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Exploring Work, Employment and Income through National and European Datasets
Full text linkThis video features presentations from three researchers at UK data resources who discuss ways of exploring employment, work and income through national datasets.
The speakers are: Pierre Walthéry, who introduces key datasets and instruments available at the UK Data Service to study work and employment, with a particular focus on the Labour Force Survey; Van Phan discusses the newly-linked ASHE-HMRC PAYE and Self-Assessment dataset, exploring how linking ASHE and PAYE data addresses gaps in understanding labour market changes in the interval between annual ASHE surveys; Jule Adriaans utilises European Social Survey Round 9 data to examine perceptions of justice and fairness in Europe, addressing the question, “How (un)fair is workers’ pay across Europe?” The talk showcases how the European Social Survey aids in understanding attitudes toward work, employment, and income.
The presentations were recorded for a webinar hosted by the Data Resources Training Network, titled Exploring Work, Employment and Income through National and European Datasets, which took place on Monday, 9 December 2024
Mass Observation Archive
Full text linkKirsty Pattrick (Mass Observation Archive, University of Sussex) here outlines the scope of the Mass Observation Archive – including what types of data it holds, what makes it ‘big’ (longitudinal, wide range of topics and observers) and some approaches that have been taken to analysis (thematic, narrative, longitudinal and comparative approaches)
The Breadth and Depth Approach to Big Qual Data Analysis
Full text linkIn this video, four speakers discuss the approach to analysing big qual data that they co-developed. The approach is the ‘breadth and depth’ approach, and the four speakers are: Susie Weller (University of Oxford), Emma Davidson (University of Edinburgh), Ros Edwards (University of Southampton) and Lynn Jamieson (University of Edinburgh)
Exploring Ageing through National Datasets
Full text linkThis video features presentations from three researchers on ways of exploring ageing using secondary, quantitative data from national datasets.
George B. Ploubidis considers a cross-generational life-course approach to healthy ageing in the 21st century.
Athina Vlachantoni explores pension protection among minority ethnic communities in the UK.
Bram Vanhoutte examines the gap between subjective and chronological age, the role of functional health, and differences between birth cohorts.
The presentations were recorded for a webinar hosted by the Data Resources Training Network, titled Exploring Ageing through National Datasets, which took place on Thursday, 9 October 2025
In Conversation: Mark Elliot and Christina Silver – AI and Social Science
Full text linkIn the fifth part of NCRM’s In Conversation series on the topic of AI, Mark Elliot speaks with Christina Silver about AI and social science.
Topics covered include what's happening in the qualitative-AI space technically, in terms of capabilities of tools, how qualitative researchers are responding to these developments and what this means for the teaching of qualitative methods.
Mark Elliot is Professor of Data Science in the School of Social Sciences at The University of Manchester. He is a Deputy Director at NCRM.
Christina Silver is Associate Professor at the University of Surrey and Director of the CAQDAS Networking Project.
Find out about the CAQDAS Networking Project: https://www.surrey.ac.uk/computer-assisted-qualitative-data-analysis
Visit Christina Silver's LinkedIn page: https://www.linkedin.com/in/christina-qdas/
Visit Christina Silver's Linktree page: https://linktr.ee/Christina_QDA
Artificial Intelligence
Full text linkThis Methods Futures Briefing focuses on Artificial Intelligence (AI), a rapidly developing technology that will purportedly revolutionize society and science. We give an overview of recent advances, outline some potential future scenarios, and discuss the opportunities and challenges for social science that AI presents—focusing particularly on generative AI (GenAI)
NCRM Bitesize Lessons for Teaching Social Science Research Methods 6: Teaching Mixed Methods Using an Open-space Learning Approach
Full text linkOpen-space learning is a transdisciplinary approach for engaging learners and teachers in a shared exploratory space. The aim is to enhance the student experience of learning where the outcome is unknown.
This approach has roots in the University of Warwick CAPITAL (Creativity and Performance in Teaching and Learning) and Reinvention Centres and in learning theories that are learner-centred, transformative and social. A high value is placed on pragmatic real world understanding, creative teaching and embodying research
Decolonial and Anti-Racist Research Methods
Full text linkThis module presents one researcher’s approach to applying decolonial and anti-racist methods through arts-based visual techniques with asylum seekers and refugees, emphasizing reciprocity and non-exploitative relationships over traditional extractive research practices.
Dr Laura Shobiye shares her experience developing research methods inspired by decolonial theory to avoid replicating colonial power dynamics of extraction and exploitation when working with asylum seekers and refugees. Her approach uses creative visual methods including drawings, photos, and digital stories to facilitate communication beyond verbal language, while practicing ongoing reciprocity through continued community engagement, teaching, and sharing research outputs in accessible formats
Research, Education and Futures Literacy
Full text linkThis Methods Futures Briefing focuses on changes in education and the role of Futures Literacy in innovative learning approaches. It describes how social processes of teaching and learning have been transformed by technologies, interconnectivity and generational change.
Demographic transformations, specifically, will imply ongoing consideration of the diverse learning needs of different groups in terms of age, life trajectories and global cultural backgrounds and a re-design of higher education institutions. Such changes suggest that a shift in the knowledge paradigm is needed to cope with new demands and expectations in creating, accessing and implementing knowledge and the briefing outlines implications for social science and educational research approaches
Exploring Digital Life, Technology Change and Attitudes to AI through National Datasets
Full text linkThis video features presentations from three researchers on ways of exploring digital life, technology change and attitudes to AI using secondary, quantitative data from national datasets.
Athina Vlachantoni examines patterns of intergenerational digital contact before and during the COVID-19 pandemic.
Roshni Modhvadia discusses the Ada Lovelace Institute and The Alan Turing Institute’s Attitudes to AI datasets.
Mark Elliot covers a recently completed mixed methods project on the public perception of AI which combined the use of the Attitudes to AI dataset described in Roshni Modhvadia’s talk with a systematic review of research on this burgeoning topic.
The presentations were recorded for a webinar hosted by the Data Resources Training Network, titled Exploring Digital Life, Technology Change and Attitudes to AI through National Datasets, which took place on Wednesday, 19 November 2025