My review of ‘I Am Pilgrim’ by Terry Hayes

By Graham

I Am PilgrimI Am Pilgrim by Terry Hayes
My rating: 2 of 5 stars

It takes special skill to write a book with over 850 pages – all of which are torturously overwritten and peppered with cheap hyperbole – and yet still retain the attention of people accustomed to better. Terry Hayes possesses this rare talent.

I am a slow reader, with diminishing patience for crappy writing as I get older and crankier. In the months it took me to get through ‘I Am Pilgrim’, there were moments when I literally winced at the bad writing. There were times I thought, that’s it, I’m done with this cliche-ridden piece of trash.

Yet I kept coming back for more. Partly this was an act of loyalty to the man who wrote the screenplay for one of the great, childhood-defining movies of the 1980s: ‘Mad Max: Beyond Thunderdome’. But it was also because I Am Pilgrim has something seriously good to offer.

What Hayes lacks in classical writing talent, he as good as makes up for through the books two principle strengths: first, his attention to detail and second, the muscle behind his storytelling. For the first, the secret agent protagonist (who name I have, tellingly, already forgotten) is given a severe credibility handicap by Hayes’ inability to imbue him with any real depth of character. And yet the detailed descriptions of how he approaches his work, the tricks of his trade, make you share in his world. Some are deliciously simple, such as when he points out that the way to break into someone’s house is not to creep around the dark with a flashlight (which neighbours tend to notice), but simply to switch the light on and move through the house normally.

But it is the second strength, the storytelling, that is the real reason I kept swerving around every unnecessarily unnecessary adverb and past every pastiche minor character. Hayes wrote ‘I Am Pilgrim’ not because he wanted to write a book and needed a story to fill it. He wrote it because he had a stroy to tell and a book was a way of getting that story out into the world.

The plot is perfectly paced. It builds suspense as it needs to and juggles competing story lines via a narrative voice with multiple layers stretched just to the limits of credibility. There are not many writers who will dare to depart on a chapters-long diversion to narrate the backstory of a villain whose crime has not even been hinted at. But Hayes gets away with it, precisely because the reader is left in the certain knowledge that the storyteller knows exactly where all this is going.

I won’t say too much about the conclusion, for two reasons. First, I hate spoilers. But second, if you’ve managed to forgive Terry Hayes all the sins against literature he committed in the preceding 849 pages, what happens from page 850 can no longer harm you.

So if you want a good read, look elsewhere. But if you want a good story, this is a Pilgrimage worth embarking on.

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As with birth rates, we use data for 4 categories of countries from 1990 to 2015 (100 observations total). We have two explanatory variables, AGE and Y, where AGE is defined as the percentage of the population aged over 65 and Y is per capita GDP.

After eyeballing the scattergrams, we test the following functional form:

d = (minY^a)/Y^a * (1/AGE^g)

Where minY is the constant equal to the smallest value of Y in the series.

Logarithmic transformation gives:

ln(d) = ln(minY^a) – a*ln(Y) – g*ln(AGE)

which we test on the data using OLS. Here are the results:

Adjusted R square: 75.191

Intercept coefficient: 7.37384
t-Stat: 20.4011

Y coefficient: -1.01444
t-Stat: -13.1059

AGE coefficient: 2.0097
t-Stat: 11.5208

The estimated intercept is a good, but not perfect, approximation of ln(minY^a)

Here are the fitted against actual values of the scattergram for death rate against per capita GDP:

fitted-death-rates-against-actual-values

While the results are not as good as with the birth rates calculations, it is nevertheless a good enough fit and the explanatory variables have a strong enough confidence factor to be usable in our estimations.

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We begin by examining the scatter of data for 100 observations of per capita GDP and per capita emissions for 4 categories of countries, over 25 years (1990 – 2015).

The scatter suggests a cubic functional form, so we test:

GHG = a + b*Y + c*Y^2 + d*Y^3

where GHG are per capita emissions of GHG, and Y is per capita GDP.

The results from OLS regression are:

Adjusted R square: 0.980438073

coefficient a: 1090
t-stat a: 3.06

coefficient b: 0.709310153
t-Stat b: 8.241453

coefficient c: -0.0000047025
t-Stat c: -1.01233

coefficient d: -0.000000000105314
t-Stat d: -1.47005

While the t-scores on the squared and cubed terms are low, the number of observations are also limited.

Here is the plot of the fitted against actual values:

fitted-emissions-to-gdp-against-actual-values

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