Reviewed: British Writers and MI5 Surveillance, 1930-60 by James Smit

Nosy parkers.

British Writers and MI5 Surveillance, 1930-60
James Smith
Cambridge University Press, 226pp, £55

The most hated person in Britain, George Orwell believed, is the nosy parker. MI5 is the state-appointed nosy parker. Some of the agency’s less radioactive files have been opened up grudgingly and James Smith is one of the first literary critics to investigate them. What has been released is partial, “redacted” and tangled. Working through the files must have been like opening oysters with your fingers (a third of the book is dense end-annotation – lots of shells, a few pearls).

Smith focuses on central figures most of whom, in the flush of youth and idealism, were “premature anti-fascists”: principally the “Auden circle” (Christopher Isherwood, Cecil Day-Lewis, Stephen Spender and others), the folk singer Ewan MacColl, the dramaturge Joan Littlewood and two outriders, Orwell and Arthur Koestler. Many, as history moved on and their blood cooled, shifted ideologically. Some were politically bipolar over the course of their lives. Others, among them Orwell, wobbled incomprehensibly. Some, including Koestler, pirouetted as their interests dictated, running rings around the (misnamed, in his case) “intelligence” agencies.

The overwhelming impression is one of officious bumbledom. As Smith neatly observes, the spooks could have garnered more relevant information from the local public library by studying the revisions to Auden’s poems or else attending performances of suspect plays in Stratford. Philistinism seems to have been one of the main qualifications for recruitment. That and a convenient vacancy where common sense should have been.

Spender was under “surveillance” for many years of his life; specially briefed customs officers rummaged through his luggage whenever he returned from abroad. His socks, as friends observed, were well-known for their “potatoes”. This was surely noted. An MI5 report on Orwell (he was then working at the BBC and being watched round the clock) said: “This man has advanced communist views . . . He dresses in a bohemian fashion both at his office and in his leisure hours.” Case closed.

It was PC Plod and Inspector Clouseau all the way – and there was a disinclination to “join up” what was known. Some of the writers were receiving payment from one branch of MI5 while being “surveilled” by another branch.

The magazine Encounter, which was funded covertly by the CIA, was solemnly investigated on suspicion of being run by a communist cell. Meanwhile, in other echelons of the secret service, operatives such as Malcolm Muggeridge were keeping lines open with Langley.

On the evidence presented here, the whole structure of MI5 was fuelled by low-level paranoia – but relatively harmlessly so, compared to the hysterical levels in the US that fuelled McCarthyism. Harmless, that is, except that MI5 did not do the one job it should have done: to monitor and catch the Cambridge spies who did substantial damage to their country.

Paranoia is infectious and it has, I think, infected the core of Smith’s book. He is a little too ready to be suspicious. The book begins and ends with lofty quotations from Spender on the freedom of the writer. One of the main thrusts of the book is to suggest that Spender (the most discussed figure here) was, despite such lofty proclamations, “complicit”.

There had always been the suspicion that he was not what he seemed. Cyril Connolly, who co-edited Horizon with him, discerned that there were two Spenders: “Stephen I”, who was “an inspired simpleton, a great big silly goose, a holy Russian idiot”, and “Stephen II”, who was “shrewd, ambitious, aggressive and ruthless”. Frank Kermode, another co-editor (on Encounter), wryly quipped that his colleague never seemed to know where he was going in London but always knew the quickest way to get there.

Smith tracks Spender’s career from gaytimes Weimar Berlin to his late-life role as public intellectual and world ambassador for British culture, noting his many interactions with various branches of the intelligence services along the way. Pivotal to the author’s verdict is Spender’s 14-year connection with Encounter (1953-67), the longest job he ever held.

Some background, missing from Smith’s account, is necessary. The CIA, much cleverer (on the evidence in this book) than its British counterpart, set out in the early 1950s to reclaim the intellectual-ideological high ground occupied by card-carrying Marxists such as Jean-Paul Sartre. Encounter was one of its most successful operations. The agency deviated its “black” (officially unrecorded) funds through a soi-disant American philanthropist, Julius Fleischmann, who had the convenient “Farfield Foundation”. Thus laundered, the money was passed on to the “independent” Congress for Cultural Freedom, directed by Michael Josselson, a man of high culture and flexible principles resident in Paris and Switzerland.

Irritatingly, Smith calls Spender “the editor of Encounter”. He wasn’t. An American always held that post (latterly Melvin Lasky, Josselson’s “favourite son” and a CIA “agent in place”). Spender owned the back half – he was the magazine’s literary editor. He was no more influential on the political front half of Encounter than, I suspect, the literary editor of this magazine is on the New Statesman’s front half.

Looking at Spender in the round, Smith finds his claims of ignorance as to who funded Encounter and paid his salary “implausible”. He knew, we are to understand. The book ends with a melodramatically “raised eyebrow” at such protes tations. It would have helped before hoisting that eyebrow to look at the many letters in the Spender archive (not hard to access). When, for example, the balloon went up on Encounter in summer 1967, with impeccably sourced articles in the New York Times, Spender wrote, furiously, to Fleischmann for a clear statement. He received a written reply asserting that “as far as Farfield is concerned we have never accepted any funds from any government agency”. Josselson wrote, in response to the same inquiry: “The only outside donor to Encounter has always been the Congress.”

The idea that Spender, Fleischmann and Josselson would have embarked on some charade à trois with letters of blunt inquiry and mendacious denial is, to use Smith’s term, implausible. You could argue that Spender should have known but all the evidence (there is a lot of it) is that he was lied to and duped – as were Encounter’s readers.

Spender has attracted more than his share of sneers during his lifetime and after. This book (more politely than most) adds to them. Does a dead poet’s reputation matter? I think it does. Among the admirable scholarship in this book, there is, I think, an injustice.

John Sutherland is the editor, with Lara Feigel, of Stephen Spender’s “New Selected Journals, 1939-55” (Faber & Faber, £45)

Cecil Day-Lewis, a member of the so-called "Auden circle". Photograph: Getty Images

This article first appeared in the 11 March 2013 issue of the New Statesman, The audacity of popes

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