Does Aaron Sorkin have a woman problem?

In the space of three shows - <em>Sports Night, Studio 60</em> and now <em>The Newsroom</em> - Aaron Sorkin's female television executives have gone from clever and competent to ditsy and childish. What's going on?

Does Aaron Sorkin have a women problem? In the early years of this century when The West Wing’s CJ Cregg was the poster girl for modern womankind such a question would have seemed unthinkable. But then came Studio 60 on the Sunset Strip, in which the two female leads were respectively "angry and incompetent" and "ditsy and repressed" and The Social Network, which ran into a storm of bad headlines about its negative depiction of women.

Sorkin vigorously refuted those claims, insisting that in The Social Network: "I was writing about a very angry and deeply misogynistic group of people." In other words just because characters are sexist, don’t presume the writer is as well.

It’s a fair point but what then about The Newsroom? Sorkin’s journalism drama, which returns for its second season this evening wears its heart on its rolled-up, ink-stained sleeves. It’s Sorkin’s funny valentine to the good old days of news before the internet came along and ruined it for everyone and it wants desperately to pay homage to the screwball comedies of the 1930s and 1940s.

There’s just one problem – those screwball comedies knew that there was nothing like a dame. When we think of His Girl Friday it’s Rosalind Russell’s smarts and savvy which springs to mind as much as Cary Grant’s savoir faire. In Bringing Up Baby the pratfalls are shared between Grant and Katharine Hepburn just as Hepburn and Spencer Tracy trade the one-liners in Pat and Mike. These are relationships of equals, of sparring partners, where no one loses. By contrast The Newsroom is a show set in modern day America that allows its female characters less agency than Mad Men, a period piece that explicitly addresses sexism in the workplace.

Thus one of the first things we learn about Emily Mortimer’s MacKenzie McHale is that’s she’s an award-winning war correspondent who has reported from Afghanistan, Iraq and Pakistan. Frankly I’m glad that Sorkin tells us this because you would never know it from her behaviour in the opening episode which includes panicking, dithering, asking the nearest men for help and dithering some more before accidentally sending an email to the entire staff announcing that she was once in a relationship with Jeff Daniel’s character, Will McAvoy. No, this wasn’t a lost subplot from 1990s sitcom Ally McBeal, although I do understand the confusion.

Similar evidence that Sorkin has confused screwball with simpleton can be found in Alison Pill’s Maggie. Maggie is a young reporter and makes the odd mistake, which is understandable. Less understandable is her inability to separate her work and love life, ensuring that she spends each episode flapping, flailing and floundering until an obliging male walks by to bail her out.

Then there’s the fiercely intelligent, super sharp economist Sloan Sabbith. Lucky Sloan is actually allowed to deliver the odd zinger but only if she then redresses the balance by worrying about whether her (extremely pert) arse is too big or obsessing over her lack of broadcast experience.

While season two appears to address some of these issues and the arrival of a smart lawyer played by Marcia Gay Harden is welcome, Sloan’s fears cut to the heart of Aaron Sorkin’s biggest problem. His male characters might have flaws but they are always explained. In The West Wing we know Josh’s commitment issues stem from his sister’s tragic death, that Toby has a complicated relationship with his father and that Sam’s sense of himself was shaken by his dad’s long-term affair. By contrast, as website feministlawprofessors.com pointed out in 2006, CJ’s mistakes are silly and often rather demeaning: in season one she doesn’t know what the census is, in season two she sits in wet paint. These aren’t things that illustrate her character, they’re little scenes to pull her down a peg or two. You might think: "Oh come off it, these are pretty minor moments" and, yes, they are, but can you imagine Josh not knowing what the census was? Sorkin will allow his male characters many flaws but never incompetence. That’s something for women. 

And this attitude has worsened. Somewhere along the line – perhaps as he became more successful and thus less open to advice - Sorkin has stopped writing men and women as equals (as he did in both Sports Night and The West Wing) and instead started to write relationships where men are wronged but righteous and women need advice. As TV critic Jace Lacob astutely noted: "In Sorkinland men act (nobly!) and women support (comically!)."

Thus MacKenzie McHale, Studio 60’s Jordan McDeere and Sports Night’s Dana Whitaker are all the executive producers of their respective shows but only Dana, an early Sorkin creation, was allowed to be funny, clever and good at her job. Dana stood up for her workmates, fought her corner in a male-dominated world and made her own decisions. She had flaws but they were believable and never affected her professionalism, plus she was a grammar pedant, and who doesn’t love them?

By contrast Jordan McDeere was outwardly competent but secretly ravaged by neurosis and prone to rubbing people the wrong way while, rather than producing Will, MacKenzie tends to hang adoringly on his every word coming across like a precocious child hoping for a pat on the head from daddy.

In the space of three shows featuring female television executives, Sorkin has gone from the competent, clever Dana Whitaker to the less competent and less clever Jordan McDeere before ending up with the almost entirely incompetent MacKenzie McHale. If that isn’t a law of diminishing returns then I’m not sure what is.

The Newsroom is on Sky Atlantic from Monday 2 September at 10pm

In The Newsroom: Emily Mortimer as MacKenzie McHale and Alison Pill as Maggie.
OLIVER BURSTON
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How science and statistics are taking over sport

An ongoing challenge for analysts is to disentangle genuine skill from chance events. Some measurements are more useful than others.

In the mid-1990s, statistics undergraduates at Lancaster University were asked to analyse goal-scoring in a hypothetical football match. When Mark Dixon, a researcher in the department, heard about the task, he grew curious. The analysis employed was a bit simplistic, but with a few tweaks it could become a powerful tool. Along with his fellow statistician Stuart Coles, he expanded the methods, and in doing so transformed how researchers – and gamblers – think about football.

The UK has always lagged behind the US when it comes to the mathematical analysis of sport. This is partly because of a lack of publicly available match data, and partly because of the structure of popular sports. A game such as baseball, with its one-on-one contests between pitcher and batter, can be separated into distinct events. Football is far messier, with a jumble of clashes affecting the outcome. It is also relatively low-scoring, in contrast to baseball or basketball – further reducing the number of notable events. Before Dixon and Coles came along, analysts such as Charles Reep had even concluded that “chance dominates the game”, making predictions all but impossible.

Successful prediction is about locating the right degree of abstraction. Strip away too much detail and the analysis becomes unrealistic. Include too many processes and it becomes hard to pin them down without vast amounts of data. The trick is to distil reality into key components: “As simple as possible, but no simpler,” as Einstein put it.

Dixon and Coles did this by focusing on three factors – attacking and defensive ability for each team, plus the fabled “home advantage”. With ever more datasets now available, betting syndicates and sports analytics firms are developing these ideas further, even including individual players in the analysis. This requires access to a great deal of computing power. Betting teams are hiring increasing numbers of science graduates, with statisticians putting together predictive models and computer scientists developing high-speed software.

But it’s not just betters who are turning to statistics. Many of the techniques are also making their way into sports management. Baseball led the way, with quantitative Moneyball tactics taking the Oakland Athletics to the play-offs in 2002 and 2003, but other sports are adopting scientific methods, too. Premier League football teams have gradually built up analytics departments in recent years, and all now employ statisticians. After winning the 2016 Masters, the golfer Danny Willett thanked the new analytics firm 15th Club, an offshoot of the football consultancy 21st Club.

Bringing statistics into sport has many advantages. First, we can test out common folklore. How big, say, is the “home advantage”? According to Ray Stefani, a sports researcher, it depends: rugby union teams, on average, are 25 per cent more likely to win than to lose at home. In NHL ice hockey, this advantage is only 10 per cent. Then there is the notion of “momentum”, often cited by pundits. Can a few good performances give a weaker team the boost it needs to keep winning? From baseball to football, numerous studies suggest it’s unlikely.

Statistical models can also help measure player quality. Teams typically examine past results before buying players, though it is future performances that count. What if a prospective signing had just enjoyed a few lucky games, or been propped up by talented team-mates? An ongoing challenge for analysts is to disentangle genuine skill from chance events. Some measurements are more useful than others. In many sports, scoring goals is subject to a greater degree of randomness than creating shots. When the ice hockey analyst Brian King used this information to identify the players in his local NHL squad who had profited most from sheer luck, he found that these were also the players being awarded new contracts.

Sometimes it’s not clear how a specific skill should be measured. Successful defenders – whether in British or American football – don’t always make a lot of tackles. Instead, they divert attacks by being in the right position. It is difficult to quantify this. When evaluating individual performances, it can be useful to estimate how well a team would have done without a particular player, which can produce surprising results.

The season before Gareth Bale moved from Tottenham Hotspur to Real Madrid for a record £85m in 2013, the sports consultancy Onside Analysis looked at which players were more important to the team: whose absence would cause most disruption? Although Bale was the clear star, it was actually the midfielder Moussa Dembélé who had the greatest impact on results.

As more data is made available, our ability to measure players and their overall performance will improve. Statistical models cannot capture everything. Not only would complete understanding of sport be dull – it would be impossible. Analytics groups know this and often employ experts to keep their models grounded in reality.

There will never be a magic formula that covers all aspects of human behaviour and psychology. However, for the analysts helping teams punch above their weight and the scientific betting syndicates taking on the bookmakers, this is not the aim. Rather, analytics is one more way to get an edge. In sport, as in betting, the best teams don’t get it right every time. But they know how to win more often than their opponents. 

Adam Kucharski is author of The Perfect Bet: How Science and Maths are Taking the Luck Out of Gambling (Profile Books)

This article first appeared in the 28 April 2016 issue of the New Statesman, The new fascism