I too hope that this succeeds.
Archive for the 'Science' Category
Overall, I’d say that, if anything, social scientists perhaps don’t spend enough time re-confirming the definitive statements. There’s a real push toward novelty, to the extent that maybe we don’t have enough “gold standards” of well-established social patterns.
For those interested, the 2013 conference of the Foundation for International Studies on Social Security (FISS) is June 13-15 in Stockholm. Details are here.
For those interested, the 2013 conference of the Society for the Advancement of Socio-Economics (SASE) is June 27-29 in Milan. Details are here.
The problem is especially pronounced in the social sciences. I’d guesstimate perhaps 2% of the pages in the leading economics, policy, political science, and sociology journals feature replication and/or reanalysis. We ought to aim for something in the neighborhood of 33%.
Why the continued preference for new theory and analysis? My guess is simple path dependence. Until recently data were relatively scarce. Replication and reanalysis was no less valuable than today, but it was more difficult, time-consuming, and expensive. That’s changed profoundly. Yet the norm at most journals hasn’t. It should.
Where the journals go, tenure committees will follow.
Then again, perhaps the shift can happen without the journals.
Bill Simmons’ The Book of Basketball is part extended sports column, part scholarly tome. The mixture works well. Simmons has taken advantage of the massive increase in available historical information on professional sports to produce a book that is insightful, colorfully written, and steeped in data.
The Book of Basketball offers thoughtful and informed answers to a number of interesting questions: Who was a better player: Bill Russell or Wilt Chamberlain? Who were the top 96 players, in order, in NBA history? Which were the best teams in NBA history? Which twelve players would form the best basketball team? The most interesting chapter of all, in my view, is one titled “How the Hell Did We Get Here?” — a fascinating year-by-year discussion of developments in the league, the players, the styles, and how they were influenced by trends in American society.
The data come from the usual statistics on scoring, rebounding, assists, turnovers, shot blocks, and other quantifiable aspects of basketball. They also come from journalist reports, from basketball books, from Simmons’ interviews and discussions with (current and former) players, coaches, and basketball executives, and from thousands of games and game segments that are now viewable on the internet and on channels like ESPN Classic.
Simmons has a deep passion for his topic, stemming partly from his having attended hundreds of Boston Celtics home games as a kid in the 1970s and 1980s. That passion is key to the book. It helps not because it leads him to openly reveal his love for the Celtics or his lack of love for Wilt Chamberlain, Kareem Abdul-Jabbar, and Kobe Bryant. Simmons’ frankness, coupled with his enthusiasm and flowing prose, no doubt help make this book a hit with many basketball fans. For me, Simmons’ passion matters because it’s surely what led him to spend so much time examining individual and team statistics, reading about and digesting reports and books on earlier eras, watching countless hours of game footage, and talking and debating with other experts and analysts. It’s Simmons’ knowledge about his subject — his reliance on evidence, in various forms and from an array of sources — that makes this a terrific book.
It’s therefore particularly surprising and disappointing that the book’s key chapter is missing. In chapter 1, before he gets to history’s best players and teams, Simmons heads straight to basketball’s most important question: What explains which teams win championships? He gives us a sensible though debatable hypothesis (pp. 46-48 in the 2010 paperback edition). But then he moves on, offering only some scattered analysis.
Simmons’ hypothesis: “teamwork over talent.”
A little elaboration: “Teams that play together, kill themselves defensively, sacrifice personal success and ignore statistics invariably win the title.”
Here’s what we know for sure:
1. You build potential champions around one great player. He doesn’t have to be a super-duper star or someone who can score at will, just someone who leads by example, kills himself on a daily basis, raises the competitive nature of his teammates, and lifts them to a better place.
2. You surround that superstar with one or two elite sidekicks who understand their place in the team’s hierarchy, don’t obsess over stats, and fill in every blank they can.
3. From that framework, you complete your nucleus with top-notch role players and/or character guys who know their place, don’t make mistakes, and won’t threaten that unselfish culture, as well as a coaching staff dedicated to keeping those team-ahead-of-individual values in place.
4. You need to stay healthy in the playoffs and maybe catch one or two breaks.
That’s how you win an NBA championship.
This seems plausible, even compelling. Then again, it sounds like a to-the-tee description of the Utah Jazz from 1988 to 2003. The number of NBA titles the Jazz won during that span: zero.
We need evidence and analysis. Here’s what Simmons offers (pp. 47-48):
1. The list of Best Players on an NBA Champ Since Bird and Magic Joined the League looks like this: Kareem (younger version), Bird, Moses, Magic, Isiah, Jordan, Hakeem, Duncan, Shaq (younger version), Billups, Wade, Garnett, Kobe. It’s a list that looks exactly how you’d think it should look with the exception of Billups.
2. The list of Best Championship Sidekicks Since 1980: Magic, Parish/McHale, Kareem (older version), Worthy, Doc/Toney, DJ, Dumars, Pippen/Grant, Drexler, Pippen/Rodman, Robinson, Kobe (younger version), Parker/Ginobili, Shaq (older version), Pierce/Allen, Gasol. You would have wanted to play with everyone on that list … even younger Kobe.
3. Too many to count, but think Robert Horry/Derek Fisher types.
Sprinkled throughout the book are additional bits and pieces of evidence that bear on the “teamwork over talent” hypothesis. But the only systematic analysis is in the chapter I mentioned earlier in which Simmons goes through the 1960s Russell-Chamberlain years comparing their teams and outcomes. It’s a very good chapter. The key conclusion is that contrary to conventional belief, Russell’s supporting cast wasn’t consistently better talent-wise than Chamberlain’s. And there’s loads to indicate that Russell prioritized and fostered a team-first approach whereas Wilt did not. Russell’s teams won eleven NBA titles; Chamberlain’s won two. Hypothesis confirmed.
But only through the early 1970s. The Russell-Chamberlain chapter ends on page 83, and I spent the rest of the 734-page book waiting, largely in vain as it turned out, for examples of post-Chamberlain teams that had sufficient talent to win an NBA title but didn’t because they lacked the teamwork element. Surely the 2004 Lakers. Possibly the post-1986 Houston Rockets, though Simmons says they also were hindered by Ralph Sampson’s bad luck and by cocaine. Others?
So here’s what I’m hoping for in the second edition: the missing chapter(s) in which Simmons walks us through each of the past forty years with an assessment of the talent and teamwork of the top four or five or eight teams. Why add more to a book that’s already very long? Because we need that analysis, and Simmons is the person to do it. It would ensure that The Book of Basketball, already splendid in many respects, remains the book of basketball for many years to come.
For those interested, the 2011 conference of the Society for the Advancement of Socio-Economics (SASE) is June 23-25 in Madrid. Details are here.
For those interested, the 2009 conference of the Society for the Advancement of Socio-Economics (SASE) is July 16-18 in Paris. Details are here.
Research on the economy, politics, and society often examines countries, comparing across them and/or over time within them.
Analysts doing this type of empirical work utilize a variety of methodological strategies. Among them are pooled cross-section time-series regression, qualitative comparative analysis (QCA), and small-N analysis. Contributions to a new book I’ve co-edited explore the strengths and weaknesses of these approaches by using each of the three to analyze employment performance in affluent nations.
The book is Method and Substance in Macrocomparative Analysis, edited by Lane Kenworthy and Alexander Hicks, Palgrave Macmillan, 2008. The introductory chapter is online here.
- Introduction, by Lane Kenworthy and Alexander Hicks
- Statistical Narratives and the Properties of Macro-Level Variables: Labor Market Institutions and Employment Performance in Macrocomparative Research, by Bernhard Kittel
- Comparative Employment Performance: A Fuzzy-Set Analysis, by Jessica Epstein, Daniel Duerr, Lane Kenworthy, and Charles Ragin
- Do Family Policies Shape Women’s Employment? A Comparative Historical Analysis of France and the Netherlands, by Joya Misra and Lucian Jude
- The Welfare State, Family Policies, and Women’s Labor Force Participation: Combining Fuzzy-Set and Statistical Methods to Assess Causal Relations and Estimate Causal Effects, by Scott R. Eliason, Robin Stryker, and Eric Tranby
- Family Policies and Women’s Employment: A Regression Analysis, by Alexander Hicks and Lane Kenworthy
- Part-Time Work and the Legacy of Breadwinner Welfare States: A Panel Study of Women’s Employment Patterns in Germany, the United Kingdom, and the Netherlands, 1992-2002, by Jelle Visser and Mara Yerkes
- Comparative Regime Analysis: Early Exit from Work in Europe, Japan, and the USA, by Bernhard Ebbinghaus
- Identifying the Causal Effect of Political Regimes on Employment, by Adam Przeworski