excerpt from an article in Congressional Quarterly Today) (internal quotation marks omitted).

43 See, e.g., Sam Stein, Sotomayor’s Reversals No Different than Souter or Alito, Huffington Post (May 25, 2011, 2:25 PM), http://www.huffingtonpost.com/2009/05/27/sotomayors-reversals-no-d_n_208362.html.

44 See Rosen, supra note 3.

45 See Milbank, supra note 8; Shapiro, supra note 8.

46 See, e.g., Erica S. Weisgerber, Note, Unpublished Opinions: A Convenient Means to an Unconstitutional End, 97 Geo. L.J. 621, 625 (2009).

47See generally Mitu Gulati & C.M.A. McCauliff, On Not Making Law, Law & Contemp. Probs., Summer 1998, at 157 (detailing the considerations that may effect a judge’s decision to publish an opinion).

48 Id.

49Density scales the height of the bars so that the sum of their areas equals 1.

50 See Jouvenal, supra note 39.

51 See Stephen J. Choi, Mitu Gulati & Eric A. Posner, What Do Federal District Judges Want? an Analysis of Publications, Citations, and Reversals, J.L. Econ. & Org. 1, 7 n.13 (Jan. 31, 2011), http://jleo.oxfordjournals.org/content/early/2011/01/31/jleo.ewq020.full?sid=400f5b79-da6f-404a-9af7-2b32af327af9.

52 E.g., Landes et al., supra note 23.

53We also add in citations from bankruptcy and tax courts.

54Other measures are available on request.

55One might expect that these measures should be roughly twice the citation count for when judges are authors of the opinions (after all, judges write opinions on only about a third of the cases that they decide). They are not. The reason has to do with the fact that we restrict our analysis to the 136 active judges who authored opinions throughout the period from 2004 to 2006. Many of the panels also have nonwriting judges, such as judges from district courts, senior judges, and judges who were promoted during the timeframe. See generally William M. Richman & William L. Reynolds, Elitism, Expediency, and the New Certiorari: Requiem for the Learned Hand Tradition, 81 Cornell L. Rev. 273, 287 (1996) (discussing the use of visiting judges on appellate court panels).

56 See James J. Brudney et al., Judicial Hostility Toward Labor Unions? Applying the Social Background Model to a Celebrated Concern, 60 Ohio St. L.J. 1675, 1680 (1999) (explaining that prior studies have failed to address significant differences in circuit court cultures); Choi & Gulati, supra note 23, at 44–45.

57 See Choi & Gulati, supra note 23, at 44–45.

58 See John R. Lott, Jr., Op-Ed., Pulling Rank, N.Y. Times, Jan. 25, 2006, at A1; Orin Kerr, Rates of Unpublished Opinions in the Different Circuits—and Especially the Fourth Circuit, Volokh Conspiracy (Sept. 8, 2011, 12:53 PM), http://volokh.com/2011/09/08/rates-of-unpublished-opinions-in-the-different-circuits-and-especially-the-fourth-circuit/ (listing the Seventh Circuit with the lowest rate of unpublished opinions).

59 E.g., NML Capital v. Republic of Argentina, 621 F.3d 230 (2d Cir. 2010).

60Because citations are calculated for all opinions from the period from 2004 until 2006, tallied from the date of publication up to January 1, 2009, opinions written in 2004 will garner more citations than those written in 2006, other things equal.

61Other regressions are available on request.

62A dummy indicator is equal to one if the observation belongs to that judge and zero otherwise.

63The issue of outliers obviously does not apply to the measure of published opinions.

64These results are available from the authors.

65To be specific, we were told that we were “damning her with faint praise” and were doing more harm than good by bringing up the issue of her merit again.

66Wood also performed at a high level in a prior study examining a time period roughly five years prior. See Choi & Gulati, supra note 23, at 68–69.

67 See John McCormick & Jeff Coe, Driven Judge Has Music in Her Heart, Chi. Trib., May 24, 2009, at C6; David Savage, Obama Speaks with Diane Wood Ahead of Supreme Court Pick, Chi. Trib., May 5, 2010, at C10.

68 See Choi & Gulati, supra note 23, at 83.

69 See id. at 31 (narrowing the period to the years from 1998 until 2000). Unlike in our current study though, Justice Alito’s performance was not the primary subject of the prior study. See id.

70 See id. at 113–15. Our current sample looks at a broader set of judges than the prior study did, because we look at all active judges and not just the ones under the age of sixty-five. If we were to assume that the additional judges would have all performed in the bottom half of the distribution, then Alito would be roughly near the top 10% of all judges (16 out of 136). Another issue to note in the Alito comparison is that Alito’s scores were particularly high on a category that we did not estimate for this project: independence. Id. at 69. Independence in the prior study was measured as a function of dissents against other judges with the same party affiliation (the overall measure being normalized for the relative numbers of judges from each party on the circuit in question). See id. at 64.

71 See David D. Kirkpatrick, Conservatives Scrambling to Prepare for a Tough Fight, N.Y. Times, Nov. 1, 2005, at A23 (noting that Alito’s record on abortion and other contentious issues made for a tough fight in the Senate).

72We should point out that our analysis cannot completely separate individual merit from a possible diversity effect. Perhaps being on the Second Circuit, Sotomayor got highly cited because of her “different” perspective vis-à-vis her colleagues. Nevertheless, a clean measure of individual merit is not necessary to ask whether Sotomayor was as meritorious as other candidate judges, because she would bring her diversity effect to the Supreme Court as well.