The Demographic Science Unit, in collaboration with the ESRC Centre for Care, is developing an ambitious database that will enable systematic analysis of every recorded political debate on Health and Social Care in the United Kingdom. Covering both the House of Commons and the House of Lords, it spans centuries of parliamentary history and millions of utterances, acting as a resource which provides unparalleled opportunities to understand how elite political discourse has shaped the governance of critically important healthcare policies. Importantly, the database is linked to supplemental characteristics, such as biographical and professional information of parliamentarians, life peers, and beyond. There exists scope for further linkage over time.
We expect the DPhil candidate to play a key role in the in the analysis of the debates using advanced natural language processing techniques. We encourage the candidate to apply these methods to uncover long-term patterns in how health and social care have been discussed. The candidate will then work on linking patterns uncovered in the speeches to actual changes in health and social care related legislation, resource allocation, and policy, as well as to prevalent health concerns and problems at the population level. This prospectively allows us to quantitatively track the interactions between population health, parliamentary health discussions, and health policy. The research will illuminate how discourse influences policy trajectories and how political structures condition heath governance in the UK. Finally, we expect the candidate to explore the possibility of creating similar databases and analyses for other legislatives bodies such as the EU Parliament, German Bundestag or the USA Congress.
The project opens up a diverse array of related analytical questions: How does party affiliation affect sentiment, themes, or legislative strategy? Are there differences in the overall focus on health and in the salience of different health policy areas as a function of parliamentarian’s gender, age, region, professional background, or educational attainment? What contrasts exist between elected representatives in the Commons and appointed peers in the Lords, and how has this changed over time? These are illustrative examples, but the candidate will retain flexibility to pursue specific lines of inquiry aligned with their expertise and interests.
While the foundational work of database construction, data linkage, and the development of initial models will be completed before the candidate begins, they will be fully involved in designing and executing models, testing hypotheses, and advancing new methodological approaches.
The successful applicant will become a fully integrated member of the Demographic Science Unit, one of the core units of Oxford Population Health. They will benefit from a collaborative, interdisciplinary environment. In addition to project-specific training, they will have access to further skill development and computational resources, including the auditing of advanced courses across the University, particularly in Statistics and Computer Science.
We seek applicants with demonstrable experience in data science and natural language processing, as well as strong general purpose Python programming skills which underpins this. Experience with relational databases such as PostgreSQL is desirable, but not essential. Familiarity with large language models is advantageous, as is a substantive interest in UK politics and health policy, though the latter is by no means a formal requirement.
Applicants should make contact with one of the prospective supervisors - Charles Rahal - prior to making an application. He and potentially the wider team will hold (informal) brief 15-minute meetings with all interested and qualified applicants to discuss their proposals. As part of all applications to the DPhil (and relevant to this project), applicants should explicitly mention this project and the prospective supervisors in their statement of purpose. Formal online interviews will be held for admission into this position; the date of the interviews is to be confirmed, but likely late January or early February 2026.