I saw it on New Year’s Eve and liked it a lot. But, I think it’s best taken as a series of brilliant set pieces. String them together and you have a fairly predictable narrative arc, and a thematic point ( [SPOILER] Greed is bad) that isn’t going to change anyone’s mind. But the set pieces are incredibly well done because Scorcese. And Leo Dicaprio is just great in it.

Some people are upset because the movie doesn’t condemn the behavior it depicts. Yikes. Scorcese is obviously showing us behavior he finds so extraordinarily bad that he was motivated to make a movie about it. To tack on some moralizing elements would only lessen the impact, because that would imply that we need to be told that the behavior depicted is bad.

Mike Ryan at HuffPo writes about this question and, citing Chuck Klosterman, compares Leo’s character to Archie Bunker. But there’s very little to understand about Archie. He’s a bigot and ignorant. Haha. Wolf of Wall Strett instead shows us a sub-culture that is twisted and extreme, but is coherent within its own little world. There’s something to understand there, which is why Leo is able to give an Oscar-worthy performance. In that it’s much like The Godfather or The Sopranos, not to mention Good Fellas. It is also more like American Psycho than like Wall Street. (And speaking of Oliver Stone, one of my very least favorite directors, if you want to be hit repeatedly with a gigantic Morality Hammer, watch Platoon, if you can get through it.)

Good Fellas is a better movie than Wolf (in my opinion, natch) because it is less predictable, the main character is more morally nuanced, there are more unforgettable characters, etc. But I thought Wolf was very good, very entertaining, and treated us like moral grownups.

Not that all of us are.

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Gary King [twitter:kinggarry] , Director of Harvard’s Institute for Quantitative Social Science, has published an article (Open Access!) on the current status of this branch of science. Here’s the abstract:

The social sciences are undergoing a dramatic transformation from studying problems to solving them; from making do with a small number of sparse data sets to analyzing increasing quantities of diverse, highly informative data; from isolated scholars toiling away on their own to larger scale, collaborative, interdisciplinary, lab-style research teams; and from a purely academic pursuit focused inward to having a major impact on public policy, commerce and industry, other academic fields, and some of the major problems that affect individuals and societies. In the midst of all this productive chaos, we have been building the Institute for Quantitative Social Science at Harvard, a new type of center intended to help foster and respond to these broader developments. We offer here some suggestions from our experiences for the increasing number of other universities that have begun to build similar institutions and for how we might work together to advance social science more generally.

In the article, Gary argues that Big Data requires Big Collaboration to be understood:

Social scientists are now transitioning from working primarily on their own, alone in their officesâ??a style that dates back to when the offices were in monasteriesâ??to working in highly collaborative, interdisciplinary, larger scale, lab-style research teams. The knowledge and skills necessary to access and use these new data sources and methods often do not exist within any one of the traditionally defined social science disciplines and are too complicated for any one scholar to accomplish alone

He begins by giving three excellent examples of how quantitative social science is opening up new possibilities for research.

1. Latanya Sweeney [twitter:LatanyaSweeney] found “clear evidence of racial discrimination” in the ads served up by newspaper websites.

2. A study of all 187M registered voters in the US showed that a third of those listed as “inactive” in fact cast ballots, “and the problem is not politically neutral.”

3. A study of 11M social media posts from China showed that the Chinese government is not censoring speech but is censoring “attempts at collective action, whether for or against the government…”

Studies such as these “depended on IQSS infrastructure, including access to experts in statistics, the social sciences, engineering, computer science, and American and Chinese area studies. ”

Gary also points to “the coming end of the quantitative-qualitative divide” in the social sciences, as new techniques enable massive amounts of qualitative data to be quantified, enriching purely quantitative data and extracting additional information from the qualitative reports.

Instead of quantitative researchers trying to build fully automated methods and qualitative researchers trying to make do with traditional human-only methods, now both are heading toward using or developing computer-assisted methods that empower both groups.

We are seeing a redefinition of social science, he argues:

We instead use the term “social science” more generally to refer to areas of scholarship dedicated to understanding, or improving the well-being of, human populations, using data at the level of (or informative about) individual people or groups of people.

This definition covers the traditional social science departments in faculties of schools of arts and science, but it also includes most research conducted at schools of public policy, business, and education. Social science is referred to by other names in other areas but the definition is wider than use of the term. It includes what law school faculty call “empirical research,” and many aspects of research in other areas, such as health policy at schools of medicine. It also includes research conducted by faculty in schools of public health, although they have different names for these activities, such as epidemiology, demography, and outcomes research.

The rest of the article reflects on pragmatic issues, including what this means for the sorts of social science centers to build, since community is “by far the most important component leading to success…” ” If academic research became part of the X-games, our competitive event would be “‘extreme cooperation'”.

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It’s been a disappointing year for those of us who enjoy Top Ten Top Ten lists. Last year I found an arguable ten or so for my Top Ten top Ten Top Ten list.

This year, my Top Ten Top Ten Top Ten lists contains only four:

• Top Ten Best of 2013 Lists of 2013 Washington Post. Alexandra Petri.

• 10 Top 10 Lists – Storytelling edition Harvard Nieman Storyboard, Paige Williams

• The Local’s top ten top ten lists of 2013 The Local: Sweden’s News in English, Oliver Gee

• The Top Ten Top Ten Lists of 2013 Swan Fungus

Then there were some sites that seemed promising but can’t count in a list as rigorous as this. I have my standards, people!

• Top Ten Top Ten Lists At TopTenTopTen.com, a site that is down. This particular list, by BrassManBob, has one list with only three entries.

• Top Ten of Everything Time Magazine. Only lists six

• Film Critic Top Ten Lists Metacritic. Lists 73 or so

Not only is this a disaster for this year’s list, it calls into question our progress toward the dream: a Top Ten Top Ten Top Ten Top Ten list. But I have hope. We can do this!

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