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*preroll music*

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Herald: Welcome Jeff with a warm applause
on stage. He works for Tactical Tech

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*applause*

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and will talk about a bias in
data and racial profiling

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in Germany compared with
the UK. It’s your stage!

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Jeff: Right. Thank you! Yeah, okay!

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My presentation is called
“Profiling (In)justice –

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– Disaggregating Data by Race
and Ethnicity to Monitor

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and Evaluate Discriminatory Policing”.
In terms of my background:

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I’ve done research, doing
mostly quantitative research

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around the issues of racial
discrimination for a long time.

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In New York, at the Center for
Constitutional Rights I was working on

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looking at trends and levels of

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use-of-force by police against civilians,
and also on stop-and-search

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against civilians. And then more
recently for the last 18 months or so

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I’ve been working as a research
consultant at Tactical Tech,

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looking at issues of data politics and
privacy. So this is kind of like a merger

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of these 2 areas. In terms of what this
presentation is gonna be about:

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there’s gonna be 3 takeaways. First, that

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we’re dealing with the issues of privacy
and also [freedom from] discrimination.

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And both are fundamental human rights.
But there’s tension between the two.

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And important questions to think about
are: “When do privacy concerns exceed

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or take precedence over those of
discrimination, or vice versa?”

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Two: That data is political, both in the
collection and aggregation of data;

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but also in terms of having the
categories of being created.

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And then, three: That data ethics are
a complex thing, that things aren’t

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so black-and-white all of the time.
So what is racial profiling?

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The term originates from the US.

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And it refers to when a police officer
suspects, stops, questions, arrests or…

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you know, or… at other stages (?)
of the communal justice system

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because of their perceived
race or ethnicity. After 9/11

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it also refers to the profiling of Muslims
or people perceived to be Middle Eastern.

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And in German there is no direct translation,
so the term ‘Racial Profiling’ (quotes)

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is used a lot in parliamentary hearings
and also in court documents.

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So the problem that we’re gonna talk
about is that because of the lack of data

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in Germany there’s no empirical
evidence to monitor and evaluate

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trends in discrimination.
This is creating problems

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for both civil society in terms of looking
at these levels and trends over time,

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but also from an individual perspective
it becomes difficult for people

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to file complaints. In Germany the only
way to file a complaint officially

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is to go to the police department,
which introduces power dynamics,

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you know, challenges and additional
barriers. But also if you’re an individual

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you have to show that there’s a trend,
right? That you are part of another,

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a long standing story. And without this
data it becomes difficult to prove

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that that’s happening.
So what we’re needing,

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or what some people are calling
for, is having this data

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at a state and a sort of national level.
And this ratio that I’m putting here,

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referring to policing, is looking at the
rate at which people are stopped

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over the census figure of the
demographic share of the population.

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And you really need both; the first
being on the police side and

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the second being on the census. So
that, you know, if you only have one,

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if you only have the rate at which police
were stopping people then you actually

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can’t see if this is discriminatory or
not. And if you only have the census

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then you can’t see that, either.
So you really need both.

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The European Commission, the International
Labour Organisation and academics are all

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calling for these… the creation of
standardized and comparable data sets.

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And I’m not gonna read these out,
but I can go back to them later

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if you’re interested. But what I’m gonna
talk about is comparing the UK

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to that of Germany. So in Germany,

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in 1983 there was a census; or there
was an attempt to making a census.

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But due to wide-spread resentment
and disenfranchisement,

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fears of surveillance and lack of
trust in state data collection

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there was a big boycott. Or people
deliberately filled in forms wrong.

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In some cases there were even
bombings of statistical offices.

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Or people spilled coffee over census
forms to try to deliberately ruin them.

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As a couple of other presentations at the
conference have already said

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this was found to be an
unconstitutional census.

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Because of the way that
they were framing it.

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Comparing the census to
household registrations.

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And so the census was delayed until 1987,

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which was the most recent census until
the most recent European one in 2011.

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This Supreme Court decision
was really important

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because it established this right
for informational self-determination.

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Very important for privacy
in terms of Germany.

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You know, until today. So what kinds
of information is being collected?

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In Germany we have pretty standard kind
of demographic information things

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like gender, age, income, religion. But
what I want to talk about in particular

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is country origin and country citizenship.

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Which are used to determine a person
of migration background. And

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this term ‘person of migration background’
generally refers to whether you,

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your parents or your grandparents
– the first, second or third generation –

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come from a migrant background. Right, and

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this term is used oftentimes as a proxy
for ethnic or for racial diversity in Germany.

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And this is problematic because
you’re using citizenship as a proxy

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for looking at racial and ethnic identity.
And it also ignores the experiences

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and identities, the self identities
of people who don’t fall into

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this ‘first, second or third generation’,
right? People who may identify

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as Black German, let’s say. But
of fourth, fifth or sixth generation.

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They’re just ignored in this
data set. So they fall out.

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Also, it’s difficult to measure these at
a national level because each state

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has different definitions of what
constitutes a migrant background.

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So we don’t have this at a national level
but also within states there’s no way

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to compare them. Of course, not
having that data doesn’t mean

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that there’s no racism, right?
And so in 2005 e.g. we see

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that neo-Nazi incidents have increased 25%

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– the NSU case coming out but still
going on in court proceedings.

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The xenophobic attacks but also the way
in which these crimes were investigated

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– at a state and at a federal level –
and the way that it was botched,

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in addition to showing that
racism now in general

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is at a higher rate than it has been for
the last 30 years. And much more recently

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seeing the rise in arson attacks on
refugee centers. There’s been

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over 200 attacks this year so far.
You know, all of these showed

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that not collecting this data doesn’t
mean that we don’t have a problem.

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So, the UK by comparison: In 1981,
there was the Brixton riots,

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in an area of London.
And these arose largely

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because of resentment towards
the way that police were

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carrying out what they called ‘Sus Laws’.
Or people being able to be stopped

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on suspicion of committing
a crime, carrying drugs,

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having a weapon etc. and so forth.
And so in the aftermath of the riot

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they came up with this report called the
‘Scarman report’. And this found

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that there is much disproportionality in
the way that Police were carrying out

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their stop-and-search procedures.
So for the first time this required…

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or one of the reforms that was
instituted was that UK Police started

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to have to collect data on race
or ethnicity during the stops.

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When they stop a person they have to start
collecting this data. And then you have

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a baseline that’s being established.
Around the same time in the UK

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we have the 1981 census.

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And in society they were having
a lot of debates around

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whether or not they wanted to have this…

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collecting this baseline national level
(?) figure, because we need these 2 things

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for this ratio in order to monitor and
evaluate levels of discrimination.

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But, you know, there was
a lot of opposition to this.

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And many found it to be (quote)
“morally and politically objectionable”.

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But not for the reason you’d think.
People found objections to it

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not because of asking these question,
but because of the way that the question

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was phrased, with the categories that
were being used. And they did surveys

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between ’75 and about ’95, and found that

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among marginalized communities
and in minority ethnicity groups

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there was actually a lot of support
for collecting this kind of data.

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They just wanted to have it phrased to
be different. And so ’91 they started

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to collect the data. They put this
‘race question’ in. And here I have,

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in 2011 – the most recent census –
some of the kinds of categories

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that they wanted to also include.
And they’ve changed over time.

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So e.g. like ‘White Irish people’ felt
that they also were discriminated against.

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And they experienced things differently
than white British people, e.g.

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So having things broken down
further would be helpful for them

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in terms of highlighting discrimination
that each specific demographic faces.

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So around that time ’91, ’93 we
have the murder of Stephen Lawrence

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in an unprovoked racist attack. Nobody
was ever convicted of that. But

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what’s important is that we have this
‘Macpherson report’ that came out.

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And it developed a lot of recommendations,
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One: to be collecting this at a national
level, and to be comparing these.

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In 2011 they stopped mandating
that you had to collect this data,

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at a national level. So none of the
data from then going forward

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can actually be trusted. Some
forces continued to do it,

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but not all of them. So you can’t actually
compare them between forces.

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In the same year we have these London
riots. The Guardian and LSE put out

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a report called “Reading the Riots”. Where
they did a lot of interviews with people

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who participated. And they found that
most of the people who participated

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had feelings of… that they
were mistreated by Police.

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Or that there is racial discrimination
in terms of the policing practices.

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That they weren’t being
treated with respect.

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So to put some data to that:
Before this was removed

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there… it was 2 different types of
stops in the UK. Those PACE stops,

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where you stops with reasonable suspicion.

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And among that you have e.g. black people
stopped at 7 times the rate of white people.

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Asian people – Asian referring to (?)(?)(?)(?)
Southeast Asian in the UK –

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at twice the rate. And ‘Section 60 stops’:
where you don’t have to actually have

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reasonable suspicion. And when you don’t
need to have that you have much, much

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higher rates. 26.6 times the rate of white
people black people are being stopped at.

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But the State Department even coming
out and they’re saying: “There’s

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no relationship between criminality
and race… criminality and ethnicity”.

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In fact it’s like: If people are being
stopped at these rates it’s…

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it’s in the wrong direction. You have
white males in particular who are

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fending at higher rates. Who are using
drugs at a higher rate. Who are

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possessing weapons at a higher rate.
But that’s not who’s being stopped.

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There is a connection though between
race and ethnicity and poverty.

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So you can see here, they call it like
BAME groups, or ‘Black, Asian and

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Minority Ethnicity’. And you can see
that among like wealth and assets:

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it’s much, much lower for non-white
households. Unemployment rates

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are much higher as well.
Income is much lower.

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So I like making maps. And I think
maps are really cool. ’Cause you can

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tell stories when you overlay a lot
of data with it. So on the left

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I put by different borough in London
where people are actually being stopped.

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Per 1,000 people in 2012.
And on the right I put

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where the crime is actually occurring.
And this is coming from UK Police.

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And so you can see that where people
are being stopped isn’t exactly

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where the crime is actually happening.
And if you’re seeing this stop-and-search

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as a crime preventing tactic then we
have to question why this isn’t lining up.

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Going back to this ratio:

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earlier I mentioned like – having the rate
at which one group is being stopped

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over that share of the total population.

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And we can take it a step further
and we can compare that to…

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between different demographic groups.

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And when using census figures
combined with police figures,

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we can do things like looking on the left.
I mean this disproportionality ratio,

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so the rate at which black groups
as a share are stopped

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versus the total population, compared
to white groups are stopped.

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And you can see the darker areas
is where you have a higher rate.

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So when we’re talking about those
‘7 times, or 26 times more likely’

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these are those areas that we’re
talking about. And so the darker areas:

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you can see that when compared to poverty,

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people are stopped… there’s
greater disproportionality ratios

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in wealthier areas than there are in
poorer areas. And this is kind of

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a way, you could say, almost
of perceiving people of colour

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as others who shouldn’t belong in
these areas. It’s also… you can…

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when combined with other census
information you can see that you have

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more discrimination, you have more
disparities in areas that are more white

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and also less racially diverse.

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So this is kind of all on the
same kind of a message.

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But if it works fine? – It doesn’t.
UK Police is saying that

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at most they have a 6%
arrest rate of all stops.

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And arrests are not conviction rates.

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Looking for weapons we have like less
than 1% of a positive search rate.

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And the European Human Rights
Commission e.g. has called for reform

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of these practices. The UN has called
for reform of these practices.

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And they instituted like
a reform that called for

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having a 20% arrest quota. And so that
could either go positively or negatively.

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Making a higher quota means that you
could be just arresting more people

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that you’re stopping. More likely, or
hopefully it means that you have

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a higher justification or grounds
for stopping a person.

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So these are the kinds of things you can
do in the UK, with these kinds of data.

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In Germany, you can’t. But I wanna
highlight there’s this one case

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in Koblenz in 2010.
There was a student of…

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unnamed, black student who
is stopped travelling on train,

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and who was asked to show his ID.
And he refused. And he said: “No,

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I’m not gonna do that. This is
reminiscent of Nazi era tactics”.

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And so he was charged with slander.
And he was brought into court.

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And the police officer, when it
was in court, said, (quote):

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“I approach people that look like
foreigners, this is based on skin colour.”

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And so this is for the first time
the police have admitted that

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their grounds for doing immigration
related stops are based on

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perceived race or ethnicity.
The judge sided with the police.

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That this was good justification,
like it was good grounds.

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But a higher court ruled
that that wasn’t the case.

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They said: “Yeah,
this is unconstitutional,

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you can’t actually do it,
it violates the constitution.”

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No person shall be favoured or disfavoured
because of sex, parentage, race,

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language, homeland, origin,
faith, religious… etc.

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Just as a side note there’s been a large
movement to remove this term ‘race’

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from that part of the constitution
since it’s been put in.

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And also the court dismissed the slander
charge. They said: “No, this student…”

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like he’s actually able to critique
the police, you know, in this way.

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But after we have the response
by the police union,

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the head of the police union
at the time, who said (quote):

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“The courts deal with the law in
an aesthetical pleasing way, but

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00:17:18,010 --> 00:17:21,760
they don’t make sure their judgments
match practical requirements”.

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And so what this means is: we see
that according to the police union

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– this isn’t official response, but this
is from the Police Union itself –

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they say that we need to
profile. We need to do this.

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Or else we aren’t able to do
immigration related stops.

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That’s crazy. They also…
I mean, at the same time

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00:17:43,470 --> 00:17:46,840
when they were doing these parliamentary
hearings they institute these mandatory

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00:17:46,840 --> 00:17:50,660
inter cultural trainings for police
officers. And these are kind of

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00:17:50,660 --> 00:17:55,210
like a one-day training where
you go and learn all about

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00:17:55,210 --> 00:17:58,650
how to deal with people from different
cultures. But in some of the interviews

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that I was doing they said: “Okay, well,
this isn’t an inter cultural issue.

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This is a racism issue”.

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People aren’t just coming from other
places. These are Germans,

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00:18:08,250 --> 00:18:11,000
these are people who grew up here. These
are people who live here. Who know

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how to speak the language.
Who were born and raised…

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And we need to be dealing
with this in a different way.

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However, in this time, we see that
racial profiling has become part of

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the national conversation. And so this
is the sticker that somebody put up

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in Berlin, in a U-Bahn.
It says: “Attention…,

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we practice RACIAL PROFILING while
checking the validity of your ticket”.

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It’s not real, but it looks…
I think it’s kind of cool.

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When they were doing this in
these Bundestag hearings…

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they released data for Federal Police
for 2013. This is the first time

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00:18:50,260 --> 00:18:54,270
that we have any data that’s released.
No data has ever been released

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based on State Police stops.
They say that they’re not actually

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collecting the information, so they
don’t have anything to show. Of course

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00:19:01,010 --> 00:19:03,960
the figures that are released from the
Federal Police are not disaggregated

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00:19:03,960 --> 00:19:08,000
by race and ethnicity.
But what does this actually show?

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So, most of the stops,
over 85% are border stops.

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Border being within ca. 30 km
of the German border.

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So this is actually taking into account
most of the German population.

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But if we’re doing these immigration
related stops then… if we break it down

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by offense – in the last two, these are
the immigration related offenses

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that people are committing – and
we have less than, at most,

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maybe 1% of people who
are found to be a positive,

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meaning that they’re found to be violating
some kind of offense. It’s – again,

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it’s not a conviction, right?
And people can challenge this.

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00:19:53,930 --> 00:19:56,550
E.g. like you don’t have to have your
ID on you in all times. You can

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present it later, and the
charge can go away.

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00:20:00,470 --> 00:20:05,080
But if we have such low
rates of positive searches

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then like why is this happening? Why
do we feel that with such good data,

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00:20:10,980 --> 00:20:18,950
and knowing, as good researchers,
why are we continuing this as a practice?

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On one of the other interviews that I was
doing they found that okay well:

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You know, we know this is ineffective.
But this has the effect of criminalizing

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00:20:26,470 --> 00:20:31,550
our communities. And
whether or not this is true

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is an argument for why we should maybe
have this kind of data to show that

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00:20:35,130 --> 00:20:41,220
this is or is not actually occurring.
Of course, European Commission

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00:20:41,220 --> 00:20:46,490
against racism and intolerance and the UN
have said: “Well, even among this at most

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00:20:46,490 --> 00:20:50,021
1% positive rates these are
not being distributed evenly, and

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00:20:50,021 --> 00:20:53,700
you have people of certain groups that are
being stopped at rates higher than others,

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00:20:53,700 --> 00:20:58,870
particularly black and other
minority ethnicity groups.”

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Okay, so, going back, why…
into the initial question…

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00:21:05,670 --> 00:21:10,670
If we have both freedom from
discrimination and the right to privacy

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00:21:10,670 --> 00:21:15,930
as these human rights how
do we address this tension?

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00:21:15,930 --> 00:21:18,270
And how do we make sure that we’re
making the right decision in terms of

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00:21:18,270 --> 00:21:23,440
which takes precedence? And so I came…
or I’ve thought of 3 different reasons

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00:21:23,440 --> 00:21:27,690
why this isn’t happening. The first
being a series of legal challenges.

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00:21:27,690 --> 00:21:31,740
Things that are preventing
us from implementing this

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00:21:31,740 --> 00:21:36,400
from a legal basis. And the first…
you know there’s 3 exceptions

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00:21:36,400 --> 00:21:39,240
that would allow for this
data to be collected.

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(1) The first being if there’s a provision
in EU directive that calls for collecting

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this kind of a data. And within that
(2) if you have the consent of the person

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the data is subject, let’s say.
Consent is kind of a difficult thing

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and we could have a whole conversation
just about that on its own.

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00:21:57,970 --> 00:22:00,950
If you’re being stopped by police officer
to what extent can you actually consent

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00:22:00,950 --> 00:22:06,660
to the data that’s being collected?
But this is put in place

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00:22:06,660 --> 00:22:10,510
as one of the mandatory
legal requirements.

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00:22:10,510 --> 00:22:16,050
Or (3) if there’s an exception in
the hopefully soon to be finalized

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00:22:16,050 --> 00:22:19,460
EU Data Protection law that
allows for collecting data

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00:22:19,460 --> 00:22:23,020
if it’s in the public interest. So you
could argue that we need to be collecting

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00:22:23,020 --> 00:22:28,920
this data because monitoring
and evaluating discrimination

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00:22:28,920 --> 00:22:34,480
is a problem that we need
to solve as a society, right?

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Two: As a lot of people here at
the conference are talking about:

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there’s a lot of distrust in terms
of collecting data by the state.

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Particularly sensitive data. But I mean
as many of us are already aware

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this data is already being collected. And
this doesn’t mean that we should maybe

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00:22:53,520 --> 00:22:57,680
collect more just for the
sake of collecting data.

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But in terms of sensitive data –

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00:23:01,460 --> 00:23:04,990
we’re collecting things also like medical
data. And medical data sometimes

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00:23:04,990 --> 00:23:08,720
is interesting for looking at trends
in terms of the illnesses,

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00:23:08,720 --> 00:23:14,850
and where illnesses spread. And you can
look at this as also possibly a way of

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using sensitive data for highlighting
and monitoring public problems.

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00:23:21,130 --> 00:23:25,150
And, (3), we have these
challenges in determining

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00:23:25,150 --> 00:23:29,060
which kind of categories
we should put in place.

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But, like the UK, if something
were implemented in Germany

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00:23:32,890 --> 00:23:37,090
I feel as though this would change over
time as other groups also want their data

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00:23:37,090 --> 00:23:43,490
to be collected… or not!

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00:23:43,490 --> 00:23:48,400
So that’s kind of where
I’m at. I think that

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00:23:48,400 --> 00:23:51,480
there are no easy answers in terms of
whether we should or should not do this.

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00:23:51,480 --> 00:23:53,670
But I think that at the very least
we should be starting to have

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00:23:53,670 --> 00:23:56,500
these conversations. And I think that
it’s important to start having these

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00:23:56,500 --> 00:23:59,440
conversations with communities
themselves who are being targeted,

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00:23:59,440 --> 00:24:05,060
or feel they’re being profiled.
So, thank you!

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*applause*

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00:24:16,320 --> 00:24:20,420
Herald: It was an awesome talk. I think
there might be 5 minutes for questions.

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There are mics over there and over
there. And whoever has a question,

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00:24:24,620 --> 00:24:28,140
like in the front rows,
I can come walk to you.

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00:24:28,140 --> 00:24:30,980
Question: Thank you very much.
I’m just wondering in terms of…

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00:24:30,980 --> 00:24:33,370
are you sort of creating this…

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00:24:33,370 --> 00:24:34,690
Jeff: I’m sorry, I can’t hear you…

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00:24:34,690 --> 00:24:37,260
Question: Sorry, of course… I’m sort
of curious in terms of how you’re

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00:24:37,260 --> 00:24:40,990
creating the disproportionate demographics
where there will be birth, including

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00:24:40,990 --> 00:24:44,520
other kinds of information, such as sex,
age, time of day they’re stopped.

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00:24:44,520 --> 00:24:46,300
Because there’s possibly
unemployment bias as well…

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Jeff: I’m sorry, I still can’t
actually hear you.

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00:24:47,830 --> 00:24:52,510
Question: Sorry… whether it’d be
worth including, say, other details

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00:24:52,510 --> 00:24:56,350
about people, such as their sex, their
age, maybe the time of day that

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these stops are happening. As there may
be a bias towards the unemployed.

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If that’s possible, do you think,
with the UK census data?

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Jeff: So you’re asking: Do I feel as
though we should also be including

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00:25:10,350 --> 00:25:15,090
other kinds of demographic data?
Yeah. I mean I do, but I think that

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I shouldn’t be the one who’s deciding how
to implement these programs. And I think

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that we should be speaking with
the communities themselves

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and having them give their opinion. So if
this is something that those communities

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who feel that they’re being targeted
or being discriminated against

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00:25:30,260 --> 00:25:33,800
want to include then I think that they
should be taken into account. But

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I don’t know that I should be
the one who’s deciding that.

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Herald: Okay, next question
over there, please.

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00:25:40,980 --> 00:25:45,230
Question: To this ratio you’ve been
talking about: So you compare

356
00:25:45,230 --> 00:25:49,530
census data to – as you
said in the definition

357
00:25:49,530 --> 00:25:53,510
in the first slide –
perceived ethnicity or race.

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So it is an attribution of the
persons themselves in a census

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compared to attribution per
police officers. And those

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00:26:01,730 --> 00:26:05,490
won’t necessarily match, I’m not
sure. So I was just wondering

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00:26:05,490 --> 00:26:08,980
whether you could comment on
that a bit. And this is related

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00:26:08,980 --> 00:26:13,130
to the second question when it comes
about: We don’t get this data

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00:26:13,130 --> 00:26:17,600
maybe from the police, because it’s
difficult for the state to collect it.

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00:26:17,600 --> 00:26:21,560
But maybe we could get the data from
those which suffer from discrimination

365
00:26:21,560 --> 00:26:25,830
in the first place. So do you see any
possibility for public platforms…

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00:26:25,830 --> 00:26:29,930
So I was reminded of this
idea from Egypt, HarassMap (?)

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00:26:29,930 --> 00:26:34,140
which is about sexual harassment
of women. That just made visible,

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00:26:34,140 --> 00:26:37,710
with maps, similar to what you do,
actually where this happened,

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00:26:37,710 --> 00:26:42,860
when this happened, and how this happened.
But it’s been the people themselves

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00:26:42,860 --> 00:26:46,700
speaking out and making this
heard. And I was wondering

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00:26:46,700 --> 00:26:51,600
whether that may be another source of the
data you would be needing for your work.

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00:26:51,600 --> 00:26:55,750
Jeff: So the first question was talking
about whether we should be using

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00:26:55,750 --> 00:26:58,640
‘self-identified’ vs. ‘perceived’,
right?

374
00:26:58,640 --> 00:27:02,280
Yeah, I mean they may not line up, right?

375
00:27:02,280 --> 00:27:06,470
People can be perceived in a way
different than they identify.

376
00:27:06,470 --> 00:27:10,450
Some groups in Germany
are calling for both.

377
00:27:10,450 --> 00:27:14,500
They’re calling for kind of like
a two-ticket mechanism

378
00:27:14,500 --> 00:27:19,750
where you have people who
put how they self-identify

379
00:27:19,750 --> 00:27:24,040
and also how the Police are identifying
them. If we’re looking for patterns

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00:27:24,040 --> 00:27:27,580
of discrimination then it may actually
be more interesting if we’re looking at

381
00:27:27,580 --> 00:27:31,580
how people are perceived.
Then, how people self-identify.

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00:27:31,580 --> 00:27:35,520
But I think it’s important to take both
into account. And for the second question,

383
00:27:35,520 --> 00:27:38,170
I’m sorry, I kind of forgot what that was.

384
00:27:38,170 --> 00:27:42,010
Question: Like asking the
people themselves for data

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00:27:42,010 --> 00:27:45,770
when they suffer from discrimination
or [are] being stopped more.

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00:27:45,770 --> 00:27:49,790
Jeff: Yeah, no, I mean I think that’s a
great idea. And there was a survey

387
00:27:49,790 --> 00:27:53,890
that was actually just done,
that was doing just that!

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00:27:53,890 --> 00:27:57,200
The findings haven’t been released,
but it just finishes up. And it’s looking

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00:27:57,200 --> 00:28:01,370
at different types of experiences of
discrimination that people are having.

390
00:28:01,370 --> 00:28:05,600
There’s also organisations like
social worker organisations

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00:28:05,600 --> 00:28:08,730
that have been collecting
this data for a long time.

392
00:28:08,730 --> 00:28:14,420
Having hundreds and hundreds
of cases. Yeah, thanks!

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*postroll music*

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