現 accused say that in our past better and better much does needs deserve to demand and that as you know the focus of today's event is identity in data. Researchers are expanding their focus on exploring how discourses of self and identity and access remain inclusive from the perspective of those populations, communities and individuals. Data collection methodologies are also developing these methodologies are increasingly becoming perceived As significant an impact for search assets in their own right. In these developments in themselves a critical element of the social construction of statistics. of data subjects. Shortly, we will be hearing from researchers and policymakers from UK academia, public and voluntary community sectors. We will hear how they use and gain insight into discourses of representation in data focused on populations, communities and individuals. We do recognise that as the first event in this area, the UK data service is facilitated. We're not able to present all of the characteristics that may be missing from data. We hope the discussion that follows from the event will be just shared with you. Now, I'm delighted to introduce our keynote speaker, Lemsisee. Lemsisee MB is a BAF-denominated award-winning writer, international poet, performer, playwright, artist and broadcaster. He was the first poet commissioned to write for London Olympics and poet of the FA Cup. He's also the Chancellor of the University of Manchester, which is one of the partners in the UK data service. On to our first panelist, who's Dermi Cepardia, now, I started introducing her earlier, but Dermi is a lecturer at the Department of Sociology at the University of Manchester and a member of the SSC Centre on Dynamics of Ethnicity. She was a member of the UK data services first cohort of Data Impact Fellows. She's got expertise in social statistical methods and her main areas of research are ethnic inequalities and health and access to health services. She's also conducted research on ethnic inequalities in the labour market and on the relationships between poverty, ethnicity and gender. Dermi, over to you. I just want to start by saying, wow, thanks to Llan for such a powerful and heart-breaking keynote speech of his journey of finding out about himself, his story and his family in the face of being made invisible in data. Thank you very much for that. Thank you to the UK data service impact team for inviting me to speak here. The past year has seen inequalities in the UK where, in the face of the coronavirus pandemic, inequalities faced by those living in poverty, by women, those working in insecure jobs and not least by ethnic minority people. I've been working on ethnic and racial inequalities in the UK for the past eight years as a member of the Centre on Dynamics of Ethnicity, led by the University of Manchester and at the moment from a research and data perspective there's a lot of interest in the inequalities faced by minority people and this is more so than before. But when researchers come to look at the data that's available on these groups, what do they find? So the phrase that I used in my blog published by the UK DS impact team last week was represented yet excluded. But another phrase came to mind this morning and Llan's already mentioned it. This phrase comes to mind repeatedly when I think about the experiences of ethnic minority people, both how they're treated in their everyday lives and in data and that phrase is so visible yet invisible. By this I mean that many ethnic minority people are visibly minorities but often their experiences to a large extent are not sufficiently acknowledged and sometimes are completely erased from our data sources. And today I'm going to talk briefly about two research projects that I work on. The first project is about inequalities faced by ethnic minority older people and this is funded by the Nuffield Foundation and this project was born out of the research team's interest in severe disadvantages that this group, these ethnic minority older people face and these disadvantages are often accumulated over the life course leading to worse health and economic circumstances in later life. These experiences that I'm talking about are experiences of racism, poor housing, poor job opportunities. Quite a lot of I think minority older people living in this country came to the UK as migrants and they faced a lot of hardship, a lot of racism, a lot of discrimination when they arrived. So because of our research interests we checked in a number of surveys housed by the UK data base and found that quite a lot of the data wasn't what we wanted, it couldn't answer our research questions. And we found that the number of people aged 65 and over was very low. So not enough to do the kind of statistical analysis that we do as quantitative researchers. So for example there are only 36 Bangladeshi women aged over 65 in the latest wave of understanding society and that's the UK's largest household longitudinal study. In the survey that looks specifically at older people, that's the English longitudinal study of aging or ELSA, there's only 500 ethnic minority people which comprises just over 5% of the sample of the latest wave. So to address these data problems we've pooled a number of data sets, data sets that include ethnic minority boost samples from the period from 1993 to 2017 to have enough people in each of the ethnic categories to do sound data analysis. And this is important because we want to keep different ethnic groups separate and we oppose the use of combining ethnic groups just to provide data on an overarching vein group, a term which I don't like and I encourage people to use to conduct data analysis and use terms ethnic groups distinctively. And I would find and ensure that inequalities in health, ethnic minority older people in this country have persisted for more than two decades up to the present day. The second research project that I'd like to talk about is the evidence for equality national survey or evens that launched last week to document the experiences of ethnic and religious minority people during the COVID-19 pandemic which is funded by the Economic and Social Research Council ESRC. The service being administered by Itsos Mori and can be completed online and on the telephone and we're aiming to recruit 17,000 ethnic and religious minority people. And we're asking participants questions related to racism and discrimination, their health, how their job has been affected during the pandemic, how caring responsibilities have changed and how they've been policed amongst others. And we're using non-probability methods. So this is snowball sampling convenient sampling as you might know it. And really now these methods are becoming more the norm especially during the pandemic for surveys where we can't go out to people's houses. And this perhaps represents the future of large scale quantitative data collection and indeed the ONS expects that 75% of the 2021 census forms will be filled in online. In our survey in evens in order to ensure that we can recruit 17,000 people we're working in partnership with large ethnic minority led volunteering community organisations such as Muslim Council of Britain Operation Black Vote Race Quality Foundation to really get the message out about this survey and encourage people to fill it in. And the innovation of this survey is not only its sampling design, we're also collecting ethnicity in a number of ways. So as Len mentioned in his answer to the question that was posed by an audience member not only providing a drop-down box where people can tick their ethnicity but also including a writing box for people to self-define their ethnicity. So this is new in this kind of survey. It's also the first time in a national survey that we're going to differentiate black African people of sub-Saharan descent on those who are not and it's the first time that Roma and Gypsy traveller populations will be meaningfully represented in such a large national survey. So just to kind of sum up I'd like to say that a lot of my presentation may have come across a little bit critical of the data sources that we have in this country but really a lot of advances have been made towards including and representing ethnic and religious minority groups in surveys. We've seen that there'll be an addition of a Roma category for the 2021 census which is the ONS and this country acknowledging that Roma people in this country do face severe disadvantages. But moving forward we need commitment to collect data to produce database evidence to tackle inequalities and we need this commitment from statutory organisations as well as being a key principle for large scale national surveys in the UK. Thank you. Great. Thank you very much, Jeremy. We're going to move on to the next panellist and at the end there'll be an opportunity to ask questions of all of the speakers so if you could save your questions until we've got into all the panellists who had a chance to speak. So I'd like to introduce Daniel Statsky. Daniel Statsky is a senior research fellow at Jewish Policy Research and Director of its European Jewish Demography Unit. His expertise spans the disciplines of demography, applied statistics in history and he's a former researcher and analyst at the Central Bureau of Statistics in Israel and at Rand Europe. He specialised in Jewish European and Middle Eastern demography with over 20 years of experience and a long publication record in those fields. Over to you, Daniel. Thank you. Thank you very much and hello everybody. I don't have a very long presentation obviously. The limitation is significant. I only have five minutes so I would keep this exhibit in front of you at all times and don't try to go through it in a very detailed way right now. Just relate to it for now as a picture of a person where you basically see three differently coloured fields and I will slowly unfold and explain what they are. It probably it's worth saying from the start that the Institute for Jewish Policy Research which is a body I represent today we are, well as it says as it basically says it tells you only ten way research body we collect not only we collect, we analyse and disseminate statistics and statistically based insights I should call it that about the condition of Jews in Europe and in Britain and this is our core activity. We do that for the sake of Jewish communities global Jewish community, European and British Jewish community but we don't we don't just work with Jewish organisations we work with every single organisation on the planet in Britain that has something to do with Jews and needs data about Jewish people. It's worth saying parenthetically that we are quite an old institution we exist since the 40s we were established in the United States of America actually moved to European soil in the 60s under the conditions of Cold War and since that time pretty much consistently demography and social statistics are our core activities. Now what we do here basically I'm moving to describe our activities with respect to inclusion and solutions around that and our activities are dictated by the essential condition of Jews everywhere apart from Israel and that Jews are a religious and ethnic minority first of all and secondly it's a small minority and that's important so in the data we more often than not display what I call the rarity problem is highlighted on the right there's a box on the right says the rarity problem this is something that dominates our activity in Britain just to give you an illustration Jews are less than half percent of the population and that has implications on how we captured in service if we are at all and the second box the second blue box is another problem if you wish it's an objective problem which I could relate to in minority status not on any particular political sense but as a factual sense being a minority you need to be part of the minority you need to be identified in the sources it's as simple as that not only we want to be identified we need to be correctly identified and not only that we need to be identified and correctly identified but also counted so all of this these are conditions that need to be in a way fulfilled in the middle between these two problems highlighted or issues highlighted and blue which is minority status and the rarity problem that is not going away I listed in a sort of an orange box the sources which contain or should contain or may contain data on Jewish individuals and the sources we work with and there are different degrees of let's say some of them include information on Jewish, some of them don't and some of them include it in the correct form some of them don't include it in the correct form all of that we're trying either to change to introduce or sponsor or lobby for changes in this particular data collection modes that lead to the creation of the sources in such a way that Jewish individuals could be identified in them or we create our own tailored solutions so we create group specific sources or resources which we sponsor ourselves and I will give a few illustrations in that respect so let me give you a few illustrations of how inclusion, what I mean by ensuring inclusion, what we actually do in that respect now a lot of sources today, whether it's administrative data or census or surveys, they rely ultimately on the forms that people fill in questionnaires that are given to people and it's incredibly important obviously in order to create to ensure inclusion of Jewish individuals or any other minority group to simply identify that group to create a response scheme in which people or members of this particular minority see themselves and they simply know how to identify themselves and Jews in Britain, there's a tradition of identifying Jewish people by religion and that works, it works in the context of the census, it doesn't work it doesn't exist in the context of vital registration so while census tells us about how many Jews are in Britain and tells us the truth as far as we can tell the vital registration so statistics of births and deaths doesn't tell us that so that is something to be from our point to be changed and enhanced administrative data sources don't collect information on religion or collect it on insufficient quality of insufficient quality so even if we have this, such as NHS for example it makes it also often it makes it unusable as for the surveys most surveys today I'd say most surveys collect data on religion Jews can be identified but we have a formidable rarity problem on the right where being just half a percent of the population we can't have much hope with respect to surveys that have typical samples of thousand two thousand, three thousand people so we need to literally wait for decades to create a sufficiently robust number of Jews in the survey so this is basically a very schematic description of our activities as I said ensuring inclusion in all of these sources listed in the middle and correcting the deficiencies in that respect when these occur and secondly solving somehow overcoming the rarity problem which is an objective problem that doesn't go away simply through removing non-inclusions through ensuring inclusion still a small minority such as Jews by no means a single minority of that kind need special methods if these people need to be captured in the sources it's either boosting or creating group specific resources a simple inclusion may or may not help so far from me this is the data dance of the institute for Jewish policy research in a nutshell thank you thank you Daniel, thank you very much so we'll move on to the next panellist which is Kevin Guian now Dr Kevin Guian works as a researcher for Advanced HE an organisation that focuses on equality diversity and inclusion among staff and students in UK higher education Kevin is the author of the forthcoming book queer data using gender sex and sexuality data for action which examines the collection analysis and use of gender sex and sexuality data particularly as it relates to LGBTQ people in the UK over to you Kevin thank you great, thank you Gillian and thank you to the UK data service impact team for the invite to speak today so I'm going to be speaking really wearing two hats as Gillian mentioned I work as a researcher for the higher education organisation Advanced HE but alongside that I'm also engaged in scholarship around the collection analysis and use of gender sex and sexuality data as it relates to LGBTQ individuals in the UK so as part of Advanced HE's research team we publish annual statistical reports on the identity characteristics of all staff and students in UK higher education and so our most recent reports published last year last October cover data collected by the higher education statistics agency for the 2018-19 academic year this was information on just under 2.4 million students and 440,000 staff as you can see that was a gigantic data set and what's particularly exciting for someone engaged in equality and diversity research is that this data includes information on a range of different identity characteristics including gender sexual orientation and trans status so my presentation this morning is going to focus on the three strands what we might consider gender sex and sexuality data so it's time and short and rather than consider what data tells us about LGBTQ staff and students I instead want to offer some provocations as to what happens at the intersection where data practices and concepts of gender, sex and sexuality meet for these reasons I'm not only interested in what data says about LGBTQ individuals but I'm really interested in what data how it relates to power and its expression and use in terms of representation I'm interested in how we establish who counts and how this brings some identities into focus while casting other identities further into shadows I'm also going to look at how we acknowledge the data practices are both productive and partial and thirdly how we might use the idea of something I label queer data competence to ensure that decisions about data are made by those who are most affected so firstly the broad question is something we're going to tease out throughout the day the question of who counts so attempts to categorise and establish who counts as LGBTQ means that some people are always left behind those most likely to gain from efforts to tweak data practices so they're more inclusive are individuals who are often closest to the ideal of full equality so in my work is often white middle class cis gay men one example where we've seen this play out quite recently is developments in Scotland related to the design of the sex question in the 2022 census so the next census taking place in 2021 next month in Northern Ireland, England and Wales and the following year in Scotland will for the first time provide an opportunity for people to identify as lesbian, gay, bisexual and trans however the census will not meaningfully count those who identify as non-binary who will still be required to identify their sex as either male or female I raise this example here to show that surface level changes to data practices can actually stifle structural progress and potentially entrenching equality in ways that are sometimes harder for us to tackle Secondly the idea of data practices as something productive and partial this really underscores how decisions made by data producers bring some identities into being while leaving others behind a critical approach data is therefore required to expose the limits of quant data that can test the decisions made during the collection analysis and how efforts to count LGBTQ communities only ever presents one representation of the social world and thirdly the actions of data producers are never neutral and therefore must ask what is being precluded from view for example what is lost when a team of cisgender and heterosexual individuals design questions intended to capture data about LGBTQ lives now it's not practical for those in decision making spaces to always bring lived experiences to the table we therefore need to ensure that those with power can make decisions about data which impacts the lives of LGBTQ individuals are queer data competence so very briefly this requires a basic knowledge of language and concepts associated with LGBTQ identities and understanding of historical and social factors that means the quality of opportunities of fiction and an awareness of power differences both between and importantly within LGBTQ communities so to bring things to an end I presented here some really critical provocations as to the collection and analysis of gender, sex and sexuality data for data producers the design of collection tools didn't arrive as some sort of a historical or a political artifact they are crafted, tweaked and changed to serve the particular interests of individuals organisations or ways of thinking so when engaging in critical studies of data we must deal with multitudes, we can celebrate developments while also reflecting upon what was lost along the way and ensure that we continue to fight to ensure that when data about LGBTQ individuals is collected is used in ways that really improves lives and experiences of those about whom the data relates okay great thank you very much Kevin on to our next speaker who is Craig Moss Craig is the research manager for scope responsible for most of the social research conducted by the organisation Craig has worked as a social researcher for 20 years within research and policy for the third sector and has delivered a variety of research programmes with marginalised and socially excluded groups Craig is passionate about data accessibility research ethics and celebrating diversity and equality for all as well as working for scope he's vice chair of the social care research ethics committee as part of the health research authority thank you Craig very much one in five people in the UK identify as a disabled person yet for such a large proportion of the population it's only relatively recently that disabled people have gained significant equal rights under the disability discrimination act despite this milestone which is celebrated as 25th anniversary last year disabled people continually struggle with the way society identifies them within the equality act 2010 which has now replaced the DDA disabled people are identified and framed by a medical definition basically to ascertain what conditions or impairments that they have and whether their condition affects their day-to-day activities for an extended period and is this application of this definition within the data collection and subsequent policy and research that can be a challenge for identity and the self the definition is inherently a medical model of disability rather than the social model of disability which when introduced revolutionised the way society's relationship to disabled people was framed and empowered disabled people to reframe how they thought about themselves the individual rather than being the problem is disabled by societal barriers environmental, attitudinal and institutional restricting people's ability to live the life they choose furthermore disabled people are often classed as one or larger simplified groups rather than people with individual needs and experiences to be heard there are parallels here to other groups who are also experiencing equality such as the LBGTQ plus community or ethnic minorities communities where in pulling together as a unit to address inequalities society can often perceive each group as an uncomplicated homogenous whole with broad brush often informed assumptions about the individuals within them meaning for consultation is to ascertain the need within these groups is frequently neglected or under resourced which is particularly affecting at government and institutional levels these institutional barriers can continue to perpetuate the way communities experiencing inequalities are measured understood and represented by data and how they are subsequently framed in policy and reports for example could disability rather than being measured as a list of long-term impairments or conditions be framed as an individual's access needs to society so that data can be utilized based on individual need and societal support structures so next slide please I've decided to leave this slide just for time but just wanted to say that coronavirus has exposed inequalities and widening cracks sort of further and it's just great that we have these opportunities to discuss things and debate a bit more and these kind of conversations are starting to happen and we'll obviously bring that up in a discussion sessions later so I'll skip on to the next slide please thank you and here is just an example some of the work that Scope's been doing happy to chat with anyone after the fact and one of the things I'm going to pick on is the disability price tag work and go on to talk a little bit further about some of our co-production work we're doing so the disability price tag research is a good example of where Scope has been able to complete some detailed analysis on a large representative using a large representative data set including disabled people it was an economic analysis to ascertain the estimation of extra cost of disability and equivalent cost of being a disabled person when comparing households in the UK we used the family resource survey from the ONS and through structured equation modern we calculated the extra cost of disability for UK households by comparing the standard of living of those households with disabled people against those without we created a number of indicator indexes our standard of living index which is the diagram there which I just described as a very complicated flow diagram but basically it uses deprivation indicators that covered areas of people's lives such as fresh food access furniture repair and the ability to go on holiday and it allowed us to create a comparable standard of life between households it would have been useful if we could have covered areas important to disabled people as well such as detailed information on transportation or energy use but we married this with identity dependent variables such as social demographics personal details, family size educational level for example and health indicators and on average the monthly cost of extra disability of disability sorry was £580 roughly £580 for disabled people and their families basically the extra cost came from three main areas, higher cost for standard services such as insurance higher usage of standard service such as energy and specialist equipment such as assistive tech and we're now using some of this work to talk to the government about calculators of poverty and about how to inform strategy and policy one of the ways we've also been engaging to work with alongside disabled people in research we've produced and support identity through scope is to embrace inclusivity through co-production across the organisation this supports embedding disabled people's direct input into the process and decision making of moving from the doing for approach to the doing with where we can and firmly embracing the mantra nothing about us without us true collaboration partnership working one such project is where we have recently completed in collaboration with the IHuman Institute of the University of Sheffield exploring social capital of disabled young people the research was conducted by the units co-research collective a group of young social researchers who are disabled people they work with disabled young people to explore key assets and elements of their lives and document their identity and extension of self and independence through their connections with the world around them the findings are yet to be published but following the success of this work scope is now looking to establish its own research collective and produce and co-produce sorry research activities working alongside disabled people as researchers and key informants to address how to identify how disabled people are expressed through statistics presented on scope's website statistics are commonly used to portray people experiencing inequalities disadvantaged to solicit empathy and we want to change this by involving disabled people in our reframing representation project to address how statistics are presented is our ambition that would be more informed about effective and engaging data collection methods how data will be more representative involving people with lived experience and using the accompanying language to frame statistics which disabled people identify with which describes them as people with their own individual lives rather than numbers and that this is inclusive and accessible as possible thanks very much and anyone really that's interested in taking part in this research project either as a researcher or a key informant please don't hesitate to contact me and if you need anything described about the work further just come back to me later in my email is available on the final slide which I think will be circulated thanks very much okay thank you very much Craig and then on to our final speaker for today which is Karen Harrell, Dr Karen Harrell is a professional statistician who's worked for the Equality and Human Rights Commission since 2007 and previously for the Equal Opportunities Commission she's worked on a wide range of issues over the years for example pay gaps stop and search and hate crime statistics and on all protected characteristics covered by the Equality Act 2010 she's currently collecting data for the next various statutory review Karen thank you yes I'm just going to say a bit about the work that the Equality and Human Rights Commission has been doing to measure progress thank you so we're a statutory non-sponsored department of public body which was established by the Equality Act 2006 and we're a national equality body as well as a national human rights institute and we cover Great Britain so England's not with Wales but not Northern Ireland and one part of the Equality Act says that we should report to Parliament at least every five years on his progress in equality and human rights and to do that we are required to define a set of indicators and those indicators have formed a measurement framework which we've created to specify the topics we will count and the types of evidence we should look at to give us a framework as it says and for pulling together the information for each of these reviews so this is the structure of the framework for the six domains education work, living standards, health justice and personal security and participation and then as you can see on the slide within each domain there's a number of indicators looking at different areas the ones in bold are the ones we look at each time and the ones in a lighter type are supplementary indicators which we will select each time we do a review according to what the most important topics are at the time and some of you may have seen our last review which was released in 2018 and we're currently working towards the next one which because of the pandemic is likely to result in reports coming out over the next couple of years the exact timetable we're still thinking about because obviously it takes some time for data to be released that actually covers the pandemic next slide please so within the measurement framework for each of those domains there's a set of measures over 50 in all and on the statistical side statistics isn't the only thing we're looking at but the statistics part of it is mainly these 50 measures and we're trying to include a cross sectionalysis each year and also look at the change of the time and you'll see here so this is the nine protects characteristics covered by the quality legislation in the top left of this diagram we're also trying to look at socio-economic group groups of people who are at high risk such as as this here is the homeless people in detention and we're trying to look at different parts of country geographical analysis so that adds up to quite a significant amount of statistical analysis we'll have the next slide please so this is a diagram of some of the sources that we draw on and given that given his authority this meeting these are the ones that we where we obtain evidence from the UK data service and these by no means all the sources we use there's a lot of admin sources as well but these are the main survey sources and I'm just going to say that the look in particular at two of the two of the protected characteristics if we'll have the next slide and and these are two areas where we have been trying to obtain a broader range of data because obviously it seems like data of sex and age are relatively easy to get hold of but this one is looking at disability data and the more details you can get if you have information on payment tab as well and you see here the very pale ones are the ones where we only have a very basic measurement of disability the others go into more detail although in a few cases they are very much based on questions about diseases rather than the complex questions that we would prefer to see asked about disability and if I can have the last slide please and this is a summary of what data there are on sexual orientation so this is in an area that is expanding and still expanding with most of the surveys now asking a question but the darker ones are those where there's a clear place to get the data from the others so in development generally you have to be requested so I think the availability of data is an improving situation but still some areas where we do have more information and I shall finish there Thank you Thank you Karen, thank you very much to all of our speakers for really excellent thought provoking presentations Okay, thanks everybody so back to the seminar and we're going to move now into our discussion session with the panel we'll start with a few questions that have been asked by the audience and then move on to some general questions we want to put to how to kind of continue this discussion going forward so first of all, could I just ask the panel first of all to just give us your reflections on the discussions we've been having so far I was going to say just first thing was how much alignment there is across all the different groups about the sort of shared experience of people in the different communities and how it's the same issues really that are raised by everyone to be honest that would be my first reflection to start the conversation That was my main takeaway as well as I think really being led by what people say, led by people's lives people's experiences and building our data building our systems, our structures around that I think sometimes we follow trap I was trying to get our lives to match what the data says it should do or the system or the way of doing things and I think that real community dimension about valuing what people say I think came out really key across everyone's talks That stood out for me as well and I think it feels quite feels a little bit disappointing that so many marginalised communities are facing such hardship exacerbated by the pandemic and then as researchers and people working in organisations advocating for people who are suffering are really having to fight to get them represented in data as well I think that feels a little bit frustrating because it seems as though that should really just be a given that if we have these really marginalised communities then of course we should direct resources towards making sure that they are appropriately appropriately represented to ensure that we have proper data on them I think these things are cyclical as well so if you don't involve people in their data then they're not going to give you the data for you to understand more about people themselves so it can be sort of self-fulfilling a bit and people then get further excluded I think as well one comment that we had on the launch of our survey last week was that well we have lots of data that show us about these qualities that different groups face so for those ethnic minority people why do we need more data why do we need more data to tell us about how badly people are doing why don't the people have the power to do something about this local governments, national governments do something about this and I think when that was paused towards I really emphasised with that and thought well that is kind of how I feel as well but the important thing is that we do need to keep pushing the message of how marginalised and how disadvantaged people are and one of the best ways to do that is presenting people with the facts about that and presenting people with the data about that Can I start with one question that's been posed from Matthew Woolard So he says can we talk a little bit about language so for years survey designers have used language to describe things which are not in their competence so and it speaks to the kind of co-creation point that some of you are making in your talk so white statisticians coming up with terms with ethnicity questions How do we allow minority opinion to have a voice without being as culturally inappropriate as some language has been in the past I think from my point of view you know I said specifically I don't like the term BAME and that an opinion I think that is shared by other ethnic minority people and researchers working in the field of ethnicity and race because it lumps together people who have very different and distinct experiences and it it's as though that term is essentialised as if BAME is a thing it's not a thing it's an acronym and I think maybe other people would disagree because it's a shortcut and it's a way to describe groups of people who we all think we know who we're describing by using that term but I think wherever possible I think this applies to any kind of marginalised community we should be being very specific about what we're talking about and who we're talking about in this country the experience of for example British Indian people is very different from the experience of Chinese people or black African people or gypsy and Irish travel people but they would all come under this category BAME and you know I think this term is now you know that's the term that's on trend at the moment and in the past it will have been other terms and I think I tend to use ethic minorities some people like to use minoritised groups instead to show the disadvantage that they face so I think terminology and the language we use is very important because it signifies what we think about these groups it signifies the importance that you're giving to their experiences what do others think and that Daniel's got his hand up I think Oh sorry yes Daniel go ahead Yeah thank you I think I would continue the subject the topic that the army started and I would say that indeed BAME is a concept that's I mean close to meaningless and I think people who do use it use it it means something for them and we need to ask ourselves all of these labels what actually do they mean do they serve any kind of practical problematic question do they help in terms of policy for example that's the that's the fixed star that I think we often should be guided by now I would share with you probably an event or that is basically unfolding the Jewish community today and in the past five years I'd say we have been consulted about the use about the proper ways to capture Jewish population and the census and service and basically it's a discussion it's a debate between religion and ethnicity okay how do you capture Jewish population is it a type of religious group is it a type of ethnic group is it maybe both so the reality the truth of the matter that it's both that doesn't particularly matter in the administrative context you really have to create a way for people so they can see themselves in the questionnaire it may be a compromise with their inner feeling for example but they have to be able to identify themselves in the questionnaire and so we advocated early on that Jewish population is reflected as religion and ethnicity later we changed this position slightly we adjusted it we could see that religion is enough even people who are not religious who don't hold very strong version of faith the Jewish people will know that religion question is there for them so they will see themselves so that particular emotion or that particular sentiment needed to be identified and reported but there is a bigger question for us and that's not a Jewish question far from that and the reality is changing all the time meaningful groups are being created all the time equality or outcomes have to be monitored along certain lines all the time and these are changing so how does the statistical system create well adjust itself is it flexible enough to reflect these changes that occur all the time and still can we marry the attention to the small groups often disadvantaged groups with the requirements of statistics because sometimes you attempt to create sizeable categories of people and when you attempt to create sizeable categories you don't want to split you want to somehow increase the size of them so I think for us at least the meaningful very meaningful discussion is A how we are reflected and is this data collection flexible enough to incorporate changes but also we need to ensure the situation should be such that we create statistically significant not in any political sense but analysable groups with all the labels that we use can this be done, how this can be done that's my preoccupation and that opinion that view is supported by what they have heard here Thank you, that actually leads in nicely into a question from Sarah Metcalf which is how can we start to approach the improvement of data collection to ensure the amplification of diverse voices if people we want to reach and not engage for various reasons and we cannot obtain their data we cannot tell their stories how can we improve this so I think that's kind of the million dollar question isn't it in this I'm really interested in in what people think about this I think that's a really interesting question I think again kind of continuing the thread from Daniel's answer in the census it's really kind of come to fruition of late around sexual orientation and transgender identity questions in the upcoming census and I think how do we how do we show people that being counted in a state data collection exercise is safe, secure but also meaningful for their everyday lives and I think for a lot of minoritised groups a lot of people's relationships to data collection activities whether it's through police, surveillance law enforcement is quite a negative experience so I think how do we ensure that when data is collected about minoritised groups whether it's gender sexual minorities or racial groups or religious groups actually that data is being used to improve people's everyday lives and I think that's really the key knob of how do we get people on board about participation and being engaged is actually ensuring that we're not collecting data for data's sake but we're actually using it in ways that has material everyday impacts and I think also sort of marginalised groups they're often they are stigmatised so and that drives those groups also experience extra levels of other issues for example domestic violence you know one in twenty people in the UK I think that suffer domestic violence but it's something like one in seven for disabled people so those those experiences push people further away from being able to engage with data collection and it makes it much more a complicated story and I think that's why I believe co-production is a really important way of approaching that to engage with the community and also to to sort of I don't know it sort of shakes the box a little bit co-production you hand the reins over to other people and the communities themselves and that's quite a scary and liberating thing at the same time being a research manager and trying to have a programme of research it would deliver for example we're trying to steer that but also let that be as free as possible and that's why I think co-production is quite a powerful thing which I mentioned obviously in my talk I think as well you know I kind of really agree with what Kevin was saying about people feeling excluded for research because there's such a lack of trust in state institutions which have been the site of discrimination so if the people that are asking you to fill in a survey are the people that have treated you very badly in the past when you think they are the people that treated you badly in the past why would you want to hand over very personal information to them I think this is one of the reasons why some people don't want to take part in data collection initiatives and they don't see the importance of them sometimes because they have participated before and nothing's actually changed so I think there is disillusionment within people but that's up to data providers data collectors and state agencies to fix, this is not about encouraging people on an individual level to take part and just to add to what Craig said about co-production we have to remember when we're talking about data we're talking about all forms of data not just quantitative data that is not the most important form of data so I'm a mixed methods researcher but I'm trained as a quantitative analyst but I don't believe that quantitative data holds all the answers so using co-produced qualitative data to add richness, to add nuance to the quantitative data we have is imperative and we do need a shift in the thinking of what counts as data what counts as important data and people's lived experiences and those stories should form part of that important resource that we have OK, thank you very much for that so we're going to capture all of the Q&As that have been put and asked people to respond separately but now I'd just like to move on to the issue of really looking at what do you think is the key development that would support the continued and evolving representation of self diversity and data so to our panellist what can we really do to make changes here I think it's embraced the communities as expert themselves empowering communities to conduct research as well that's been very self rewarding for the people involved and to expand the research that I've been working on with people it's very been quite a reciprocal relationship and that builds trust and people are able then to go into the communities and to think about in creative ways to engage people and I think that trust is a really important thing especially when elements like benefits are affected or people's statuses in the UK for example are affected and how society responds to them I think I can kind of add to that as well thinking about I guess again what happens at space between data practices identity and I think as data has more and more interest in work around identity characteristics I think we do need to really acknowledge that people for a variety of reasons will not want to share data about their identity I think we need to build systems and structures that fully acknowledge and recognise for refusal, that space for not participating in these systems and I think there is a lot of particularly fantastic work taking place in the US among data justice campaign groups particularly around the issue of data on black people in America and again how do we build systems and structures that acknowledge people's refusal and acknowledge people's decision informed decision to participate in data collection exercises I think we often have an assumption that everyone will give data if we can just push them hard enough actually I think we need to turn the head kind of turn that issue slightly and think how do we really acknowledge people's refusal in meaningful ways as well and I think that's kind of lacking at the moment OK and actually one question I think that we should come back to and it relates to this you know the small size of some group so how do we address the situation so marginalised groups make up such a small proportion of the available data that the data controllers won't let researchers see the data because it might be disclosive and things like won't have to be linked with other data or it's classed as statistically insignificant how do we make sure that we involve the groups whilst also protecting their privacy when it's administrative data or census data and that is the actual number of people looking at it on a local level then there's not much you can do about that that is a statistical disclosure control issue and you can't access data that will put people at risk but obviously if you are looking at things on a country level there probably wouldn't be such small groups that you can't access the data but it might be the case of some groups but when we're talking about data that's collected in national surveys we need to go back to the beginning and think about oversampling groups that we need to make sure we've got a big enough sample to do proper analysis so as I mentioned in my talk I use surveys that use ethnic minority boost sampling to try and make sure that there's enough ethnic minority groups understanding society tries to aim for 1000 people in each of the large ethnic minority groups that's Black African, Black Caribbean Pakistani, Bangladeshi and India so that when researchers are looking at the data you can do some subgroup analysis obviously that gets hard if you want to try and do it by geography so for example at MSOA level so things do get difficult but I think for surveys and smaller data collection initiatives you need to think about this at the design level and obviously for some admin data I don't think that's an issue that can be solved I just added a very quick point to that as well I think the bulk of work I see actually people often use small numbers as an excuse not to do things and actually when we jump into the data whether it be quant or qual is often enough to work with and I sometimes feel that meaningful concerns around small numbers often stops work before it even begins and I think that's what I tend to come across more so particularly in the higher education sector with quite large samples and the issue of overly small numbers OK there's one kind of overarching question so how would you see intersectionality in supporting identity and data and could we go around the panel and ask you all to comment on that so Craig your top left of my screen so can I begin with you thank you can you just repeat it sorry how would you see intersectionality could support identity and data well one of the things that has jumped out on me is as I said at the start the issues that have crossed over the different groups that we are sort of talking about here and I wonder if there could be a way there would be a standard approach where all of these groups have kind of captured as standards within any survey that someone might do and that's obviously tricky because it's hard enough to get that data collection any way for the group so but I wonder if there's a way that that could be done so then any kind of piece of research that's being conducted could be analysed from the different points view of the different communities involved thank you that's a good point Daniel could you comment I think the greatest lesson really for my 11 maybe years of involvement in the minority research let's call it that in Britain was that first of all there's a tremendous very obvious for me need to ensure that the major administrative sources at the level of for example organisations like NHS they include the relevant variables that describe the diversity in Britain so they either they don't include them or they include them but actually data are not collected it's left to the discretion of the respondents for example if you register with a new practice there isn't ethnicity question on the questionnaire and it's made clear to you that you don't have to fill it in now so there has to be some sort of shared position on I mean if we are serious about collecting the data how do we go about it because most people don't fill it in or a lot of people wouldn't fill it in not because they object they don't want to be identified but they would they don't particularly enjoy filling in the questionnaire as simple as that however to capture ethnicity to capture religion that needs to be done it needs to be done in NHS perhaps other data administrative data sets it's an imperative to include these variables in the deaths and birth certificate in these systems I have to run short of time actually thank you so that's basically that's basically why sorry to cut you short Karen I wonder if you could comment on that from your perspective yes I mean in sectionality I didn't mention this during the presentation earlier but that's an important part of our analysis and we try and look at combinations of characteristics and not just each of them separately because you really don't get a a sufficient picture of what's going on if you just look at a disability separate from sex and all the other characteristics but again of course there are limitations then from as we have mentioned before if you're going to divide up a population into very many different groups then it can make it more difficult to get good robust results thank you Kevin sorry I have to say perhaps 30 seconds each on the intersectionality point I'll try and say something very quick I think I'll go back to the point I said about looking within groups so I think if we treat the LGBTQ community as a monolith actually what that does is bring to the four those who are already most privileged so often white gay men and it leaves some of the people who are maybe experiencing multiple kind of intersections of disadvantage often cast them further into shadows so I think it really needs to be baked into all the work we do to ensure that when we do work it's not just kind of going for the people who are the least minoritised within minoritised groups and I think this is an issue that we thought about when we were designing the evens because we wanted to make sure that obviously our interest is in ethnic inequalities but we want to make sure that we collect lots of different characteristics as well so on socio-economic status sexuality some questions on living so some people living for example the Roman and Gypsy travel community living different types of accommodation so we made different questions which would ensure we would capture their experiences but I think what tends to happen in these kinds of surveys and when we're doing individual work on our research areas is we're limited in space we have limited space we want to capture the variables that we're most interested in to do our research and I think this is where statutory organisations have a larger role to play to make sure the data that everybody needs is collected in more detail rather than leaving it to different smaller surveys which are great but at the end of the day we all have limited resources Thank you so much I'm really sorry, really interesting discussion but I'm going to have to draw this to close I do want to say so the UK data service is going to be setting up an open community so that there will be opportunities to continue the engagement and continue the discussion there'll be information on the last of a disk mail address and information on that in the final slide and going into the chat so do sign up to that if you're interested in continuing the discussion so it just leaves me really to really thank all our speakers today so thank you very much to Lem Tisei, to Kevin Guillam Dermi Cepardia, Karen Hurill Craig Moss, Daniel Statski Thank you so much, really really great interesting presentations and a great discussion special thanks also to Dr Victoria Moody who's Deputy Director and Co-I of the UK Data Service who devised the concept of this event and also thank you to Neil Diamond Greene who's been doing a lot of the admin and bringing the speakers together and other technical support from the UK Data Service for running all the technology today so thank you so much for that yes so thank you thank you very much for joining us this morning hope you'll join in continuing the conversations that have started today and there's the disk mail details for you thank you