Racism and the tabloids

The hypocrisy of Question Time outrage

If you thought tabloid outrage over Nick Griffin's appearance on Question Time was hypocritical, you weren't alone. Anton Vowl at The Enemies of Reason blog has produced a very thorough picture essay on the subject, which we repost here in full.

NB: "Today" below refers to Friday 23 October, as that's when Anton made the original post.

Today's tabloids express mock outrage at the appearance of N*ck Gr*ff*n on the BBC Question Time programme. But they have short memories.

Here's today's Star:

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Hang on, though. Isn't that the same newspaper that did this?

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And this?

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The Express, meanwhile, is also clutching its pearl necklace, claiming that the party is going to get taxpayer-funded broadcasts at the next election. Not a big lead on Griffin, because there's apparently another twist in the Diana saga (and as ever the stock image of her wearing a seat belt, which would have saved her life in the crash, nutjob neenaw whoop-whoop conspiracy or no conspiracy).

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But it's got those because it's gained votes. I wonder why? I wonder which newspapers are read by BNP supporters? Maybe ones that say stuff like this

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Or this?

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Or even this?

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And not forgetting the all-time classic:

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Not some. Not five hundred. Not even a thousand. Not half. Not three-quarters. No. ALL. IN BIG RED LETTERS SO YOU'RE MADE CLEARLY AWARE THAT IT'S ALL.

Hey, and please let's not forget this:

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I almost didn't include this!

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Which is almost the same as this!

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But no. The Express doesn't like the BNP. They just happen to share entirely the same views on immigration, but Griffin is bad, because . . . well. I haven't quite worked out why he's bad. Maybe he doesn't hate Muslims enough for their tastes?

The Mail have also had a bash, but as ever they're more concerned with attacking their nemesis the BBC than they are about hand-wringing over Griffin:

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Having said which, I still think

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it's worth making the point

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that the Mail doesn't always steer so far away

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from using content

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which the BNP and "bigot" N*ck Gr*ff*n

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might completely agree with

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and it's not long

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before you might start thinking to yourself

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are they really protesting a bit too much? And what's the difference, really, between the BNP bigots and the supposedly mainstream newspaper which claims to distance itself from them so much?

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And you have to start thinking: do these newspapers which select certain types of images of ethnic minorities and use them again and again

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really have such different views or agendas from the likes of the BNP?

It's all very well people blaming Labour, or the BBC, or whoever, for the "rise" of the BNP. But if there has been a significant increase in BNP support -- and it hasn't translated into votes yet, despite a severe recession and growing unemployment -- perhaps that might have more to do with the legitimisation and absorption of their extreme views by newspapers creating scare story after scare story concerning race and immigration, often baseless stories created simply to scare? It's one thing going to a BNP meeting but it's quite another to hear exactly the same thing over the breakfast table from a publication which purports to report the facts.

But no. It's all the BBC's fault. Let's blame them.

 

Daniel Trilling is the Editor of New Humanist magazine. He was formerly an Assistant Editor at the New Statesman.

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