| Project Supervisor | Mark Williams |
| Institution & Department | Queen Mary University of London – School of Business and Management |
| Research Area | RA 2: Business Analytics, Management, and Applied Economics |
| Project Start Date | July 2026 – flexible start date offered. |
| Project Duration | 3 months |
| Application Deadline | 4th June 2026 |
| Working Pattern | Full-time (5 days per week over 3 months) |
| Working Arrangements | Hybrid |
| We will try to have both in-person and remote meetings as is mutually convenient. | |
| How to Apply | View Guidance Here |
Project Description
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Influential research on higher managerial and professional occupations observed that those from working class origins earn approximately 17 per cent less than those from upper middle class origins. Inequalities remain substantial when controlling for qualifications, occupation, and other factors.
The aim of this project is to investigate: Has pay inequality according to social class origin decreased, stayed the same, or increased over the last half century?
This is an important question because it sheds light on whether high paying occupations are becoming less or more open to those from lower social origins. Theoretical augments can be made for an opening up thesis, a trendless fluctuation thesis, and an increasing social closure thesis. Careful empirical investigation is required to ascertain which perspective is the correct one.
This project has the potential for impact beyond academic research because the findings will:
• Frame current debates about “socio-economic diversity” initiatives, including the increasing practice by large employers of collecting social class origin data from recruits.
• Addresses broader debates on conflicting findings in social mobility research in the United Kingdom, and informing governmental policy.
This project analyses several large-scale datasets spanning 53 years. The main activities will be the cleaning of these datasets and statistical analysis using multivariate regression methods.
The main output will be one scientific publication published in a strong social science or human resource management journal.
The findings of the research will be disseminated to large employers and social mobility stakeholders. There will also be presentations at academic conferences and practitioner workshops.
The intern will be involved in all aspects of the project.
Internship Details
The project involves data extraction, cleaning, and analysis of at least two datasets, in conjunction with the academic lead who will do the same for at least one other dataset. The main tasks are as follows:
- Cleaning the datasets.
- Descriptive analysis.
- Multivariate analysis.
- Writing the academic outputs.
- Presenting the findings at conferences and workshops, including to practioners (HR professionals, policy makers)
Beyond the internship, there will be voluntary opportunities for further outputs (e.g., blog posts) and presentations (subject to supervisor approval).
To get a better understanding of the research area, read the following articles provide a good introduction:
- Laurison, D. and Friedman, S. 2016. The Class Pay Gap in Higher Professional and Managerial Occupations. American Sociological Review 81(4), pp. 668–695. doi: https://doi.org/10.1177/0003122416653602.
- Williams, M., Gifford, J. and Koumenta, M. 2025. Social Class Origin and Job Quality Among Higher Managerial and Professional Occupations in the United Kingdom. Sociology (forthcoming). doi: https://doi.org/10.1177/00380385251339592.
Anticipated Benefits for the Student
Through this internship, the student will develop the following doctoral-level research and transferable skills:
- Possibly broader knowledge of an adjacent quantitative field.
- Working with a new academic, as a part of a wider community in the Centre for Research in Equality and Diversity and the School of Business and Management at Queen Mary University of London.
- An academic publication in a world-leading social science or human resource management journal.
- Gain knowledge of a new and flexible surveys, which can be used to investigate many other research questions, especially in relation to work and employment.
Skills, Experience and Knowledge Requirements
Essential Requirements:
- Interest in the subject matter.
- Studying for a PhD using of quantitative methods (e.g., regression analysis).
- Experience of managing large-scale datasets, especially survey data.
Desirable Requirements:
- Proficient in the statistical software packages Stata or R.
- Researching socio-economic background, or other ascribed characteristics (e.g., sex, ethnicity, disability) in relation to labour market outcomes (e.g., jobs, wages, etc.).
- Ability to write and present for a practitioner audience.