The Sex Myth: Why Everything We're Told Is Wrong (14 page)

Calculating the change in rate from one year to the next gives us the percentage change, be it a rise or a fall. The change in rate from 1999 to 2000, or the change from 36.8 to 43.4, is a 17.9
per cent rise.

That is considerably different from 50 per cent. So the rate (which is what counts) of rapes in Camden did not go up by 50 per cent after the lap-dancing clubs opened. If you include the even
more modest increases in 2001 and 2002, you still come up with a result that is nowhere close to the Lilith reports original claim. The combined change from 1999 to 2002 is a rate increase of 26.9
per cent – in other words, about half of what was claimed.

So, not only did the papers take six years to correct the error in the Lilith report, the media didn’t even get it right the second time around. But the story doesn’t end there.

Even more important than correcting the errors is trying to get things right. For example, one might try looking at the longer-term trends. Rapes might go up one year, or two, or three . . . and
they might fall the next. It’s kind of like all the discussion around climate change: you can’t tell from one year, or two, or even three what is happening on a long-term scale. There
are natural fluctuations that can mask the overall trend. The more data we have to analyse, the more accurate the results. The more accurate the results, the more informed the reporting.

A problem common to dealing with small numbers is making a hasty generalisation. This is a fallacy that happens when someone makes a large conclusion based on a small sample of evidence, such as
an initial result that disappears later, when more data are collected.

Here’s an example of a hasty generalisation: let’s say you’d never been to York before, and went there for a five-minute visit while changing trains. Let’s also say that
while in York you saw exactly three people – all of them with red hair. It would be a hasty generalisation to then go around saying that everyone in York is ginger. And yet, given the very
small number of observations, saying so (while obviously not true) would not be a contradiction of the evidence you collected.

Small numbers are a problem in statistics, because the less information we have, the less we can reliably say about it. Dealing with this problem means having to collect
more evidence where available, making pertinent comparisons, and applying more than just simple arithmetic. Reported rapes are relatively rare, so writing about rape statistics requires special
attention.

Now, just because a crime is rare doesn’t mean it isn’t serious. Rape is extremely serious. No matter how many people are raped, it’s too many. One rape in the course of a year
would be a tragedy; 72 is obviously a problem.

It’s also important to find out whether the rate was a one-off, or whether the rise implied in the Lilith report was sustained. So let’s calculate rates, but this time for a longer
timespan. We know that between 1999 and 2000 the rate of reported rapes in Camden rose. But did the trend continue? Have a look at the results:

The change in rates fluctuates a lot on a year-to-year basis! Surprised? Actually, that’s another feature of dealing with small numbers. Because the event is uncommon, a
few incidents either way have more power to change the trend. Which is why percentage change for a couple of years, even if a lot different from what was originally reported, is not a good
indication of what is really happening. (Or, as I like to say, more years equals more better!)

But, without the trend, the door is left open for people to misinterpret the statistics in a way that could be sensationalist and scary. As an example, let’s say
there was one death due to vending machines falling over in Glasgow in one year, and then two the next. Irresponsible reporting might say, ‘Vending machine deaths double in one year!’
Technically, that’s true – but it misses the spirit of what is really going on. It makes people think the risk of being squashed by a vending machine is going through the roof, when in
fact there aren’t many incidents of this kind at all . . . and there might be fewer next year.

If we graph the rates, we can see if the trend is rising, falling, or staying the same. The years covered in the Lilith study are highlighted by the thick grey line:

Rapes per 100,000 in Camden, 1999–2008

For the ten years 1999–2008, it appears the trend for rate of reported rapes in Camden is actually falling, not rising.

Another problem with the original paper is a lack of an appropriate control population, with which to compare the results. Having a control population is particularly important in assessing
risk. Controls are populations where the thing you want to test – strip
clubs, in the case of the Lilith report – doesn’t exist, for comparison purposes.

The report makes comparisons between Camden, Westminster and Islington, all of which contain lap-dancing clubs. As far as control populations go, that’s no good: you need somewhere where
there are no lap-dancing clubs. Kind of like a placebo group in a medical trial.

For instance, in order to suggest a link between smoking and lung cancer, the original epidemiologists had to examine lung cancer rates not only in smokers, but also in non-smokers. You need to
show that the factor being examined – smoking, or in our case, lap-dancing clubs – is the influencing factor.

The lack of a control group means that the numbers of rapes in Camden were not reported against the rape stats in an area with no lap-dancing clubs. It’s perfectly possible that the trends
happening in Camden were happening everywhere, regardless of whether there was lap dancing or not. It’s impossible to know from the Lilith study if other parts of London were experiencing
similar trends in their crime rates.

It’s common sense that local problems require local solutions. What goes on in one part of London could be completely different from what is happening somewhere else. When it comes to
serious topics like sexual assault, rape, and similar crimes, it’s vital to recognise the factors that can vary from place to place, and over time.

So, let’s run the statistics using Camden, one of the other areas the report uses that does have strip clubs, and an additional area that has none at all. Because crime can be influenced
by factors such as poverty, the area should preferably be of a similar demographic profile. Then an assessment of the occurrence of rape in that area can be made, for comparison’s sake.
Without doing this, it’s impossible to say whether any trend was locally concentrated or happening everywhere regardless of strip clubs.

Lambeth has a somewhat larger population than Camden and similar make-up in terms of ethnic origin. It contains no lap-dancing clubs at all. Islington has a somewhat smaller population than the
other two boroughs and has two venues licensed for fully nude lap dancing. And since these statistics are also available
for the entire country, let’s throw them in too.
After all, the original claim was that Camden’s rape stats were
three times the national average.

Comprehensive statistics are available for crimes reported to police throughout England and Wales, so these are straightforward to add. They also provide a useful baseline for what the national
averages are. Now, the graph of those data. Again, the years covered by the Lilith paper for Camden are highlighted by the thick grey line:

Rapes per 100,000 in Camden, 1999–2008

The graph shows that adding comparison changes the picture considerably. It no longer appears that lap-dancing clubs lead to an increase in rape, since boroughs with fewer or
no clubs had consistently higher rates than Camden’s. The data from the original study is shown to be a small blip in a larger – downward – trend.

If there was were a relationship between the number of lap-dancing clubs and the occurrence of rape, you would expect the rates of rape in Lambeth to be lowest of the three because it has no
clubs. The rates in Islington would be higher because it has a couple, and Camden would have the highest rates because it has more than those other boroughs. But Camden turns out to be the lowest
of the three. There does not appear to be any relationship between the number of lap-dancing clubs in a borough and the risk of rape.

Apart from the early 2000s peak, Camden’s numbers are close to the overall rate for England and Wales, and are sometimes even below it. This is a far cry from the ‘three times the
national average’ claimed by the Lilith report.

The trend for the three London boroughs shows clearly that Lambeth (with no lap dancing) and Islington (with only two clubs) both have rates that are higher than Camden’s. All three have
decreased over
time, as well, which is why it pays to look at the longer trend rather than cherry-picking a few years.

There’s a dangerous culture of assuming we know the answers before the research has even taken place. This is how cargo cult science becomes less an unusual anecdote
about Pacific islanders, and more a real and relevant force in forcing policy change.

All things considered, you might wonder why the Lilith report chose to look at Camden at all. According to the introduction, it was because ‘Lilith and Eaves believe that Camden’s
opinion and acts carry great weight with other London boroughs.’ Which, if you consider that there are no references or other reasons given, doesn’t make sense.

If we were to take the graph on the previous page as our only evidence, we might conclude that the risk of rape goes up not in areas where there are lap-dancing clubs, but in London, with Camden
actually safer in that regard than other boroughs (and, in some years, safer than the rest of England and Wales on average). We might also be tempted to conclude that the presence of lap-dancing
clubs in fact indicates a safer borough in terms of rape.

Naturally, that would be a very rash conclusion, and something a responsible statistician would be reluctant to suggest. It would require far more data from the rest of London and the entire
nation before such an idea could be suggested. But that’s the point – in order to make a conclusion about the effects of social phenomena in general, you need a huge amount of
information to back it up. I’m not going to claim lap dancing makes places safer. My remit is to point out it categorically does not make them less safe. It could be a beneficial influence.
It could also be not at all related to crime. One limited study of a crime statistic is not enough and should never be allowed to stand on its own.