276 Unit 7 Critical reasoning: Advanced Level
other states. Indiana and New York may be no
more than dramatic exceptions to the national
picture. There may even be states in which the
crime rate is falling more rapidly than in New
York, but in which prisons are also getting
fuller.Sample may not be representative
This criticism of Chart 5 is one that can
frequently be levelled against statistics which
take samples. Firstly, the sample may be too
small to be representative of wider trends.
There are 50 US states with a total population
of over 300 million. New York and Indiana,
though large, account for less than 10% of the
national population. Secondly, because the
statistics come from just two states, they are
not a random selection, meaning that 90% of
the population are not represented at all.
Thirdly, it is very likely that the two states have
been selected deliberately because they
support the claim or claims being made.
Selection bias is almost certainly an issue with
these statistics.
Despite these critical comments, the data in
Chart 5 is not without significance. There are
inferences that can be drawn from it, though
not broad generalisations.What can be inferred?
The specific inference that you were asked to
assess was not as strong as ‘Prison works’ or
‘Prison does not work’. It was simply the
contention that we can reduce our reliance on
prisons and be safer. With the emphasis on
‘can’, [4] can be understood as a much weaker
proposition than, say, [3]. It challenges the
claim that long prison sentences are the best
or only answer to crime, and suggests that
there may be other ways to tackle the problem.
On that understanding, the evidence for [4] is
much more compelling, because it is merely
registering that there may be another way of
doing things. It is not saying that we should
throw open the prison doors tomorrow and
expect to see law and order swiftly return. It is
saying that we should not assume that justLet’s look at the numbers. From Chart 3 we
know that in the same decade crime fell
nationally by around 1.8 million from 12
million, which is approximately 15%. New
York’s crime rate fell by almost twice that,
29%. Indiana’s fell by a mere 8%. From Chart 4
we can calculate that the national increase in
prisoners per 100,000 was around 7% over the
relevant period. Indiana’s was a massively
inflated 47%, whilst New York, as we see, saw a
reduction of 20%. This amounts to one in every
five prisoners being released without being
replaced.
New York certainly ‘bucks the trend’.
Compared with the national pattern, it is an
anomaly. But does it prove anything in general
terms? The answer has to be no.
Generalisations drawn from particular cases
are always questionable, as you will recall from
discussions earlier in the book (see Chapter
2.10). Anomalies, likewise, can very often be
‘explained away’ (see Chapter 4.2, pages
140–1), which lessens their impact. In the last
section it was suggested that falls in crime can
have many other causes besides high rates of
imprisonment. New York’s police may have
done a better job than Indiana’s. New York
may have fewer of the social problems that
lead to crime. The fact is that if there are fewer
crimes – for whatever reason – there will be
fewer people being sent to prison and
replacing those who are leaving; so of course
prison numbers will fall. That does not mean
that releasing prisoners lowers crime. We have
the same problem as we had with claiming
that more prison meant less crime.
The problems with Chart 5 have more to do
with what we don’t know than what we do.
For one thing, the statistics do not tell us why
prisoners were released in New York. If they
had simply reached the end of their sentences,
and crime was declining anyway for other
reasons, then the prison population would fall
naturally and have nothing to do with a
deliberate policy to reduce offending. But
what we lack most of all is other statistics for