bluuebunny/crossref_metadata_2025_split huggingface dataset:
Comparing the 2021 Census to administrative data to better understand the population estimation challenge
Authors: Pereira Elizabeth , Robertson Zak , Barnes Ayesha , Jones Ffion , Mylles Sally , Pearce Chloe 
Published: September 2023

ObjectivesTo analyse the linked dataset between England and Wales 2021 Census/Census Coverage Survey and the Demographic Index (DI). This is a rare and unique opportunity to make direct comparisons between Census and administrative data to provide evidence on improvements in the use of administrative data in population and migration statistics.
MethodsThe DI is a composite dataset made up of several linked administrative sources. The linked output is complex, made up of individual sources grouped into clusters. These were linked to the Census, using both automatic and clerical matching to obtain the highest matching quality possible. To carry out the analysis, a flagging strategy has been designed to enable analysts to form cuts of the linked dataset that are specific to their research needs. High level research questions were designed to compare the coverage and capture across the Census and administrative data.
ResultsInitial analysis has been completed and reviewed, including: comparing the coverage of the DI and Statistical Population Datasets (which use inclusion rules to approximate the usual resident population) to Census, comparing how Communal establishments are captured in the DI and Census and comparing the geography of those found in both the DI and the Census.
The results will inform the National Statistician’s 2023 Recommendation, but also the future delivery of transformed population and migration statistics. This includes:

Providing insights to improve the DI’s linkage methodology
The SPD’s construct
Identifying the extent of over and under coverage in the SPD, allowing development of an estimation strategy to estimate the population using administrative data more accurately

ConclusionThis opportunity to compare linked administrative and Census data enables analysis to provide unique insights on quality and coverage, to improve the use of administrative data to inform population estimates, provide evidence on the use of additional administrative sources and improve future linkages.
Hidden in plain sight: Using administrative data to conduct a longitudinal cohort study of children exposed to opioids in pregnancy
Authors: Marryat Louise , Rauchhaus Petra , Boardman James P , McFadden Alison , Whittaker Anne , Frank John 
Published: September 2023

ObjectivesChildren of women who use substances are difficult to research at a population-level using traditional research methods due to the complexity of their lives. Resultingly, we have little robust evidence on their outcomes. This study developed an administrative data cohort of children exposed to opioids and explored health outcomes.
MethodsUsing data from birth records, antenatal records, prescription data, hospital/psychiatric hospital admissions, and drug and alcohol service data, we identified 6,408 children (born 2009-2019) in Scotland who were exposed to opioids through illicit use and/or medication assisted treatment (i.e. methadone/buprenorphine). A control group (n. 19,089) of children not exposed to opioids were matched on age of mother and Scottish Index of Multiple Deprivation. Data were described and linear and logistic regression models were used to examine the relationship between risk factors (such as drug and alcohol use in pregnancy, gestation at booking and at birth), and key early outcomes.
ResultsAlthough the majority of women had their substance use recorded in antenatal records, 28.9\% did not, demonstrating the importance of using multiple administrative datasets to form the cohort. Children in the cohort were more likely to experience a range of adverse outcomes including being born early (17\% born prematurely, compared with 6.5\% in control group), having a below normal Apgar score (the scoring system used to assess newborns shortly after birth) (2.9\% in cohort vs. 1.5\% in controls), having significantly lower birthweight, length and head circumference, and more likely to be removed from their mother prior hospital discharge. Differences between the cohorts remained after controlling for other risk factors including alcohol use, and gestation.
ConclusionThis feasibility study brought together a cohort of children usually excluded from traditional forms of research. The research demonstrated early differences in outcomes between exposed children and others from similar socio-economic groups. The next stage of this research is exploring health and development outcomes in the preschool period.
Ethnicity, gender and community sentences
Authors: Sorsby Angela 
Published: September 2023

ObjectivesThis paper presents findings from administrative data analysis examining differences between ethnic groups and men and women in the number and type of requirements that make up community sentences as well as the effectiveness of different requirements in terms of successful completion of the sentence.
MethodsThe paper presents findings from analysis of the Data First probation and criminal justice linked datasets. The analysis will focus on whether:

there are differences between ethnic groups and men and women in the number and type of requirements that make up community-based orders (rehabilitation, unpaid work, curfew and accredited programmes)
some requirements are more effective in terms of successful completion of the order.

The paper presents findings from regression analysis used to examine the above relationships while controlling for other relevant variables such as age, number of previous convictions and offence type.
FindingsGraphs will be used to set out differences between broad ethnic groups and men and women in the total number of requirements which make up community-based orders and the proportion of offenders from each group which receive each of the main types of requirement namely: rehabilitation; unpaid work; curfew; and accredited programmes. Graphs will also be used to set out differences between the different order requirements in terms of successful completion. The paper will also present findings from regression analysis which will identify differences after taking account of other factors. The findings will of necessity be based on broad ethnic groups as it is unlikely that there will be sufficient numbers of people within more narrow ethnic groups to meet statistical disclosure criteria.
ConclusionThere is a lack of information on relationships between ethnicity, gender and community sentences. Better understanding of these relationships has been identified as crucial by HM Inspectorate of Probation. This paper provides more information on these relationships enabling policy decisions to be better targeted to provide equality of outcomes.
Evaluating teacher grading during the pandemic: An analysis of how teacher grades in 2020 compared to exam grades during ‘normal times’
Authors: Stratton Tim , Okpala Chifumnanya 
Published: September 2023

The aim was to evaluate teacher grades awarded in 2020 after GCSE and A-level exams were cancelled due to the pandemic. We identified if there were changes in the relationships between student, school and subject-level features and grades awarded by teacher judgement in 2020 when compared to pre-pandemic years.
A multi-level modelling analysis was conducted using the GRADE dataset which links data on pupil characteristics with results data and university application data. The model outputs identifying the relationship between student, school and subject characteristics and GCSE and A-level results were compared between 2020 and normal exam years to identify any notable changes.
A further study focussed on whether university application patterns had an influence on teacher judgements at A-level, since teachers may have known students’ application decisions when deciding on grades. For this analysis university tariff and the degree subject applied to by each student were key variables.
Analysis showed that across both GCSEs and A-levels there was an average increase in results by around half a grade in 2020. There was also less variation in grades in 2020. However, the majority of relationships between grades and other features studied had not substantially changed.
Prior attainment was by far the strongest predictor of grades, but this relationship was slightly stronger in 2020 compared to previous years.
Subjects with more non-exam assessment tended to be those with the largest increase in grades, as well as ‘facilitating’ subjects at A level. There was also a decrease in the attainment gap between male and female students at A level.
The follow up study indicated that teachers were not influenced by student’s application decisions when allocating grades.
Findings suggest that teacher grades did not introduce any substantial sources of bias or different patterns of grading in 2020. This research helped to inform policy decisions around national assessment in England in 2021, as well as contributing to the broader understanding of direct grading by teachers.
The dynamics of the nursing and midwifery professions: Initial findings from analysis of longitudinal registrant data
Authors: Atherton Iain , Jamieson Michelle 
Published: September 2023

ObjectivesTo ascertain geographical differences in retention of nurses and midwives across the United Kingdom using registrant data.
MethodsThe Nursing and Midwifery Council (NMC) are responsible for holding a register of all nurses and midwives in the United Kingdom. Registrants are required to revalidate every three years. Linking together resulting data creates a longitudinal dataset that follows registrants over time. The NMC is providing anonymised data through the ONS Safe Researcher Service (SRS). Data sharing agreements have been signed off and data is in process of being ingested by ONS. Initial analysis will focus on geographical differences in retention by for nurses by field of practice (adult, mental health, children, and learning disability) and midwifery.
ResultsThere are estimated to be around 750 thousand nurses and midwives currently registered. Processes used to take this work forward will be described including public and stakeholder engagement. Early findings will be presented comparing demographic profiles of the professions and, for nursing, fields of practice in 2018 and 2021. Cox proportional hazard models will enable comparison of geographical differences in retention between England, Scotland, Wales, and Northern Ireland.
ConclusionRegistrant data provides a basis that can inform policy. This is especially important given current challenges with regard to recruitment and retention in the nursing and midwifery professions. Future work will be outlined that will utilise registrant data including linkage to other administrative and census data sources.
Combining commercial assessment products with administrative data to shape education policy: Tracking pupil outcomes during the Covid-19 pandemic
Authors: Andrews Jon 
Published: September 2023

Objectives To inform the government’s response to the COVID-19 pandemic by providing an ongoing analysis of the learning loss and recovery experienced by pupils in England after the cancellation of national statutory assessments. Our aim was to use data from a commercial assessment product linked to large administrative datasets.
Methods We constructed a pupil level dataset of assessments in reading and mathematics. The assessments covered multiple time points in the pandemic period and in the years before. We matched this to the National Pupil Database to give a wide range of pupil characteristics information – including eligibility for free school meals, the area they lived in, and information about their school.
By constructing a regression model of pupil outcomes in the pre-pandemic period, we produced a counterfactual of what we would have expected each pupil to achieve had the pandemic not occurred and hence estimate the extent of learning loss.
Results National lockdowns and restrictions to in-person learning were associated with pupils in England making less progress than normal. By the summer of 2021, learning losses in reading amongst primary-aged pupils amounted to around 0.9 months of learning, and learning losses amongst secondary-aged pupils amounted to around 1.8 months. Learning losses in mathematics were even greater, at 2.8 months. We found that the pandemic’s effects were not felt evenly with larger losses for those from economically disadvantaged backgrounds and larger losses in parts of the north and midlands than in London and the south. Indeed, by the start of the 2021/22 academic year, results in reading for primary aged pupils in London and the south-west were broadly in line with pre-pandemic levels.
Conclusion The project demonstrated the power of combining commercial products with administrative datasets to shape policy. The analysis informed the government’s education response to the pandemic including the targeting of additional support to pupils from low-income backgrounds who, as subsequent national tests have confirmed, were disproportionately affected by the pandemic.
We need to talk about data! Transforming the conversation between researchers and the public
Authors: Welpton Richard 
Published: September 2023

ObjectivesOur Future Data Services (FDS) work has shown that researchers find it difficult to start conversations with the public about their work and the use of data. This session will explore how data services could effectively facilitate conversations between the public and researchers in the future.
MethodWe know that the public is much more aware that data about them are collected: sometimes through mistakes made, leading to public engagement as an afterthought.
Researchers have told ESRC that they would like to engage with the public; but barriers prevent them from doing so. ESRC would like to run this workshop to find out from researchers what barriers they believe prevent their engagement with the public.
We’ll facilitate face to face discussions as a deep dive to understand what these barriers are, and what resources would help researchers to meaningfully connect with the public in the future.
ResultsThe input collected from researchers at this workshop will help us draft recommendations about how ESRC/UKRI funded data services can in the future support researchers to engage with the public when designing research proposals that use personal data.
These recommendations will likely identify specific funding opportunities that ESRC can target to enable data services to support researchers to engage with the public. For example, resources could be provided through data service website, such as training materials (including crib sheets and videos) and signposting to organisations that can enable them to speak to the public about how they would like to use their data for research.
These recommendations will be published in Spring 2024 and funding opportunities could be made available from 2025 onwards.
ConclusionESRC has heard researchers say they would like to work with the public when designing and undertaking research with personal data in the future. But routine engagement with the public is a hard ask; unless supported through specific programmes, navigating the public engagement remains niche, yet essential.
Optimising data curation pipelines for population-level analytics in secure data environments: Findings from a phenome-wide analysis in the NHS England Secure Data Environment
Authors: Al Arab Marwa , Welshman Zach , Allara Elias , Nolan John , Denholm Rachel 
Published: September 2023

ObjectiveSecure data environments (SDE) ensure safe access to large population-level sensitive data. However, computational capacity is limited in these environments, which leads to challenges in the analysis of large population data within the constraints of a complex cloud architecture leveraging multiple software ecosystems. Here we present an efficient pipeline to conduct phenome-wide analyses using electronic health records (EHR) in the NHS England SDE.
MethodsWe accessed deidentified linked EHR from NHS SDE for around 50 million people in England. The exposure is SARS-CoV-2 infection, with outcomes being a phenome-wide atlas of all diseases recorded in EHR data. For computational efficiency, we created three cohorts tables using PySpark within the Databricks environment and a sampling algorithm with inverse probability weights which adds a flag to the dataset to mark the inclusion of a row in the sample of a specific outcome. We will conduct survival analysis using Cox models in RStudio on the samples while adjusting for potential confounders in the main datasets and 15 subgroups.
ResultsSampling with inverse probability weighting produced datasets that are statistically equivalent to the original population data. In terms of computational efficiency, the time needed to sample and read the data for modeling one outcome is 2.3 min compared to ~45 min when trying to read the entire dataset, which could fail due to the 4GB memory limits of in Rstudio within the SDE. This is particularly important in our study since we will be running at least 13,296 models for main and subgroup analysis in the three cohorts. By adding a flag to each data row to indicate its inclusion in a sample, the sampling strategy significantly reduced the storage space required for the outcome table of each sample.
ConclusionPreparing datasets in Databricks and applying sampling can increase the efficiency of big data analysis pipelines within SDE, save storage space, and help in avoiding memory overload caused by using complete datasets for statistical analysis.
Trends in ethnic inequality in child welfare interventions in Wales, 2010 – 2021
Authors: Jing Yongchao , Cheung Sin Yi , Griffiths Lucy , Scourfield Jonathan 
Published: September 2023

ObjectivesChildren’s chances of receiving welfare interventions are found to vary by ethnicity in England, but the ethnic pattern in child welfare interventions in Wales over time is unknown. We aim to estimate the scale and trend of ethnic inequalities in intervention rates in Wales over a 12-year period, using population-based linked administrative records.
MethodsWe analyse cross-sectional administrative children’s social care data: the Children in Need (CIN) dataset from 2010 to 2016 and the Children Receiving Care and Support (CRCS) dataset from 2017 to 2021. These data are linked to both the ethnic population data to obtain the ethnic variation in child welfare intervention rates and, using the WIMD, to identify the relative deprivation level in the neighbourhoods from which children entered care. For observations in CIN/CRCS whose ethnicity are missing, we link Census 2011 to obtain the children’s ethnicity to achieve a fuller coverage. For the first time, our analysis also links children’s social care data with the religion variable in the Census data, allowing us to estimate the extent of religious inequalities in child welfare intervention.
ResultsBased on research findings in England on ethnic variation in child welfare intervention, we hypothesise higher intervention rates among Black children and a lower intervention rates among Asian children in Wales, compared to White children, controlling for deprivation status. By extension, we also hypothesise lower intervention rates among Muslim children compared to Christian children.
ConclusionsNo research to date has quantitatively documented the pattern and trend of ethnic inequalities in child welfare intervention in Wales using linked administrative data on CIN/CRCS. Our study is also the first to examine religious inequality in UK child welfare by linking social care data to the Census. Our findings will have significant implications on policy and practice in social work and particularly in children’s social services. We conclude by discussing what future research questions may emerge from the new insight we shed.
A policy impact case study using real world data from Welsh government fuel poverty schemes to inform scheme design
Authors: Morrison-Rees Sian , Lowe Sarah 
Published: September 2023

ObjectivesTo reduce fuel poverty in Wales: the Welsh Government developed schemes to provide energy efficiency improvements to lower income households.
To inform scheme design: investigate health impacts by linking scheme data to health records.
Presented objective: to demonstrate how research findings using real world data can impact policy focus.
ApproachThe research was conducted by an independent researcher at Swansea University who co-produced research questions with the Welsh Government Fuel Poverty Policy Team.
A longitudinal dataset was created linking anonymised ‘Warm Homes: Nest’ improvements data to residents’ routine health records in the SAIL Databank at Swansea University. We examined recipient health before and after intervention compared with controls.
A high-level policy briefing and research report were published in the Welsh Government Social Research – Analysis for Policy series.
Findings were used to design and pilot new eligibility criteria to capture low-income individuals with a respiratory, circulatory or mental health condition.
ResultsThis presentation will describe the policy impact pathway from initial discussions with policymakers to real world change, including:

securing ESRC funding for a Knowledge Transfer Fellowship, which included a 2013 data linking demonstration project…
…which allowed funding to be secured for a 2015-18 research project on the impact of improvements on recipient health…
…which published emerging findings in 2016…
…and substantive findings in 2017, showing a significant positive impact of improvements on recipient health…
…which policymakers used to design a pilot to test ways to widen eligibility criteria to include individuals on a low income with a respiratory, circulatory or mental health condition…
…which led to scheme criteria being widened in 2019.

By 2021, 25% of recipients entered the scheme via the ‘health route’.
ConclusionBy delivering research findings generated using linked real world data, and focused on questions co-produced with policymakers, researchers can successfully impact the design and implementation of government policy, thereby improving the lives of people in the real world - in this case, the health of the citizens of Wales.