This hour. Been wary quickly, too.
So we're going to take just a few minutes on maybe
if there are questions from the audience For now,
I don't see any hands up, but maybe
some people would like to intervene
Let's wait a few seconds.
Yes, I see one person.
Alex,
please If you could try to be brief
and then we'll have time to react.
I'm sorry.
I just
it's right.
Thank you to all the speakers.
It's raised so many different
issues and questions, so I've only got time for comment.
Maybe one.
And I just wondered
whether one or several of the speakers could comment
on the challenge of responses to two different men's health surveys.
Different surveys.
And how do we get over that?
Potentially the perceived perceived fears of of data misuse.
And and so in terms of
when people are answering surveys, you know,
the potential feeling of intrusion into private lives and so on.
So something about how the data is collected.
Emily, you sort of hinted at that in terms of
the way said certainly the Office for National Statistics works.
But I wonder, given the sort of global context of this conference,
whether some of the maybe some of the other speakers
might like to say a little bit about that
Okay.
Maybe while we're waiting to see if there's other questions.
One of the ones I had was that
you drew a very complex picture of what is happening of the implications
of the data revolution and how all of this is affecting your work.
So my question is,
if we have to transmit some very clear messages to students.
So, for example, in the future for somebody going into the sector
or who wants to work?
What would be the one scale or the one most important point
that they would have to, I don't know, think about or training themselves?
Because we saw that you have to be a statistician somebody who specializes
in, who knows, like in social sciences, but also sometimes
a lot of
technical skills that you need to know about.
So, yeah, how what could we say to students today
how to deal with all these new changes
Let's see if there's other questions
for now. No.
So, yeah, maybe if if there's no questions, maybe you could
each react in two in a couple of minutes and
yeah. Thank you.
We can go in the same order
or maybe we can start from the end with Emily and go up.
Emily, would you like to react to what was just said
Sure.
I mean, on the question of household survey responses,
I mean, this is a big challenge all over the world.
And I think the approach that
NASA has taken is to kind of stop from ensuring the frameworks
are as solid as they can be to prevent any misuse of data,
to ensure that data is used in an ethical way to ensure that people's
data is protected and really put that at the heart of everything that we do
and raise awareness of that fact.
But it's a very partial answer to your question.
And I think in terms of in terms of skills
that that people working in development need to have,
I think recognizing the importance of using data and recognizing
when there are opportunities to use innovation to improve the data
that's available
but continually having in mind the kind of need to do that
in a systematic and supportive
way, that's going to build the data ecosystem in that country
rather than kind of silos of separate innovation
and blooming many flowers, separate innovations.
I think just having having those those things in mind as you
as you carry on in your work are both really important.
Thank you very much, Emily. Dr..
A really Hepburn hat as a. Doctor
and would you like to answer this question.
Next I know you like especially.
When it's your company.
Yes. The question was a little bit about.
The mix having.
This complex panorama with so many players involved
producing data which. Are.
Held by different people.
So what are the scales, the competencies required?
What single message could you possibly send out to students nowadays?
Who wish to work in this sector?
Do the well,
given that currently
there is a great challenge
ahead of us in social sciences, for instance,
a program
because projects and programs
and research institutions need to be able
to use all of the tools we have available to us.
Regardless of the project.
Diagnosis, assessment monitoring.
Is important because.
All of that is extremely important
and this should be applied to the entire project as a whole.
To do that, we need statistics
that allow us to perform these assessments.
Schools and research institutions
have to help make this understand more.
As well as having this ability
to use technological tools,
statistics need to be available to everyone in this day and age.
And see.
That it should not be necessary to be,
for instance, a mathematician to produce these statistics.
If it should be just like using a mobile phone, it should be easy
to understand the logic behind these technological tools.
Let's move on.
Thank you for sharing a bit of optimism with the students.
Amy, would you like to react to what was just said?
Yeah, just just a quick reaction and on both of the issues.
The first one raised by Mr.
Machado, I mean, when it comes to Oxfam and given
that that the research that that we do
often
takes place in the global south in settings characterized
by poverty, by shrinking civic space
or limited rights, infrastructure,
fragility, insecurity,
or even I mean, we do
this kind of research under the watch of of of repressive governments.
I mean, that's why we have developed.
That's why we have developed different research guidelines in order
to support ethical research to set up these ethical research principles.
And how to put this this these principles into practice.
And that that refers to the anonymity
and the way we collect the data, how we design
a research that is ethical how
we conduct inside of different risk analysis.
And this is something that that we take a lot of consideration
when it comes to our approach in different settings.
And also, I mean, on your question, Tatiana, I mean,
I would like to raise this this issue and how
I see my position here that I need to transform data into knowledge.
So when it comes to what are the kind of skills that
that organizations like like they cause we need, I mean,
is it a very varied and different set of skills?
Because, I mean, first of all, we need to know we
we need to have the skills to understand what we are measuring,
what is the data that we have in our hands.
What are the limitations and what they are so in.
And that for this to happen, I mean, we need a center certain
the specific skills we are talking about like economic data.
I mean, we need people that get to know
what are the foundations of those concepts.
So if we if we are talking about sociological data
and then we need people that gets to know
or the specifics of the data, what are the limitations are?
But then beyond that, I mean,
I mean transforming data into into knowledge and information.
I mean, at least, for example, that Oxfam,
we have very creativity people that they are able to
to to basically condense very complex things into an amazing graphic.
I mean, we we are aware that people do understand
more than one minute over in front of the computer watching the video.
So we need to be like we need we work with people
that they are really really good at
coming up with what are the clear messages and things like that.
So I mean, the variety of skills are
I mean, we need people with different skills.
But with this idea of making sure that that data is used for
something that works is for influenza and for campaigning and advocacy.
Thank you.
All right.
Great.
Thank you very much, Rafaela.
Hey, very quickly, also on a positive note,
to students, I would say that they are the more and more needed
in development processes because as we have said,
there is a
bigger proximity
between those who are able
in some media with the data collection and data analysis
and those who program and implement programs.
And that, as the colleagues have said as well, we are the less
and less kids, and we feel that there is a a less
prominent disconnect or in any case, speak for them to disconnect.
And we understand better what
is demographic to say when when they talk to us
about this phenomenon, we we have the ambition to act on.
What I would also add is that very quickly on the
on the impact assessment, we will not will not go into the details.
It is just that we have
an enormous pressure on our shoulder to prove
that what we are doing in terms of development has an impact
and that the territories where we do not intervene on
or the areas where we do not intervene on, they experience
bigger problems rather than those where we intervene.
So we are in more the more and more push towards new methodologies
like such counter-factual impact assessment evaluation
with enormous amount of data to be collected in areas where
development actors intervene in areas where you to intervene.
So there is really an important window of opportunity
for those who study statistics and demography
to to really contribute
to better define these assessment tools.
This results and impact assessment tools and
talking about training to help us to learn
how to how to better use them
Great.
Thank you very much, Rafael.
And our last speaker is Bill.
Very quickly on household surveys,
I mean, I think the one thing is that the work
that's being done on privacy and confidentiality
now is I mean, there's a lot of work going on.
It's really important to finding the balance between getting out
useful data and respecting people is important
in terms of what how that affects the data.
I mean, we've got very
good examples in the work I'm doing in Malaysia at the moment.
We were trying to put together data on industry indicator for point two.
Point one, which is about violence against women.
The brand new household survey with the right question asked.
The statistics
people are already saying we are not going to trust this data
because of the sensitivity of the question.
And I think that as Emily was talking about,
about how you triangulate data across various issues.
So what they're looking at is we're looking at the data
from the police
on incidents of violence, looking at data
from the Ministry of Women and Women's Refuges
and trying to match that up against what's coming out of the survey.
That triangulation of data and checking properties against real data
I think is really important an issue of skills.
For me, it is an understanding and respect for public administration
and the civil service.
If people have that, that is development
needs public good public administration and good services.
And that's where data needs to set
All right.
Well, thank you.
If there is nobody answering yes, no more questions.
I would like to say a huge thank you for all the speakers
in this session for these very interesting insights on
how they see their work on how they view the role of data
and all these changes under going in the sector.
And for the students who are listening to us or who will be
maybe watching this video later.
I think one of the
most important messages is, yes, there's a lot of changes going on
and sometimes it's quite compli Lex with more
and more different types of data, more private and public actors.
But I think there's some really interesting messages.
And I just want to point out two or three.
Well, first of all, to work on these issues
and to work with data, we need people with very different skills.
So some that are more technical, some that are more statistical, but also
who have yet we're
also looking for anthropologists, geographers, social scientists.
So there's really room for everybody.
And I think another important message is that yet
even if in the past to work with data or statistics,
you needed to have a mathematical expertize.
Today, there's really a lot of tools out there and a lot of trainings
and a lot of possibilities to
work with data without having, yeah, a PhD in mathematics.
So you really shouldn't be scared but
yeah, just dove on in because there's lots of opportunities
and people who understand the data are
of how it's produced
know about the context in which it produced.
They really have something to bring to to the debate.
So thank you very much again.
For all the speakers.
We're running a little bit of late, but we're still going to have
a two minute pause before we start
the very exciting session with the keynote by Sabina Leon.
So just a two minute pause and then we'll start with the next session.
Thank you very much.