In the next two posts, we’re reviewing Justice Corrigan’s voting record.

Since joining the Court, Justice Corrigan has voted to reverse in full in 283 civil cases.  She has cast split votes (affirm in part, reverse/vacate in part – denoted in the chart as “AR” votes) 44 times.  She has voted to affirm in 188 civil cases.  Justice Corrigan’s heaviest year for reversals was 2007 with 30.  Her lightest year for affirm votes was 2020 with only five.  Including both outright reversal and split votes, the outliers are 2006 (32 reverse or AR, 14 affirm), 2007 (34 reverse or AR, 17 affirm), 2010 (22 reverse or AR, 11 affirm), 2011 (23 reverse or AR, 6 affirm), 2012 (18 reverse or AR, 8 affirm), 2015 (24 reverse or AR, 8 affirm) and 2020 (17 reverse or AR, 5 affirm).

Meanwhile, Justice Corrigan has cast 472 votes to affirm in full in criminal cases.  She has cast 106 split votes and voted to reverse 254 times.  Her split votes reached double figures in 2012 (13) and 2014-2016 (10 per year).  The outlier years are 2007 (39 affirm, 21 reverse or AR), 2010 (47 affirm, 26 reverse or AR), 2011 (34 affirm, 17 reverse or AR) and 2018 (30 affirm, 19 reverse or AR).

Join us back here next time as we reach part 4 of our post – how often does Justice Corrigan vote with the majority?

Image courtesy of Flickr by Dennis Jarvis (no changes).

Last time, we began a six-part post reviewing the tenure (to date) of Justice Carol Corrigan. This time, we’re reviewing Justice Corrigan’s record in opinion writing.

Through the end of last week, Justice Corrigan has written 83 majority opinions in civil cases.  She has filed only five concurrences and 14 dissents.  Her heaviest year for dissents was 2007 with 3; she has not written a civil dissent since 2017.  Her heaviest years for majority opinions were 2007 and 2017 with 9 each and 2019 with 8.  Her lightest full year was 2010, when she wrote only one.

Justice Corrigan has written 135 majority opinions in criminal, quasi-criminal, juvenile justice and mental health cases.  She has written 11 concurrences and only 16 dissents.  She has never had more than two criminal dissents in a single year.  She filed three concurrences in her first year, 2006.

Justice Corrigan has reached double figures in criminal majority opinions eight times – 2009 (13), 2010, 2011, 2012 and 2019 (12 each) and 2007 and 2008 (10 each).  Her lightest full year was 2006, with three majority opinions.  She has written four so far this year and wrote five each in 2015 and 2016.

Join us back here next time as we continue our review of Justice Corrigan’s tenure.

Image courtesy of Flickr by Ken Lund (no changes).

 

This week, we’ll begin a series of posts reviewing the tenure of each Justice of the Supreme Court.  Similar to our recently completed review of former Justice Cuéllar’s tenure, we’ll devote six parts to each Justice.  Although technically the Chief Justice is always the senior member of the Court, we’ll take the serving Justices in length-of-service order, beginning this week with Justice Carol Corrigan.

Since joining the Court in 2006 (through the end of last week), Justice Corrigan has participated in 554 civil cases.  Her busiest year was 2007 with 53 cases.  She also participated in 47 cases in 2006, 42 in 2009 and 41 in 2017.  Her lightest full year to date was 2014, with 23 cases.

Justice Corrigan has participated in 834 criminal, quasi-criminal, juvenile justice and mental health cases.  Her heaviest year was 2012 with 77 cases.  She participated in 73 cases in 2010 and was in the sixties in 2008 (66), 2009 (61) and 2007 (60).  Her lightest full year to date was 2019 with 41 cases.

Join us back here next time as we continue our review of Justice Corrigan’s tenure.

Image courtesy of Flickr by Giuseppe Milo (no changes).

This time, we’re concluding our six-part post on the tenure of Justice Mariano-Florentino Cuéllar with a look at the subjects of his majority and dissenting opinions in criminal, quasi-criminal, juvenile justice and mental health cases.

Not surprisingly, the most frequent topic of Justice Cuéllar’s majority opinions in criminal cases was death penalty law.  He wrote 13 opinions in all – 3 in 2016, 5 in 2018, 2 each in 2019 and 2021 and one in 2020.  He wrote eight opinions about sentencing law – two each in 2015 and 2017 and one in 2016, 2018, 2019 and 2020.  Justice Cuéllar wrote seven opinions on criminal constitutional law – 4 in 2017 and one each in 2018, 2020 and 2021.  He wrote three majority opinions regarding political crimes, three in 2015 and one in 2016.  He wrote three majorities on criminal procedure – one each in 2016, 2018 and 2021.  He wrote two opinions about property crimes (both in 2016), two about violent crimes (2018 and 2019) and two about juvenile offenses (2019 and 2021).  He wrote one majority opinion about habeas corpus law and one about sexual offenses.

Justice Cuéllar wrote only nine dissents in criminal cases.  Two-thirds of those were in death penalty cases – two each in 2017 and 2019 and one each in 2015 and 2018.  He wrote one dissent each in criminal procedure (2017), sentencing law (2017) and constitutional law (2018).

Join us back here later this week as we turn our attention to a new topic.

Image courtesy of Flickr by Harold Litwiler (no changes).

This week, we’re reviewing the written opinions of Justice Cuéllar’s seven-year tenure.  The most frequent topics for his majority opinions in civil cases were government and administrative law and civil procedure, with six opinions each.  Justice Cuéllar wrote two government and administrative law majority opinions in 2016 and 2018 and one each in 2019 and 2020.  He wrote two majorities about civil procedure in 2017 and 2019 and one each in 2020 and 2021.  Justice Cuéllar wrote four majority opinions about tort law – one each in 2017, 2019, 2020 and 2021.  He wrote one majority opinion each about environmental law (2015), employment (2016), constitutional law (2017), contract law (2018), bankruptcy law (2018), construction law (2018) and arbitration (2019).

Justice Cuéllar wrote only seven civil dissents.  Three dealt with employment law – one in 2019 and two in 2021.  Two were about environmental law – one each in 2016 and 2017.  He wrote one dissent relating to government and administrative law, in 2016 and one on constitutional law, in 2017.

Join us back here next time as we review Justice Cuéllar’s criminal opinions.

Image courtesy of Flickr by TomH2323 (no changes).

Today, we’re reviewing the metric we’ve argued in past posts is a reasonable proxy for determining the degree to which a particular Justice is in sync ideologically with the rest of his Court (and/or the degree of influence that Justice has on the Court).  For purposes of this number, we’re including only total agreement – voting to affirm in part and reverse in part where the majority affirms outright is counted as being in the minority, not partial agreement.

Overall for his tenure, Justice Cuéllar has voted with the majority in 210 of 220 civil cases – 95.45%.  His highest year was 2016, when he voted with the majority in all 36 civil cases he participated in.  Next were 2015 (96.3%), 2018 (96.97%) and 2020 (96.55%).  Justice Cuéllar’s lowest civil agreement rate was this year – 89.47%.

Justice Cuéllar has voted with the majority in 276 of 293 criminal cases – 94.2%.  His highest level of agreement was in 2015 – 36 of 36 for 100%.  Next were 2016 (98.08%), 2020 (97.62%) and 2021 (93.33%).  His lowest level of agreement was in 2017, when he voted with the majority in 85.71% of cases.

Image courtesy of Flickr by Kevin Gill (no changes).

Today, we’re continuing our multi-part series on the soon-to-conclude tenure on the Court of Justice Mariano-Florentino Cuéllar.

We begin this time with a review of Justice Cuéllar’s votes.  To simplify our numbers (and since it’s the smallest portion of the docket), we disregard the certified question appeals where the Court’s holding was something other than “affirmed,” “reversed” or “affirmed in part, reversed in part.”  However, in writ cases, we assume that “denied” signifies approval of the underlying ruling and thus count it as a vote to affirm and that “granted” or “vacated” signifies disapproval and count that as a vote to reverse.

Since joining the Court, Justice Cuéllar has vote to affirm in 80 civil cases: 18 in 2017, 16 in 2016, 15 in 2018, down to a low of 6 each year in 2020 and 2021.  He has cast a split vote – affirm in part, reverse in part – 17 times, ranging from a high of 5 in 2017 and 4 in 2018 down to zero this year.  He has voted to reverse in 104 civil cases.  Justice Cuéllar’s busiest year was 2016 and 2019, when he voted to reverse 18 times.  He cast 17 reverse votes in 2020 and 16 in 2017, ranging down to lows of 10 in 2018 and 2021.  The only two years in which he voted to affirm more than to reverse were 2017 (18-16) and 2018 (15-10).

Justice Cuéllar has voted to affirm in 146 criminal cases.  He has cast a split vote 44 times and has voted to reverse in 102 cases.

Justice Cuéllar’s busiest year for affirmances was 2018 with 33.  There were 22 affirm votes in 2016, 20 per year in 2019 and 2020 and only 15 so far this year.  Justice Cuéllar filed 12 concurrences in 2016 and 8 each in 2015 and 2019.  He has filed only 3 this year.  Justice Cuéllar’s busiest years for dissents were 2016 and 2017 with 18 each.  He dissented in 17 cases in 2020, 13 in 2019 and only 12 in 2015, 2018 and 2021.

Join us back here tomorrow as we continue our series.

Image courtesy of Flickr by Becky Matsubara (no changes).

As we continue our review of Justice Cuéllar’s nearly seven years on the California Supreme Court, today we’re looking at his published opinions.  Since joining the Court, Justice Cuéllar has written 99 opinions – 43 in civil cases and 56 in criminal cases.

Justice Cuéllar has written a total of 27 civil majority opinions along with 8 concurrences and 8 dissents.  His busiest years for civil majority opinions were 2018 and 2019, with five each.  He has written three majority opinions in 2015, 2016 and 2021.  He never wrote more than two concurring opinions in civil cases in a year (2018 and 2020).  Similarly, he wrote two civil dissents per year in 2016, 2017 and 2021.

Justice Cuéllar has written 42 majority opinions in criminal cases since joining the Court.  He has written only five concurrences, but has also published nine dissents.  His heaviest year for criminal majority opinions was 2018, when he wrote 11 (meaning that he published a total of 16 majority opinions that year).  Justice Cuéllar published eight majority opinions in criminal cases in 2016, seven in 2021, six in 2017 and five in 2019.

Justice Cuéllar’s concurring opinions in criminal cases were clustered in only two years of his tenure – 2020 (3) and 2016 (2).  He published four dissents in 2017, two each in 2018 and 2019 and one in 2015.

Join us back here on Thursday as we continue our series.

Image courtesy of Flickr by FancyLady (no changes).

The resignation of Justice Mariano-Florentino Cuéllar from the California Supreme Court becomes effective on Sunday, October 31.  Today, we’re beginning a four-part review of Justice Cuéllar’s tenure.

Justice Cuéllar took his seat on the Court on January 5, 2015, replacing retired Justice Marvin Baxter.  Since that time, he has participated in 513 cases (assuming no decisions are issued on Thursday October 28.)  Two hundred twenty of the cases were civil and the remaining 293 were criminal, quasi-criminal, juvenile justice or mental health cases.

The Court’s civil docket reached its high point in 2017, when Justice Cuéllar participated in 42 civil cases.  Since that time, the civil caseload has declined almost without interruption: 33 cases in 2018, 34 in 2019, 29 in 2020 and only 19 in 2021.

The criminal docket has been more predictable.  The high point of Justice Cuéllar’s tenure was 2016, when he participated in 52 criminal cases.  The docket rose to nearly that level in 2018, when he sat on 50 criminal cases.  Since that time, the cases have been down: 41 cases in 2019, 42 in 2020 and only 30 in 2021.

Image courtesy of Flickr by FancyLady (no changes).

Reprinted with permission from the October 2017 issue of ALI CLE’s The Practical Lawyer.

On Lex Machina’s platform, counsel can use the “motion kickstarter” to survey recent motions before the assigned trial judge. The “motion chain” links together the briefing and the eventual order for each motion, so counsel can identify the arguments which have succeeded in recent cases, and review both the parties’ briefs and the judge’s order.

Ravel Law offers extensive resources to help counsel in crafting their arguments. As counsel does her research, Ravel Law shows visualizations demonstrating how different passages of a case have been cited, and by which judges, enabling counsel to quickly zero in on the passages which judges have found most persuasive. Or the research can be approached from the other direction, by identifying the cases and passages most often cited by your judge for particular principles. How does the judge typically explain the standards for granting a motion to dismiss, or for summary judgment? Does the judge tend to frequently cite Latin legal maxims, or even sports analogies? How does your federal judge handle the state law of his or her home jurisdiction? How has your judge ruled in rapidly evolving areas of the law, such as class certification, arbitration and personal jurisdiction? Now it’s easy to find out.

And when the case finally goes to trial, there’s still a role for judicial analytics. How often do the judge’s cases go to trial? What kinds of cases have tended to go to trial before your trial judge? What were the results? The data you pulled at the outset on the length of the judge’s previous trials might suggest just how liberal or strict the judge tends to be with the parties in trial. Did either party waive a jury, and if so, what happened? How has your trial judge handled jury instructions in recent trials where the parties didn’t waive the jury? What were the awards of damages, plus any awards of attorneys’ fees or punitive damages?

Post-trial is an often overlooked opportunity to cut litigation short by limiting or entirely wiping out an adverse verdict through new trial motions and motions notwithstanding the verdict. Counsel can determine on Lex Machina’s motion comparator, Ravel Law’s motions database or Bloomberg’s Litigation Analytics how likely judges are to either overturn or modify a jury verdict. A close look at the data and recent orders and motions will help inform a decision as to whether to file a motion for judgment notwithstanding the verdict or a motion for new trial. If your client has been hit with a punitive damages award, you’ll need to review not only the judge’s record on post-trial review of punitives, but drill down from there to the order and the briefing on the motion to evaluate what approaches worked (or didn’t).

Analytics have tremendous potential in appellate work too. All of the major vendors have enormous collections of data on state and federal appellate courts and judges. But for my firm’s appellate practice, I was interested in tracking a number of different variables which would be difficult to extract through computer searches, so rather than relying on any of the vendors, I built two databases in-house. Our California and Illinois Supreme Court databases are modeled after Professors Spaeth and Segal’s Supreme Court database, tracking many of the same variables. My California Supreme Court database encompasses every case the court has decided since January 1, 1994 – 1,004 civil and 1,293 criminal, quasi-criminal and attorney disciplinary. My Illinois Supreme Court database is even bigger, including every case that court has decided since January 1, 1990 – 1,352 civil and 1,529 criminal. For each of these 5,000+ cases, I’ve extracted roughly one hundred different data points. Was the plaintiff or the defendant the appellant in the Supreme Court? Is there a government entity on either side? Where did the case originate, and who was the trial judge? Before the intermediate appellate court, we track dissents, publication, the disposition and the ideological direction of the result. We track three dates for each case: the date review was granted, the date of the argument and the date of the decision. Before the Supreme Court, we note both the specific issue and the area of the law involved, the prevailing party and the vote, the writers and length of all opinions, the number of amicus curiae briefs and who each amicus supported, and of course each Justice’s vote. In addition, our database includes data from every oral argument at the Illinois Supreme Court since 2008, and arguments at the California Supreme Court since May 2016, when the Court first started posting video and audio tapes of its sessions.

Conventional wisdom in most jurisdictions holds that unless the intermediate appellate court’s decision was published with a dissent, it’s not worth seeking Supreme Court review. We’ve demonstrated that in fact, a significant fraction of both the California and Illinois Supreme Court’s civil dockets arises from unpublished unanimous decisions. We track not just aggregate reversal rates for intermediate appellate courts, but break the data down into reversal rates by area of law.

Lag times are particularly interesting in California, since the Supreme Court is generally required to decide cases within ninety days of oral argument. As a result, the vast majority of the lag between grant of review and final decision in California falls between grant and argument, rather than argument and decision. Not only have we tracked the average time to resolution for civil and criminal cases— we’ve demonstrated that there’s a correlation between the Supreme Court’s decision and the lag time from grant to argument. We’ve tracked the individual Justices’ voting records, not just overall, but one area of law at a time.

Only in the past few years have data analysts began to take a serious look at appellate oral arguments. The earliest study appears to be Sarah Levien Shullman’s 2004 article for the Journal of Appellate Practice and Process.  Shullman analyzed oral arguments in ten cases at the United States Supreme Court, noting each question asked by the Justices and assigning a score from one to five to each depending on how helpful or hostile she considered the question to be. Based upon her data, she made predictions as to the ultimate result in the three remaining cases. Comparing her predictions to the ultimate results, Shullman concluded that it was possible to predict the result in most cases by a simple measure – the party being asked the most questions generally lost.

John Roberts addressed the issue of oral argument the year after Shullman’s study appeared. Then-Judge Roberts noted the number of questions asked in the first and last cases of each of the seven argument sessions in the Supreme Court’s 1980 Term and the first and last cases in each of the seven argument sessions in the 2003 Term. Like Shullman, Roberts found that the losing side was almost always asked more questions.

Timothy Johnson and three other professors published their analysis in 2009. Johnson and his colleagues examined transcripts from every Supreme Court case decided between 1979 and 1995—more than 2,000 hours of argument in all, and nearly 340,000 questions from the Justices. The study concluded, after controlling for a number of other factors that might explain case outcomes, all other factors being equal, the party asked more questions generally wound up losing the case.

Professors Lee Epstein and William M. Landes and Judge Richard A. Posner published their study in 2010. Epstein, Landes and Posner used Professor Johnson’s database, tracking the number of questions and average words used by each Justice. Like Professor Johnson and his colleagues, they concluded that the more questions a Justice asks, all else being equal, the more likely the Justice will vote against the party, and the greater the difference between total questions asked to each side, the more likely a lopsided result is. Our study of every oral argument at the Illinois Supreme Court from 2008 through 2016 came to the same conclusion: the larger the margin between your total questions from the Court and your opponent, the less your chance of winning.

Litigation analytics can uncover useful insights outside of courtrooms as well. Corporate legal departments are increasingly using analytics to track and manage their outside counsel. Does the company have more or less litigation than its competitors? Do the lawsuits last a comparable length of time, and is the company’s win rate comparable to its peers? What are the trends over time? When the company is selecting counsel for a particular lawsuit, depending on where the case is venued, it should be possible by consulting Premonition, Lex Machina or Bloomberg to compare each candidate counsel’s winning percentage in the jurisdiction and before the particular judge, as well as to develop far more background information than was ever possible before. From the viewpoint of the law firms competing for business, analytics offers an invaluable insight into the nature of your target client’s business. All the same questions which the legal department will likely be interested in are valuable to the outside attorneys as well. Is your target’s current counsel not winning cases as often as other companies are? What’s the nature of the company’s litigation? And if candidate counsel can discover the names of the other firms competing for the business, analytics databases can provide detailed information about those lawyers’ experience and relevant background. Premonition’s Vigil court alerts system can get lawyers word of a new filing or case development involving a client or potential client only an hour or two after it happened, not a few days later.

So how does the future look? We’re still in the early days of the revolution in litigation analytics. As the federal PACER system is upgraded and more and more states put some or all dockets in electronic form, more litigation data will become available to analytics vendors. Analytics scholars will develop new methods to turn additional aspects of litigation into usable data. Upgrades in artificial intelligence systems will result in analytics learning to gather more subtle data from court records— the kind of variables that require understanding and interpretation, rather than simply looking for text strings. More analytics vendors will inevitably enter the market.

Lawyers will have to become comfortable working with analytics data in situations where decisions were once made based upon intuition and experience, both in courtrooms and in clients’ counsel searches. More law firms will likely develop in-house analytics databases similar to mine in other large states.

We’ve barely scratched the surface in terms of statistical and theoretical techniques which can uncover new insights about litigation and judicial decision making. Several academics have proposed algorithms for predicting case outcomes based on information such as the composition of an appellate panel and the ideology, gender and background of the judges, and these algorithms have generally performed better than law professors’ predictions based on the legal issues involved. Regression modeling is a natural next step not just to predict case results, but to estimate the real impact of various variables, such as how much (if at all) amicus support increases one’s odds of winning. Several vendors have touted their data on winning percentages for lawyers, but regression modeling could isolate how much impact a particular counsel really has upon a party’s chances, or whether the jurisdiction or the nature of a lawyer’s clients explains his or her record. As Judge Posner and Professors Epstein and Landes suggested in The Behavior of Federal Judges, computerized sentiment analysis of the content of judicial opinions could produce more nuanced insights about particular judges’ attitudes and ideology. Game theory is another well-developed academic discipline with a largely untapped potential for understanding how appellate courts work.

We end with the question every analytics scholar (and vendor) is asked sooner or later: will litigation analytics replace lawyers?

The answer is no, for two reasons.

The first is what I think of as the orange used car problem.

A few years ago, a company which conducts data mining competitions for corporate clients ran a contest in hopes of building an algorithm to determine which among used cars available at auction was likely to have mechanical problems. They collected the data, ran the correlations, and it turned out the strongest correlation to “few or no mechanical problems” was, you guessed it, that the vehicle was orange.

A few people facetiously proposed theories as to why orange used cars might be more trouble-free (maybe car fanciers with better maintenance habits are drawn to them?), but this is an example of one of the most fundamental rules in data analytics: correlation does not necessarily indicate causation. Saying two variables are highly correlated doesn’t necessarily mean one is causing the other; both could be caused by a third, unidentified variable, or it could be a random correlation, or your dataset could be biased or simply too small. Much of litigation analytics—at least short of the more sophisticated logistic regression modeling – currently consists of identifying correlations. It takes an experienced lawyer intermediary to review the data and understand what are valuable, actionable insights and what are just orange used cars.

The second reason is even more fundamental: all litigation analytics require interpretation, and one must keep constantly in mind—and remind clients early and often – that nothing in analytics is a guarantee of any particular result. The more heavily questioned party does win at times in the appellate courts. Just because Justices A and B have voted together in 75 percent of the tort cases in the past five years is no guarantee they won’t disagree about the next one. The academic algorithms which have been developed for predicting results at the Supreme Court are wrong anywhere from twenty percent to a third of the time. Some often-quoted statistics can mislead through over-aggregation. For example, perhaps an intermediate court’s overall reversal rate on all cases is two-thirds, but on further analysis, it turns out that the reversals are all in tort cases, while the court is generally affirmed in other areas of the law.

Does this mean that litigation analytics are irrelevant? No, no more so than the bank would find the experiential data on the hypothetical mortgage bundle we discussed at the outset irrelevant. Attorneys have been predicting what courts are likely to do for generations based on intuition, experience and anecdote. The business world began moving away from that a generation ago, and now that revolution has struck the law full force. Today, there’s data for most aspects of litigation, and that trend builds every year. The advent of litigation analytics and data-driven decision making is a game-changer in terms of intelligent management of litigation risk.

Image courtesy of Flickr by Ken Lund (no changes).