My Authors
Read all threads
I've been thinking more about #stopsearch disproportionality. Thought I'd have a look at Lambeth, which is a borough with v high volumes of SS and lots of youth violence type issues.

1/ THREAD
The MPS #stopsearch dashboard shows SS during Jul19-Jun20 (total n=15,908) focused on males (93%), black subjects (61%), 15-24 yr olds (49%). Peak rate for 15-19 yr olds (309 per 1,000).

2/
Using the @LDN_data GLA 'Ethnic group projections (2016-based housing-led)' I looked at the estimated borough population structure, by gender, age and ethnicity, in 2019.
data.london.gov.uk/download/ethni…

3/
In many ways, it's a tale of 2 populations: those <20 and those 20+. Here's the 2019 popn totals by single year of age and ethnicity. I have highlighted the white (green shades) and black ethnic groupings - the latter incl black mixed race. NB the huge white bulge 20-45yrs.

4/
Lambeth looks to be somewhere young white adults move to in their early 20s, & gradually leave fr their early-30s. By contrast, a significant % of black & black mixed race residents (almost 4 in 10) seem to leave around 19/20. [NB these are popn projections & hence estimates]

5/
Now see how the ethnic profile varies by single year of age, as % of each year. 15-19yr olds are 49.1% black/black mixed race, 20-24 yr olds only 16.3%, the total population 27.6%. Remember the peak rate of #stopsearch is for 15-19.

6/
Takeaway point: the ethnic profile of Lambeth's population varies hugely by age. #stopsearch is concentrated in a v narrow age range, where the demographics are v different to the population as a whole, and even those slightly older.

7/
What's the implication/answer: need age-specific disproportionality ratios and a much more focused discussion about who is being subject to #stopsearch. Unfortunately, the published MPS data don't allow this level of analysis.

8/
For an eg of such analysis, see this report I wrote in 2007 for the Met, looking at the policing of cannabis possn. library.college.police.uk/docs/Policing-…

9/ends
To add: that 309 per 1,000 figure for 15-19yr olds covers males & females. The male rate will be close to 2x that as almost all SS is on males. Can't say exactly how it relates to individs as some will be stopped multiple times, but ~40-50% aged 15-19 stopped in 1yr.

10/
Link to the MPS stop and search dashboard: met.police.uk/sd/stats-and-d… Charts above from the 'searches demographics' tab.

11/
Another reflection: who are the 'faces' the police are most likely to know, and who might be the focus of things like #stopsearch? I'd guess the ones who grew up in and got into offending and ASB in the borough, not the 20s and 30s interlopers.

12/
Nearly forgot to link to the schools census data, which tells a very similar story

13/
That previous tweet is from a longer thread which starts from some personal observations about the bit of S London I live in, including that I don't see many white teenagers there.



14/
Missing some Tweet in this thread? You can try to force a refresh.

Keep Current with Gavin Hales

Profile picture

Stay in touch and get notified when new unrolls are available from this author!

Read all threads

This Thread may be Removed Anytime!

Twitter may remove this content at anytime, convert it as a PDF, save and print for later use!

Try unrolling a thread yourself!

how to unroll video

1) Follow Thread Reader App on Twitter so you can easily mention us!

2) Go to a Twitter thread (series of Tweets by the same owner) and mention us with a keyword "unroll" @threadreaderapp unroll

You can practice here first or read more on our help page!

Follow Us on Twitter!

Did Thread Reader help you today?

Support us! We are indie developers!


This site is made by just two indie developers on a laptop doing marketing, support and development! Read more about the story.

Become a Premium Member ($3.00/month or $30.00/year) and get exclusive features!

Become Premium

Too expensive? Make a small donation by buying us coffee ($5) or help with server cost ($10)

Donate via Paypal Become our Patreon

Thank you for your support!