My review of Gary Paulsen’s ‘Hatchet’

By Graham

Hatchet (Brian's Saga, #1)Hatchet by Gary Paulsen
My rating: 3 of 5 stars

Some books smack of polish. The prose is heavy with the weight of old creative writing classes or mimickry of past literary idols.

Sometimes the polish even drips and coagulates into globs at the bottom of the page. It’s as if we can smell the coffee from the Starbucks where the author sat, back in February of 1998, when she first read Hemingway and, looking out the window at the drab Seattle rain, dreamt of one day living in New York City and ‘being an author’. Or else we hear the writer’s impatient fingers upon the keyboard at his office in the community college’s English department, desperately trying to ‘find his voice’ the way he tells his students to, rather than just telling a story.

Gary Paulsen’s Hatchet is certainly not one of these books. The prose has no polish whatsoever. As a result, the writing is crude, almost to the point of distraction. Choppy. Fragments of sentences, running on. An attempt. An attempt to convey the protagonist’s panicked state of mind. A heavy-handed abuse of language. At least in my opinion.

But what Paulsen lacks in literary finesse, he more than makes up for with the quality of his story. The tale is a simple one – a teenage boy named Brian survives the crash of a single engine plane and must learn to live in the Canadian wilderness, with only the eponymous hatchet and the clothes on his back.

Like all great stories, Paulsen has no need to mimic other writers, or to worry about finding a voice. He simply tells Brian’s story, and that is more than enough for the reader to suspend disbelief; to join Brian in the woods, rejoicing with him over every little comfort, salivating at the taste of berries and fish in the starving boy’s mouth.

I understand completely why this book has become a favourite of high school English teachers. And as is the case with all good young adult fiction, it reads just as well, even if you are much older.

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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:


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.


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: