Mapping Crime – A sort of lesson plan.
A big thanks to my colleague Jim for his posts on crime stats.
This put me in mind of a lesson which I’ve used to evaluate Shaw and McKay and the Chicago School’s
approach to crime and deviance. I’ve not written it up in strict Ofsted, PGCE style with aims and
objectives, but I hope it can give teachers enough of an idea of what I have done in the past. I’m sure
loads of you will be able to adapt, modify and improve on this. I always found that students seemed to
enjoy it – especially the colouring in bits and the looking stats up on the computer. This also seemed to
make the evaluation bits come pretty easily to them – it also helped that quite a few of them had some
knowledge of London.
Remember, Shaw and McKay argued that crime rates were highest in inner city areas because these
formed a ‘zone of transition’ – an area where there was a high turnover of population, people didn’t
know each other and lots of rented properties. Shaw and McKay argued that these factors meant that a
high level of what they termed ‘social disorganisation’ ensued, leading to high rates of crime.
Briefly, Shaw and McKay argue that the further you move out from the ‘zone of transition’ – situated in
the central business district (CBD), the crime rate falls steadily.
I’m skimming the details – you can check them up in most sociology textbooks.
I would point students to focus particularly on the key indicators used by Shaw and McKay. Consider
also how the concept ‘social disorganisation’ is operationalized ( I flagged this up early on and asked
them to reflect on it during the activities).
Now, wouldn’t it be nice to test this old, old, theory? The answer is ‘Yes’.
You can obviously use the stats sources highlighted by Jim yesterday – however, I always like using used
the stats from London for this, even when I was teaching in Cambridge. Clearly if you are in a big city
elsewhere in the country, you can use figs for that.
So the lesson can proceed like this:
Get students to download a map of the London boroughs
Now go to the Metropolitan Police Website:
This last link will take you to the crime figures for each London borough.
I used to get students to use the most recent month’s figures. Write in the number - in rounded ‘000s or
if you want, get them to turn it into a percentage of crimes - in each borough (use the two maps to
work out where the figs go).
You will then find that you have a map filled in with crime stats for each borough.
Then try to colour code your map. To do this, you need to look at the numbers and group them
into about four bands, e.g. there might be a fair number of boroughs with between 15 and
18,000 crimes per month, so make that one band, allocate it a colour, and so on.
Once you have sorted the bands out, give each band a different colour or shading pattern.
Now it’s a bit like primary school again – shade in all the boroughs in the same band and do the
same for each of your four or so bands.
What they should have at the end of this is a map of London (or wherever), shaded in about four zones
which reflect the levels of crime in the difference boroughs.
And oh, yes, don’t forget to fill in a figure for the ‘square mile’ – the City of London. You can find stats
for the City here:
Now, back to the sociology.
Examine your map carefully. You (the students I mean) may notice it is rather similar to
diagrams from Shaw and McKay’s research which are in many textbooks.
My question is this:
Does the evidence of your map and the recent crime figures, support or refute Shaw and
Get the students to brainstorm this and think about indicators and operationalisation.
I’ll just sketch this in. My classes invariably found, surprisingly perhaps, that the London data in fact
generally seemed to confirm Shaw and McKay’s findings from 1930s Chicago. The highest levels of
crime were in central London boroughs like Westminster and as you moved out, crime rates generally
There were a few anomalies however, and we used these to develop a critique of Shaw and McKay.
The ‘hot spots’ in outlying boroughs were invariably in high street areas.
And there was also a much lower rate in the City of London
This led us to focus critically on the indicators used by Shaw and McKay.
Arguably, defining a CBD in a large conurbation like London is not straightforward. There are in fact
many CBDs spread throughout different boroughs. Where do you draw the line? This is an issue of
operationalisation – explain this to your students.
Secondly, the fact that the highest levels of crime occurred in a central borough like Westminster led my
classes to make the criticism that crime in fact seemed to ‘follow the money’ - here you need to know a
bit of London geography, but the boroughs of Westminster and Camden just happen to include the big
shopping areas of Oxford Street, Regent Street, and Camden Market. And of course, it’s not a
coincidence that these areas get the lion’s share of police attention. Also, whenever there are any big
public protests (and consequence arrests) they happen here.
So can these insights provide any fuel to criticise Shaw and McKay?
My students said ‘yes’ (they were well trained). Recorded crime rates do reduce as one moves from the
centre of the city, but that does not mean that there is little crime going on in other areas. It depends
what sort of crime you are referring to and measuring.
The City of London force does its best with fraud and so on, but of course, sociologists can make the
point that detecting white collar crime is complex and time consuming. Can we really trust the evidence
of the figures in this exercise? Isn’t it just possible that rather more’ crime’ is occurring in the City than
the pretty maps indicate?
And equally, lots of white collar crime or other crimes could be going on behind closed suburban doors.
We therefore concluded that what such maps reflected was not the ‘real’ incidence of crime, but the
reporting of crime and the level of police activity.
‘Social disorganization’ is a highly value-laden concept. Just because an area has a high turn over of
population, lots of rented properties and so on, it does not follow that it has a high crime rate. And in
boroughs like Westminster and Camden, there are plenty of other indicators which need to be
considered as well.
Such maps were not therefore ‘valid’ representations of the true level of crime in the city. The high
levels of crime for Westminster for example, could be explained by the preponderance of shopping
areas in that borough, making an nice, juicy target for certain types of criminal.
Finally, it’s worth noting that crime mapping is becoming very important and indeed popular these
days. It’s popular with police forces and with local and national politicians. But it may well be that there
are ‘political’ reasons why agencies and officials like to put resources into this venture. They are not
without their own interests in the matter. That is not to say that mapping crime presents us with a lie –
but it may well reflect only a part of the truth and thus distort our understanding of crime.