#DataImpact2021 raised many interesting questions from participants.
Here, Dr Dharmi Kapadia, who spoke on Represented yet excluded: How ethnic minority people are counted in national surveys, gives her thoughts on three questions which were posed.
How can we start to approach the improvement of data collection to ensure the amplification of diverse voices? If people we want to reach are not engaged for various reasons and we cannot obtain their data we cannot tell their stories. How can we improve this?
Firstly, we should address the reason why people may not be engaged, and think carefully and critically about why this may be the case, before formulating plans to improve representation in surveys. There are often very good reasons why people may not be engaged with research or do not wish to take part.
For example, for ethnic minority groups in the UK, there is some mistrust of government institutions which has been exacerbated by the failure of the UK government to sufficiently address the stark ethnic inequalities in Covid-19 prevalence and mortality. The recently published Sewell report has added to this mistrust by denying the existence of institutional racism.
In this context, it is not hard to fathom why ethnic minority people may be reluctant to take part in research, when many of them may well believe that research does not and cannot impact policy and government decision making. So the first step to ensuring that a diverse range of voices are represented in data, is to ensure that at national and local levels, people are valued by acknowledging the inequalities they face.
Secondly, to truly ensure a diverse range of voices in datasets, these must be considered at a planning stage not as an afterthought, and data collection should be geared to collect data not only on what researchers deem to be important, but also on what the population of interest consider to be relevant to their lives.
At this design stage, input from people who are affected by the research, relevant VCSE organisation and other stakeholders is vital.
It’s great you mentioned ethnic group classifications should not be combined but separated, why do you think ethnic inequalities has received less credence in policymaking discourse when compared to socioeconomic inequalities? Do you think the pandemic will lead to structural change on the policy forefront for ethnic inequalities?
Very simply put, racism is not considered to be a ‘damaging enough’ issue and hence does not feature high on policy agendas.
However, the overwhelming evidence that details ethnic inequalities in health, employment, education, housing and almost every other important life domain from the past 5 decades and during the pandemic, makes it much harder for the government to completely ignore and continue with a strategy of inaction on racial injustice veiled by race reports.
The recent Sewell report has come under heavy fire from leading race equality charities, academics, activists, professionals in many sectors, and most recently by the UN Human Rights Council. I am hopeful that the evidence that we as researchers are generating during the pandemic will contribute to a positive change for race equality, but the change will be slow given the current policy climate.
Do you think there are new and innovative opportunities here through collecting data through means other than surveys and using textual analysis for example?
There are numerous ways in which data are collected and surveys are only one way. Surveys are popular, as when designed correctly they allow inference from the collected sample to the population from which the sample were collected. And even within survey methodology, we have seen an increase in online surveys and new methodologies using non-probability samples in order to make generalisations.
There are also many innovative ways to make use of digital data, including textual analysis of, for example, social media posts. A recent NCRM series of workshops were very valuable in thinking about how data collection has changed during the pandemic and how researchers have adapted their methods.
About the author
Dr Dharmi Kapadia is Lecturer at the Department of Sociology, University of Manchester and a member of the ESRC Centre on Dynamics of Ethnicity (CoDE).
With expertise in social statistical methods, her main areas of research are ethnic inequalities in health and access to health services. She has also conducted research on ethnic inequalities in the labour market, and on the relationships between poverty, ethnicity and social networks. She has published in journals including the British Medical Journal and Ethnicity and Health.
Dharmi is one of the original group of UK Data Service #DataImpactFellows. She has written several posts for the Data Impact blog.
Follow Dr Dharmi Kapadia on Twitter @Dharmi Kapadia
Follow CoDE on Twitter @EthnicityUK and Instagram @codemcr
Follow the Evidence for Equality National Survey (EVENS) on Twitter @EVENSurvey and Instagram @evensurvey