Review of Franz Kafka’s ‘The Trial’

By Graham

The TrialThe Trial by Franz Kafka
My rating: 5 of 5 stars

When you get used to reading inferior books, even a nibble of a great masterpiece can challenge your digestive system in ways that cause stomach cramps. Franz Kafka is no light read. After a diet of heavily processed modern literature, Franz Kafka’s The Trial is as hard to digest as a meal of wholegrain rice and raw vegetables would be to a junk food aficionado. And yet like its gastronomical equivalent, Kafka’s prose stays with you and nourishes you much longer.

Though hard to digest, The Trial is not hard to chew. The prose is in fact deceptively accessible, inviting the reader into a world that is familiar enough, and well rendered enough, to suspend one’s disbelief, despite the many incongruities that make that world so intriguing and so mysterious. This, indeed, is the fine art of surrealism: To lure the reader with hyper-realistically crafted descriptions into the acceptance of things he might otherwise dismiss as simply absurd.

But unlike, say, a Magritte painting, Kafka’s Trial does not stop at flaunting absurdity. Instead, it takes the reader well beyond the ridiculous into something far more dangerous, as we accompany Joseph K., our middle-aged protagonist, on his descent into insanity. We begin our journey in his bedroom, following him into the bank at which he holds a mid-ranking position, into a farcical courtroom and through the various sordid relationships that belie his repressed sexuality. At no point are we sure of what is truly real and what is a projection of his mental illness. Yet the quality of the prose is such that we can glimpse through the cracks in the protagonist’s madness the light of a more solid world; one that is just beyond his grasp, the existence of which is indispensable for us to appreciate what Joseph K. is experiencing.

The narrative device which Kafka uses to set up this surreality is the bureaucracy of a modern judicial system. This is particularly effective for any reader who has had the displeasure of knowing the vagaries of an inefficient and often self-contradictory public administration; in particular, the infuriating functioning of the legal system. Bureaucracies really are insane, which makes it all the easier for us to accept what Joseph K. is going through. Yet we are reminded at regular intervals that this device is only a metaphor, and that the trial, the court which hosts it and the many court attendants we meet throughout the story, are all of the protagonist’s own making.

It’s possible, if one reads about Kafka’s life, to draw parallels and seek explanations for this or that aspect of the book. But I feel doing so adds nothing to the reader’s experience. My best advice is to sit down at the table, clear your palate and take small and deliberate bites.

But be prepared to spend a lot of time digesting.

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 Category: Art Book Reviews

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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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