Papers included:

• Understanding Masculinity: How it is Defined, Measured and Experienced.
• Growing Up Without Parents: Spatio-Temporal Dynamics of Skipped-generation Households and the Impact on Adolescent Mental Health.
• The Division of Labour and Female Partners' Relative Pay Across Phases of Parenthood: Evidence from UK Couples.
• The Decomposition of Group Differentials.
• Working Life Expectancy Among China’s Middle-Aged and Older Population.
• How Does the Use of Information and Communication Technologies Impact on the Wellbeing of Older Adults?
• Got SWAG? A Simple Scalable Approach to Bayesian Inference.
• How Effective is the UK Homeless Policy in Assisting Young People Out of Homelessness?
• Exploring the Impact of Gender Roles and Social Norms on Fertility Intention Among Young Adults - An Empirical Analysis of International Data.
• A Socio-Semantic Analysis of the Perception of Large Language Models by Scientists.
• Factor Recovery of Bifactor Models Using Machine Learning.
• Work Schedule Typologies and Job Satisfaction Among UK Workers.
• Willingness to Participate in Smartphone-Based Research: Evidence from the UK.

Find out more about our current PhD students and their research projects.

The focus of the visit was to contribute to the development of a novel methodological framework that integrates Matrix Decomposition-based (MD) estimation into Structural Equation Model (SEM) Trees and Forests.

Traditional SEM Trees rely on Maximum Likelihood Estimation (MLE), which can be unstable, have improper solutions (e.g., negative variances), and be computationally intensive, especially in small subgroups or misspecified models. The team in Tokyo worked on developing an alternative approach based on matrix decomposition, which avoids many of the pitfalls of likelihood-based estimation.

During his visit, Ahmed worked on extending existing simulation studies from single-tree models to ensemble-level forest models, comparing four major estimation frameworks: MD-based SEMTree, Maximum Likelihood-based, constrained ML-based, and Bayesian SEMTree. He implemented forest-level simulations that assess both shared metrics (such as improper solution rates, computational time, and node recovery) and forest-specific ones (like variable importance, prediction accuracy, and ensemble diversity). He also continues to explore alternative splitting algorithms, including Factor Analysis by Instrumental Variables (FABIN) and other non-iterative multi-start approaches. Eventually, the team intends to develop an open-source R packages to support this new methodology.

This visit provided a unique environment to engage with cutting-edge computational and quantitative research which contributes to the methodological advancements that will benefit the broader SEM and statistical community.

Ahmed will continue to collaborate with Professor Usami and Dr Todo not only to finalize and publish this research, but to collaborate for more research together in the future. The Department of Social Statistics at the University of Manchester and the team at University of Tokyo both expressed interest in more contact and collaboration in the future between the departments and the universities in general.

Examining how young people across Europe imagine and plan their path to adulthood, the article, “Ideations and Intentions in the Transition to Adulthood: A Cross-European Comparison,” draws on data from the Generations and Gender Survey and the European Social Survey to explore young adults’ ideal ages, intentions, and actual behaviours across 33 European countries. 

The study provides a comparative picture of when young people expect to leave home, form partnerships, marry, and become parents; and how these expectations align, or fail to align, with reality.

Findings show that while young Europeans tend to view their twenties as the ideal period for key life transitions, they often experience these events later than intended. The mismatch between ideals and outcomes highlights persistent gender and regional differences, suggesting that cultural norms and structural barriers continue to shape the pathways to adulthood across Europe.

Primary health services are the first point of contact for those seeking support for common mental health problems, such as anxiety and depression. These services form an essential part of the response to the UK’s mental health crisis. 

Engagement with those accessing and navigating primary care pathways for common mental health problems has highlighted that accessing and engaging with support frequently involves struggling with complex and burdensome bureaucratic processes at an already difficult time. These experiences can leave people with a profound sense of unjust treatment that continues throughout their journey through the system.

Research across different disciplines has suggested that perceptions of ‘just’ treatment can also significantly impact treatment outcomes by affecting engagement with services, deterring individuals from seeking support in the future, and exacerbating existing inequalities within the system.

A research programme, led by Professor Joe Tomlinson and funded by a £2.5 million Wellcome Discovery Award, will pioneer the application of the theory of ‘bureaucratic justice’ in primary mental health services. By deploying an innovative combination of a longitudinal quantitative and qualitative study with participatory storytelling methods, the programme will develop a new understanding of the nature and relevance of just treatment in the context of how people interact with frontline administrative processes in primary care mental health services.

The programme will also build an interdisciplinary community of researchers, while providing a platform to embed lived experiences of seeking mental health support into research practices in innovative and engaging ways.

The programme formally launches in January 2026 and will run for six years. Alongside Professor Joe Tomlinson, The Dickson Poon School of Law and King’s College London, the programme will benefit from the expertise of co-investigator Professor Todd Hartman Head of the Department of Social Statistics and Deputy Director of the Cathie Marsh Institute at The University of Manchester. Co-investigators are also based at the University of York (including Dr Jed Meers, Dr Simona Manni, Dr Annie Irvine, Dr Aisling Ryan, and Professor Lina Gega).

The research, funded by Good Neighbors (in 2022-23) and The University of Manchester - International Science Partnerships Fund (in 2024-25), was led by a joint team from the School of Social Sciences and Global Development Institute, University of Manchester, including Dr Jihye Kim, Professor Wendy Olsen, Dr Mohammed Ibrahim, Harshada Ambekar, Sonny McCann and Mindy Park. 

They conducted both surveys and focus groups, finding that students who participated in the programme showed a shift in their attitude about early pregnancy, such as postponing the expected age of having their first child. The programme’s success is attributed to its emphasis on education, future development, and mutual respect among peers, rather than solely focusing on negative outcomes.

Community leaders have observed a noticeable drop in teenage pregnancy rates. This progress is encouraging, but the report emphasises the need for continued support and a long-term strategy. Misunderstandings about family planning still need to be addressed at a community level to achieve a sustainable reduction in teenage pregnancy.

The study concludes that social engagement is a potent tool for empowering young people and improving sexual and reproductive health knowledge.

The baseline and follow-up study reports are available on the Good Neighbors UK website. The paper on the results from the baseline study has been released in Children & Society.

We gratefully acknowledge the support of the Good Neighbors Alliance, known globally as Good Neighbors International, a federation of independent but affiliated Non-Government Organisations operating in over 50 countries.

You can read the paper, “Up and Down With… Polarisation? Intrinsic and Instrumental Polarisation Dynamics in US Climate Policy Debates”, online.

Political elites in the US are ideologically divided over climate change. We identify two perspectives: 

• The intrinsic view on ideological climate polarisation views climate beliefs as entrenched parts of an actor’s identity and posits that ideological positions have factually shifted towards ever more extreme positions over time.
• The instrumental view, in contrast, emphasises that polarisation entrepreneurs mobilise their constituency to participate in the climate policy debate by amplifying ideological differences over climate-related focusing events when they arise, leading to fluctuations in visible polarisation, rather than a steady trend. 

This study examines which of the two perspectives holds in US Congressional and subnational media debates by analysing time trends of polarisation and phases of structural stability. We distinguish between endogenous events, which can be attributed to the political process, and exogenous focusing events, such as extreme events or those related to the international climate regime, and investigate which type of event tends to be associated with changes in polarisation. 

Applying two novel time series measures for discourse networks - structural polarisation and the detection of phases of structural stability - to the climate debate during the 112th to 114th Congress (2013–2017) and subnational print media in four swing states, we find that exogenous events are largely irrelevant while endogenous political dynamics increase the polarisation of the debate considerably. 

We find ups and downs of polarisation corresponding to distinct structural phases in which polarisation is linked to participation. This temporal fluctuation of polarisation around endogenous political events is consistent with the instrumental perspective.

Drawing on their expertise in population data, large scale social surveys, and the use of data to inform fair and effective health policy, the Manchester academics highlight the vital role of robust evidence in ensuring policy keeps pace with societal change.

Launched in 1991, the Health Survey for England, has been the backbone of health policy evidence for more than three decades, providing annual, nationally representative data to monitor the nation’s health and guide healthcare delivery. At the June 2025 conference, the government confirmed that NHS England would no longer run the survey. While details of any replacement are yet to be confirmed, discussions are under way on the future of population health surveys in England.

Since the conference, The UK Data Service has acted swiftly to ensure researchers’ voices are heard in the national debate:

• Boosting consultation responses – negotiating with Department of Health and Social Care (DHSC) and the Office for National Statistics (ONS) to re-open a user consultation on the future of population health surveys for three weeks in July, generating a further 140 responses from health survey users.
• Showcasing impact – collaborating with a key health survey user to publish a Data Impact blog highlighting the importance of the survey: Help shape the future of population health surveys.
• Supporting decision-makers – at DHSC/ONS’s request, preparing a written summary of the Health Survey for England’s value and impact, including user testimonies, to feed into their internal report (due end of September), and advising on an expert peer-reviewers.

Through this work, Manchester academics and the UK Data Service are playing a pivotal role in shaping the future of the Health Survey for England, influencing how health data will be collected to meet the challenges of a changing world.

Policy subsystems are comprised of competing advocacy coalitions, in which public and private political actors with shared belief systems learn from each other and coordinate their strategies in the pursuit of influencing policy making in their favour. 

While numerous studies have focused on the longevity and structural stability of advocacy coalitions, there is scant theory and evidence on how nascent policy subsystems bifurcate into stable, competing coalitions. 

This article proposes a three-stage model of problem discovery, differentiation, and consolidation. 

We apply discourse network analysis to the nascent subsystem of the UK's COVID-19 response in order to study these phases and discuss their applicability and implications for other institutional and issue contexts.

The paper “Goodbye human annotators? Content analysis of social policy debates using ChatGPT” can be read online.

Content analysis is a valuable tool for analysing policy discourse, but annotation by humans is costly and time consuming. ChatGPT is a potentially valuable tool to partially automate content analysis for policy debates, largely replacing human annotators. 

We evaluate ChatGPT’s ability to classify documents using pre-defined argument descriptions, comparing its performance with human annotators for two policy debates: the Universal Basic Income debate on Dutch Twitter (2014–2016) and the pension reforms debate in German newspapers (1993–2001). We use the API (GPT-4 Turbo) and user interface version (GPT-4) and evaluate multiple performance metrics (accuracy, precision and recall). 

ChatGPT is highly reliable and accurate in classifying pre-defined arguments across datasets. However, precision and recall are much lower, and vary strongly between arguments. These results hold for both datasets, despite differences in language and media type. Moreover, the cut-off method proposed in this paper may aid researchers in navigating the trade-off between detection and noise. 

Overall, we do not (yet) recommend a blind application of ChatGPT to classify arguments in policy debates. Those interested in adopting this tool should manually validate bot classifications before using them in further analyses. At least for now, human annotators are here to stay.

The paper “When does discursive change happen? Detecting phase transitions in discourse networks of sustainability transitions” can be found on ScienceDirect.

Sustainability Transitions Research (STR) confronts complex societal challenges by examining societal shifts and their trajectories. An emerging perspective in STR is discursive approaches, which analyse the role of discourses and discourse coalitions in shaping sustainability transitions. However, discursive approaches face challenges regarding the analysis of sustainability transition processes as complex, temporal processes of stability and change. 

We discuss the nature of these challenges and extend the method of discourse network analysis (DNA) by measuring distinct temporal states (phases of stability) in discourse networks and detecting phase transitions (significant changes) between these discursive states. 

Whereas most approaches analyse discursive changes in a top-down way, we introduce a method for the bottom-up detection of discursive stability and change. This facilitates a more accurate tracing of how sustainability transitions unfold over time. An empirical application of this extension to the discursive networks around the introduction of a Low Emission Zone demonstrates how and when discourses and actors display significant structural shifts. This methodological innovation addresses the need for measuring stability and change in the complex, discursive, temporal dynamics of sustainability transitions.

Highlights

• Identification of 3 challenges of discursive approaches to energy transitions.
• Discourse Network Analysis is extended by drawing on mathematical network science.
• Bottom-up detection of temporal phases, states, transitions in discourse networks.
• Energy transitions should be analysed through the lens of temporal networks.
• Case study on the changing debate on a low emission zone in Ghent, Belgium.

You can read the paper, “Multiregional Population Forecasting: A Unifying Probabilistic Approach for Modelling the Components of Change”, on Springer.

Regional population forecasts are important for planning and understanding how populations are changing and redistributing. To forecast regional population changes, one must have a mechanism to capture different sources of population growth. In low fertility and developed societies, the main factors driving population redistribution are internal migration and immigration, for which both tend to concentrate people towards large metropolitan areas. 

In this article, we extend the multiregional cohort-component population projection model developed by Andrei Rogers and colleagues in the 1960s and 1970s to be fully probabilistic, by using Bayesian inference. We apply the model to forecast population for eight states and territories in Australia. 

The projections are based on forecasts of age-, sex- and region-specific fertility, mortality, interregional migration, immigration and emigration. The approach is unified by forecasting each demographic component of change by using a combination of log-linear models with bilinear terms. 

This research contributes to the literature by providing a flexible statistical modelling framework capable of incorporating the high dimensionality of the demographic components over time.

Forecasts of a population totals by sex for states and territories in Australia, b total population. States or territories: NSW—New South Wales, VIC—Victoria, QLD—Queensland, SA—South Australia, WA—Western Australia, TAS—Tasmania, NT—Northern Territory, ACT—Australian Capital Territory. 

Prior to starting the position, Mariana was working on her PhD in Sociology at the University of Oxford. Her PhD was titled “A Sociodemographic Study of Only-children and Only-child Fertility” and explores only-child fertility from a sociodemographic perspective. 

At the University of Oxford she also worked as a research assistant on the project “Digital Gender Gaps”, focusing on combining traditional surveys and big data for population analysis. Her main research interests are family demography, fertility and the use of formal demographic methods for exploring changes in kinship networks.

Since joining The University of Manchester, she has been co-teaching in SOST10012-Understanding Social Media Data and SOST2002-Essentials of Survey Design and Analysis.

Prior to moving to the UK, Mariana trained as a demographer at the Centre for Development and Regional Planning (Cedeplar) in Brazil, where she was awarded an MSc, and developed her research interests in family demography, as well as formal demographic methods.

The award is presented annually to students who demonstrate exceptional contributions to artificial intelligence (AI) and data science research.

Constanza's doctoral research employs advanced machine learning techniques to examine the causal impact of front-of-package food labelling on consumer behaviour, drawing on both randomised trials and observational data. Her research in this field has implications in areas ranging from health causal inference to data linkage.

She will receive funding to continue the research and join the Turing Institute network, a collaborative platform aimed at advancing AI and data science.

Congratulations to Constanza on this remarkable achievement!

Further information on the Turing Enrichment Scheme can be found on The Alan Turing Institute website.

“Ground-truthing political elites in the public sphere: Measuring the arena effects of elite opinion” is available to read online.

Political elites express their ideological positions on contentious issues across various arenas in the public sphere. Social science research often relies on data extracted from various media or political and administrative sources, as well as surveys that are administered directly with the political actor. 

Although some studies compare ideology across different sources, few systematically analyse how political actors adjust their ideological messaging to the audiences in the respective communication arenas and how such changes are associated with systematic bias in data sources. 

This paper uses a unique dataset, combining climate policy belief observations from three arenas - social media, Congressional testimony, and surveys - on identical ideological variables and during the same time period. 

We apply item response theory to understand how responses differ by arena and find that ideological communication on X is most left-leaning, Congressional testimony is most right-leaning, and surveys, the data source with the smallest potential arena effect, is in the middle. We also find that actors with strong ideological leaning moderate their positions on social media and in Congress. 

These findings enhance our understanding of strategic communication depending on audience context and inform social research on biases when analyzing specific data sources.

I am a Professor of Social Statistics in the Department of Social Statistics at The University of Manchester, which is part of the School of Social Sciences. I am also a member of the Mitchell Centre for Social Network Analysis and the Cathie Marsh Institute for Social Research. 

Before joining Manchester in April 2024, I was a Professor of Comparative Politics in the Department of Government at the University of Essex. 

I am also a DFG Mercator Fellow in the Research Training Group on Digital Platform Ecosystems at the University of Passau (2022-2027) and serve as chair of the Political Networks Section of the American Political Science Association (APSA) in 2024-2025. 

My main research interests are politics and public policy, network analysis and complex systems, statistical modelling, and computational social sciences. I am best known for my work on discourse network analysis (and the software Discourse Network Analyzer), the texreg R package, and my work on statistical models for longitudinal network data (e.g., implemented in the btergm R package). 

My research has appeared in leading political science journals (e.g., AJPS, JOP, BJPS), public policy and administration journals (e.g., PSJ, JPART), technical journals (e.g., Physica A: Statistical Mechanics, Network Science, JStatSoft), and outlets in other fields (e.g., Nature Climate Change, Addiction, Personality and Social Psychology Bulletin). 

More information on Professor Philip Leifeld can be found on his website. 

The paper, “Learnings from a decade of data fellows: Co-creation of a data skills framework for non-stem students”, is available to read online. 

This workshop provided a reflection on an experiential learning model developed in the UK. The Data Fellows initiative supports undergraduate social science and humanities students to develop their data skills through work placements. 

The findings have resulted in a book, academic articles and international presentations which collectively provide a substantial body of evidence to illustrate how non-STEM (science, technology, engineering and maths) students can learn and practice their data analytic skills and progress into data and technical careers. 25% of the 373 Data Fellows placed to date have been from historically under-represented groups and 70% have been female. 

A case study was presented to show a journey from a first degree in social science to a postgraduate degree in data science. The aim of the workshop was to challenge the deficit narrative that can accompany the teaching of data skills in the social sciences and explore whether a suitable data skills framework exists or could be developed.

For more information about Jackie visit her research profile.

Slides and recordings (if available) from these events can be accessed on the event web page by clicking the links above. Recordings are also available on the UKDS YouTube channel. 

For information about upcoming events visit the UK Data Service website.
 

Our colleague, Dr Nikita Basov, has recently published a study, “The Space of Coordination: Accounting for Multiple Expert Knowledges in Environmental Communication”, in Environmental Communication. 

The authors propose an account of environmental communication as a dynamic space involving multiple expert knowledges to address growing diversity of expert knowledges in environmental communication. 

To enable this account, they offer a computer-assisted mapping technique relating these knowledges to each other at various time points. 

The authors illustrate the proposed approach with a case study on flood risk management in the UK, where diverse expert groups have been engaged in a shared communication space which enabled coordination of their knowledges over time. 

They conclude that researchers can use the proposed technique to trace knowledge dynamics in environmental communication. Communication practitioners can use it to map thematic areas that experts specialise in, identify knowledge gaps, find relevant documents, and facilitate expert communication. 

The project “Building computational capacity among global data service staff” was funded for the UKRI's call on “Digital infrastructure: new approaches to skills or software."

Digital research infrastructures connect researchers, policymakers and innovators with the computers, data, tools techniques and skills to undertake ambitious and creative research. 

Social science data services worldwide play a key role in the digital research infrastructure by curating and managing access to many forms of social and economic data as well as promoting increased data literacy among the community. 

Recognising the growing importance of computational skills for data services staff in the social sciences, this project, led by academics affiliated with the UKDS, will address the critical need for training. 

The aim of this project is to build capacity within the international data services community, by providing upskilling opportunities for UK Data Service (UKDS) staff and developing foundational level data skills modules in computational social science for the wider global community. It will also establish a community of practice to provide enhanced support to users through the lifetime of the project and beyond. 

Direct beneficiaries of this project will include UKDS staff who will be given the opportunity to upskill in computational skills, as well as global data service staff who will be given access to a foundational-level online structured course(s) on computational social sciences. 

Through both upskilling mechanisms, this project will enhance data services capacity both in the UK and globally, enhance the careers of data service professionals, and through the establishment of a Community of Practice will contribute to a culture of lifelong learning.

Attendees explored how sociotechnical changes might shape the future of research, hearing from a variety of experts and collaborating with researchers and professionals from different sectors and disciplines. 

In addition to fostering vibrant discussions, Methods Con: Futures 2024 featured the launch of NCRM’s Futures Briefs a series of publications reflecting on how sociotechnical changes might impact the way social science is conducted. 

The event was a resounding success, garnering excellent feedback for its interdisciplinary approach, valuable insights and providing an opportunity to engage with cutting-edge methods. 

The NCRM is proud to have facilitated such a dynamic exchange of ideas and looks forward to its continuing commitment to staying at the forefront of methodological innovation in the social sciences. 

During the month of September, University of Manchester colleagues at the UK Data Service (UKDS) delivered the following events: 

• Computational social science drop-in (10 September, J. Kasmire, Louise Capener and Nadia Kennar) 
• Data in the spotlight: Large scale social surveys (24 September, Nigel Denoronha and Placide Abasabanye) 
• Survey data drop-in (24 September, Alle Bloom, Pierre Walthery) 
• Presentation at RSS International Conference 2024: Coding in public: recognising vulnerability as a barrier to reproducibility (2 September, J. Kasmire) 
• Presentation at RSS International Conference 2024: Developing quantitative data driven research skills in social science students outside the classroom (2 September, Vanessa Higgins) 
• Presentation at NCRM methods showcase: The UK Data Service Data Skills Framework (11 September, Vanessa Higgins)

Slides and recordings (if available) from these events can be accessed on the event web page by clicking the links above. Recordings are also available on the UKDS YouTube channel.

For information about upcoming events visit the UK Data Service website. 

The Department of Social Statistics celebrates the publication of the report “Exploring the Intersection of Technology and Democracy”. 

Led by Professor Mark Elliot, the 2023 Futures Summer Camp, funded by SPRITE+, was a collaborative effort with the Research Institute for Sociotechnical Cyber Security (RISCS) and facilitated by the School of International Futures (SOIF). 

The event aimed to foster future-focused collaborations across various disciplines to address challenges in digital security, identity, privacy, and trust.

The camp brought together 28 experts from academia, government, and industry for a two-day workshop to explore how technological advancements might impact democratic institutions over the next 5-15 years. 

Participants discussed potential threats and opportunities, considering actions to mitigate negative outcomes and maximize positive impacts.

Key themes and insights from the workshop will shape SPRITE+’s future initiatives, including a TIPs-focused expert meeting in May 2024 and a themed sandpit in June 2024 titled "Living in an Inauthentic World". 

This event underscores the importance of interdisciplinary collaboration in preparing for the future intersection of technology and democracy.

The report can be accessed here.

On Thursday 16 May, the department of Social Statistics held its away day at HOME, in central Manchester. The event was a resounding success, fostering a collegial environment where important discussions flourished. 

Key themes included research collaborations within the department and support for early career academics. The day’s activities not only sparked meaningful conversations but also played a crucial role in shaping the future direction of the department.

During the month of April, University of Manchester colleagues at the UK Data Service (UKDS) delivered the following events:

• Computational Social Science Drop-in (9 April, J. Kasmire, Nadia Kennar and Louise Capener)
• How to become a computational social scientist (16 April, Louise Capener and Nadia Kennar)
• N8 CIR Synthetic Data Generation Event (17 April, J. Kasmire)
• SRMS Dissertation workshop: Locating Research Data and Data Access (18 April, Vanessa Higgins)
• Getting Started with Secondary Analysis (22 April, Nigel de Noronha)
• DRTN Lessons from Covid-19 data (30 April, J. Kasmire and Alle Bloom)

Slides and recordings (if available) from these events can be accessed on the event web page by clicking the links above. Recordings are also available on the UKDS YouTube channel.

For information about upcoming events visit the UK Data Service website.

Professor Mark Elliot (Social Statistics) has been awarded an ESRC grant for the project Enhancing Data Accessibility and Security through Innovative Data Synthesis (EDASIDA).

The EDASIDA project aims to transform both data accessibility and confidentiality through innovative data synthesis techniques. In essence, the project will develop a methodology for providing tailored teaching datasets and systematic disclosure risk assessment methods.

The new methodology involves leveraging cleared analytical outputs from data services as the basis for generating synthetic data using genetic algorithms. The goal is to provide trainees with data that not only closely resembles real-world data but also yields analytical output very similar to that of the real data, enhancing the training experience. 

A pilot study conducted in collaboration with Administrative Data Research UK, demonstrated the feasibility of generating synthetic teaching datasets with both high utility and no marginal disclosure risk. The pilot dataset (a synthetic version of the linked ASHE-census dataset) was successfully used in a ADR-UK training course in April 2024.

The approach also offers a route to formalise assessment the disclosure risk associated with analytical outputs from safe settings. By embodying statistical outputs in synthetic data, it enables a systematic evaluation of disclosure risk, addressing the informality and potential inconsistencies present in current output checking procedures. 

Finally, the project aims to bolster the federated services agenda by exploring the creation of synthetic linked data from using analytical outputs from data of multiple services. This approach expands the possibilities of data synthesis without the need for actual linkage and elaborate governance of infrastructure, such as trusted third parties.

On Wednesday 24 April, the Department of Social Statistics hosted the grand finale of the Data Science in Practice Series. 

Karolina Michalska from KANTAR's London office captivated an audience of eager students from the MSc Social Research Methods and Statistics program and the undergraduate Data Analytics pathways.

Karolina dazzled the attendees with an exhilarating presentation showcasing her groundbreaking work at KANTAR. 

She offered an in-depth and eye-opening overview of the diverse and dynamic roles available for data scientists within the company. Her presentation was not only highly informative but also sparked a vibrant and engaging discussion, leaving everyone inspired and buzzing with ideas.

On March 22, Dr Nikita Basov received laudation as the recipient of the Friedrich Wilhelm Bessel Research Award from The Alexander von Humboldt Foundation for outstanding research achievements, as part of the Symposium for Research Award Winners in Bamberg, Germany, March 21-24, 2024. 

The award was given for major scientific contributions over the past 10 years, including the pivotal role in building the field of socio-semantic network analysis and the pioneering input into understanding the dual relationship between culture and social structure via innovative methodological combinations of statistical network modelling and interpretive analysis of ethnographic data on creative collectives. 
 

During the month of March, University of Manchester colleagues at the UK Data Service (UKDS) delivered the following events:

• Dissertation projects: Introduction to secondary analysis for qualitative and quantitative data (11 March, Alle Bloom) 
• Computational Social Science Drop-in (12 March, Jools Kasmire, Nadia Kennar and Louise Capener) 
• Developing research questions (13 March, Jools Kasmire and Nigel de Noronha) 
• Coding in public: barriers to reproducibility (19 March, Jools Kasmire) 
• Developing research questions (27 March, Jools Kasmire and Nigel de Noronha) 

Slides and recordings (if available) from these events can be accessed on the event web page by clicking the links above. Recordings are also available on the UKDS YouTube channel. 
For information about upcoming events visit the UK Data Service website. 
 

Chris Shumba, Head of Data Operations (Football) at Manchester United, visited the university on Wednesday, 13 March, to share insights with students enrolled in the "Data Analytics" pathways of the BASS/BAEcon programmes. 

In his talk, Shumba provided valuable perspectives on career pathways in data science and discussed the technologies shaping the field today. 

His presentation was well-received by the audience, sparking meaningful discussions and leaving attendees eager for future engagements with Shumba.

Dr Nikita Basov (Department of Social Statistics) has been awarded a British Academy Small Grant. The grant will fund the project titled "Statistical Modelling of Meaning Creation in Interaction: A Test of Core Social Theories.".

In this project, Dr. Basov will explore the capabilities of recently advanced network modelling methods to test two core social theories: symbolic interactionism and social constructivism. By doing so, he aims to provide the first comprehensive quantitative test of these theories.

These new methods allow the disentangling of 3-layer socio-cultural network structures that connect individuals, words, and material objects within small groups of collocated individuals. This, in turn, facilitates the cross-validation of the fundamental assumptions that both theories make about how cultural meanings are formed across different types of interactions, structural levels, and time spans.

The project will utilize a globally unique multi-dimensional dataset capturing socio-cultural dynamics in five groups of visual artists over two years.

The development of statistical models for analysing how cultural meaning is created in society will constitute a significant contribution to social science. The results of testing core social theories have the potential to catalyse fundamental changes in social sciences and beyond.

Prof. Arek Wisniowski published in February a new article in the prestigious journal “Migration Studies”. This new article explains that undercounting is a critical issue in migration statistics, resulting in bias. 

It typically arises from insufficient reporting requirements and problems with enforcing such requirements. The main sources of information on undercounting are the metadata accompanying official statistics and expert opinions. 

However, metadata and arbitrary expert opinions may be limited by overlooking important details in migration data shared by various countries. This includes potential oversight of changes in methodologies, definitions, or retrospective updates to the data following censuses.

In their paper, Prof. Wisniowski and his colleagues present a methodological solution with three objectives to address undercounting in international migration data. First, they provide an overview of available metadata and expert opinions on undercounting in European migration flows. 

Second, they propose a novel data-driven approach that incorporates year-specific and duration-of-stay-adjusted classifications. The proposed methodological solution relies on comparisons of flows in the same direction reported by a given country with high-quality data reported by another set of countries. 

They use bilateral migration data provided by Eurostat, UN and selected national statistical institutes. Duration-of-stay correction coefficients are derived through an optimization model or borrowed from the literature. Metadata and expert opinion scores can also be integrated to classify undercounting. Finally, they provide a dynamic classification of undercounting for 32 European countries (2002-2019), accessible through an online Shiny application, offering flexibility and adaptability.

Their findings highlight significant undercounting in new EU member states, particularly Bulgaria, Latvia, and Romania. Interestingly, other European countries, including those presumed to maintain reliable population statistics, also exhibit notable periods of undercounting.

The UK Data Service (UKDS) ran several events in the month of February.

During the month of February, University of Manchester colleagues at the UK Data Service (UKDS) delivered several training courses in partnership with the Office for National Statistics, the Home Office, and the Scottish Government, among others.
 

These included:

• Crime Surveys User Conference, 6th at UCL, London (Sarah King-Hele)
• Using multivariate census 2021 data to develop area profiles, 7th, online (Nigel de Noronha) 
• Introduction to Machine Learning, workshop for the University of Nottingham Data Fest, 7th, online (Jools Kasmire) 
• Computational Social Science Drop-in, 13th, online (Louise Capener and Nadia Kennar)
• Mapping crime data in R: An introduction to GIS and spatial data, 13th, online (Nadia Kennar)
• Data in the spotlight: Large scale social surveys, 14th, online (Sarah King-Hele)
• Mapping crime data in R: code demo, 16th, online (Nadia Kennar)

For more information about these events and future courses, you can visit the Social Statistics website.

Aidan O’Brien and Zainab Kapasi (Data scientist at TalkTalk) came to the Department of Social Statistics to talk about their roles as Data Scientists at TalkTalk (a leading U.K. provider of mobile and internet services). 

They explained to our students how data science helps in their sector and what type of careers are available to aspiring data scientist.

A new article by Dr Nikita Basov (Social Statistics) has appeared in the leading international journal “Poetics”. 

The paper notes that in creative settings, people are often put together physically - to stimulate the exchange of ideas and practices. However, little is known of how exactly different spatial zones foster such creative sociality. 

The new paper by Basov et al. draws on a combination of interviews, observations, and surveys - analysed with an innovative mixture of abductive coding, computational space analysis, and statistical network modelling - to unveil how room sharing and object usage relate to friendships and collaborations in artistic residences. 

While social ties are indeed associated with joint material embeddedness, different types of spatial zones appear to encourage unexpected types of social ties. 

The findings inform the practice of creative space organising and the proposed approach enables explanatory analysis of the relation between material space and sociality in various contexts.
 

• Professional patios, emotional studios: Locating social ties in European art residences paper

Are Children School Ready? Research by Dr. K. Purdam and colleagues from Social Statistics has highlighted the substantial differences in School Readiness at the individual, school and local area levels in England. 

The educational attainment levels of children in state-funded schools in England are lower than in many countries with comparable levels of economic development. There are also striking differences at the local level across England. To understand these differences it is important to examine children’s development in their early years. 

This research uses multilevel analysis of the National Pupil Database to investigate child development at ages 4 and 5 years old at the individual, school and local levels including within a case study urban area. Child development is assessed using teachers’ observations to measure what is termed School Readiness. This is based on a child’s communication, literacy and numeracy skills and their physical, personal and social development. 

The findings reveal substantial differences in School Readiness at the individual, school and local area levels including in terms of sex, ethnic background, age in the school year, welfare benefit entitlement and local area income deprivation level. Such differences are also evident across the separate Early Learning Goals that are used to assess School Readiness. 

Between local areas children with similar backgrounds can vary considerably in their likelihood of being categorised as School Ready. Many children face multiple disadvantages as a consequence of different interlinked factors including where they live. The gap in the levels of School Readiness has long-term implications for the individuals themselves and for society more widely. 

Whilst increasing the levels of School Readiness is a key target in the UK Government’s Levelling Up policy, tackling the stark inequalities will take considerable investment, highly targeted support and engagement across the home and school learning environments. 

The research is available to read here.

Research by Dr Alex Cernat, Dr Hafsteinn Einarsson and Professor Natalie Shlomo from Social Statistics has highlighted new methods to improve the accuracy of cross-national surveys. 

Cross-national surveys run the risk of differential survey errors, where data collected vary in quality from country to country. 

Responsive and adaptive survey designs (RASDs) have been proposed as a way to reduce survey errors, by leveraging auxiliary variables to inform fieldwork efforts, but have rarely been considered in the context of cross-national surveys. 

Using data from the European Social Survey, we simulate fieldwork in a repeated cross-national survey using RASD where fieldwork efforts are ended early for selected units in the final stage of data collection. 

Demographic variables, paradata (interviewer observations), and contact data are used to inform fieldwork efforts. 

Eight combinations of response propensity models and selection mechanisms are evaluated in terms of sample composition (as measured by the coefficient of variation of response propensities), response rates, number of contact attempts saved, and effects on estimates of target variables in the survey. 

We find that sample balance can be improved in many country-round combinations. Response rates can be increased marginally and targeting high propensity respondents could lead to significant cost savings associated with making fewer contact attempts. 

Estimates of target variables are not changed by the case prioritizations used in the simulations, indicating that they do not impact nonresponse bias. 

We conclude that RASDs should be considered in cross-national surveys, but that more work is needed to identify suitable covariates to inform fieldwork efforts.

The research is available here.

Dr. Tatjana Kecojevic, a lecturer in Social Statistics, has been honoured with the Outstanding Digital Enhanced Teaching award for the 2022/2023. 

A cornerstone of her teaching methodology is the creation of reproducible teaching materials using a combination of R and RMarkdown. The approach empowers students to engage with course content in a meaningful way and also ensures that educational materials can be easily replicated, contributing to a more effective learning process. 

A workshop focused on reproducible research techniques is also being held. The workshop will use a specially developed reproducible platform dedicated to advancing the principles of reproducibility in research. 

The workshop and the learning resources will be a valuable resource for researcher practitioners seeking to enhance their research methodologies. For more information and to register for the workshop, please visit the website.

The University of Manchester is one of five partner organisations who together have been awarded £37.5 million from The Economic and Social Research Council to fund the UK Data Service until 2030. Of this award £7 million is to support our team at the Cathie Marsh Institute (CMI), now 13-strong, where Vanessa Higgins and Debora Price lead the national Training and User Support functions of the service.
 

Welcoming the award, Professor Andrew Miles, Director of Research, School of Social Science said:

The UK Data Service provides access to the largest collection of economic, social and population data in Europe. It hosts over 9,000 datasets including the UK Census, Understanding Society and the Labour Force Survey. There are 50,000 registered users, from 148 countries.
 

Professor Debora Price, Deputy Director of the Service and lead Investigator at the University of Manchester, said:

The cross-site Training and User Support service led by the CMI team at Manchester has grown significantly in recent years with an outstanding track record of providing appropriate training programmes. 

Last year, they ran over 100 live training events and there is a large and growing range of online materials, from interactive data skills modules, to written guides and how-to videos for all levels of user. Feedback from users is excellent with 97% of respondents last year saying they would recommend their training event to others.
 

Dr Vanessa Higgins, Co-Investigator at the University of Manchester, and national Service Director for Training and User Support said:

Our research has examined the inequalities in health using Office for National Statistics (ONS) data on life expectancy. The differences in life expectancy between local areas in the UK can be as high as 25 years. 

The deprivation levels of an area and premature mortality are strongly associated, and the differences in life expectancy between economically deprived and prosperous areas are increasing. In some areas the long-term increases in life expectancy have stalled or even reversed. 

A number of interrelated factors are associated with lower life expectancy. These include access to health care, income, employment, smoking and alcohol consumption, diet, exercise, the local environment, social status and social isolation.
 

What’s on offer?

How does where you live affect your life expectancy? What can we do about it? 

Find out at this pop-up information session, based around the striking differences in life expectancy at key points along the River Mersey and the River Thames. 

The maps are using the River Mersey and the River Thames to link life expectancy data to well known places. The researchers will be on hand to answer questions and leaflets will also be given out with information about the research and the findings.
 

Who’s leading the event?

• Dr Kingsley Purdam
• Dr Diego Perez Ruiz
   

Event Booking details:

• Turn up on the day - no need to book
   

For more information about this event, visit the Festival of Social Science website.

The main objective of the event was to provide students and the younger generation with the appropriate assistance for their exploration of quantitative analysis at the early stages of their careers.

The Social Statistics Hackathon attracted a wide and diverse group of participants from industry to three different universities. The programme consisted of a mixture of talks, teamwork and presentation competitions.

The groups of participants were asked to conduct analyses on data from the UK Census 2021 to find hidden associations between a set of variables.

At the end of the Hackathon, the head of the Department of Social Statistics, Dr Arkadiusz Wisniowksi presented awards to the final winners of the prizes. A group comprised of two students from The University of Manchester and Manchester Metropolitan University won the first prize.

New research into the affordability of funerals in the UK by K. Purdam, G. Chatzi and A.M. Nicoriciu from the University of Manchester has been highlighted by the BBC.

The research drew on official survey data and interviews with older people aged 50 years and older living on low incomes. Substantial numbers of older people did not have the financial resources to be able to afford the costs of an expense such as a funeral, particularly those people living on low incomes and those in poor health.

There were widespread concerns about the costs of funerals and the burden on the families people leave behind. 

As one interviewee aged 86 stated: 

“I save £2 coins for my funeral.” 

Many older people had not made a plan for their funeral. As one interviewee aged 75 commented: 

“It’s the height of irresponsibility, putting the burden on someone who is grieving.” 
 

It is important that funerals are affordable, and that people are supported during a time of grief and vulnerability. Those people who die without family or close friends should also be treated with respect. The full research findings will be published shortly.

New research by staff from Social Statistics has reviewed the methodology of one of the most comprehensive indices of gender equality, the Gender Equality Index by the European Institute for Gender Equality (EIGE). 

The research shows that in addition to the use of the correcting coefficient, other methodological choices (such as the use of ratios and geometric means) result in an unjustified penalisation of lower-GDP countries and the reinforcing of biased assumptions about gender equality progress.

The research calls for greater transparency around theory, method and the relationship between the two while also proposing methodological improvements. 

These changes would bring the EIGE index closer to fulfilling its potential to provide a nuanced understanding of gender equality levels in the European Union and effectively inform policy development toward social change.

The full research article is available here:

Schmid, C.B. and Elliot, M., 2023. “Why Call It Equality?” Revisited: An Extended Critique of the EIGE Gender Equality Index. Social Indicators Research.

The UK Data Service and Social Statistics staff co-led two data user conferences with the Office for National Statistics, the Department for Work and Pensions, NatCen and University College London. 

For more information see:

• Health Studies User Conference
• Family Finance User Conference

Alle Bloom has presented the work of the UK Data Service at the European Survey Research Association conference in Milan. Further details are available here.

Big data and how important insights can be gained from the vast quantities of data we generate in our everyday lives was highlighted by Dr Julia Kasmire from the UK Data Service on BBC Radio 4. More details here.

The UK Data Service is delighted to announce the winners of this year’s UK Data Service Dissertation Award. 

The award celebrates undergraduate dissertations based on the use of archived data available through the UK Data Service. 

The winners were:

• Aiste Timukaite, BA (Hons) Criminology, University of Manchester. 
  A quantitative analysis of victim’s rational decision to report violent crime: does trust in the police matter?
• Caitlin Lin, Population Health Sciences (Data Science), University College. London (UCL). 
  A quantitative study into the control of diabetes in older age: who goes on to have eye problems?
• Finlay Yates, Economics (BA), Durham University. 
  The impact of the minimum wage on employment: An assessment of the effect of employer concentration.

Further information can be found here.

Social Statistics staff led a session on children’s wellbeing for researchers and policy makers at the Royal Statistical Society Annual Conference. 

The event highlighted research on: School Readiness, Covid-19 and the impact on wellbeing and attainment and young people’s mental health. 

The various data sources for researching wellbeing were presented by the UK Data Service and new innovative approaches for linking data were also highlighted.

You can read more about the conference and the research here:

• RSS International Conference 2023

Social Statistics and UK Data Service staff recently presented new research at the World Statistics Congress. Professor Carter spoke about the importance of data literacy and the value of work placements. 

Dr. Vanessa Higgins discussed the UK Data Service online data skills training events and the results of a qualitative research project to explore how Social Sciences, Arts and Humanities (SHAPE) students participate in UK Data Service training events to develop their data literacy skills. 

The session was chaired by Professor Natalie Shlomo. You can read more about the work here:

• Developing a future pipeline of applied social researchers through experiential learning: The case of a data fellows programme
• Vanessa Higgins to feature at the ISI World Statistics Congress in Ottawa

Jingwen Zhang from Social Statistics at the University of Manchester recently presented her research at the British Gerontology Conference. The research examines ageing and internal migration in China. 

The research found that not only current migration status, but also the timing of migration and the sequence of migration destination, are associated with health in later life. 

Migrating in early adulthood is associated with better mental health in later life, whereas internal migrants who subsequently return to rural settings have similar mental health outcomes to rural residents, who have comparably poorer health outcomes. 

Migration and health in later life is highly gendered. For example, migrating before marriage has an empowering effect for rural women and they are more likely have better physical and mental health outcomes as they age. For married couples, the relationship between migration trajectories and later-life health for men and women also depends on the migration trajectories of their spouses. 

You can read more about the research and findings here:

• Understanding the longitudinal dynamics of rural–urban mental health disparities in later life in China
• Gender differences in rural-urban migration and its impact on depression in later life
• Do migration outcomes relate to gender? Lessons from a study of internal migration, marriage and later-life health in China

Professor Jackie Carter talks about her passion for helping young people overcome barriers and how they can pursue their careers in research and policymaking. Her recent book is also available from Sage.

The full Times Higher Education article is available here.