Sociology and Demography
Lead Research Organisation:
University of Oxford
Department Name: Sociology
Abstract
In social and health sciences, 'birth cohorts' are often used as a unit of analysis. These are the set of people who are born in a single year in a population, and they are often tracked over time to understand the life-course experiences and attributes of people born in the same period. By comparison, a 'social cohort' is the set of people in a population who were ever alive during a period. They refer to the set of all people who have been exposed to certain social, political, and/or environmental circumstances, regardless of age. Social cohort analysis is rare relative to birth cohort analysis, and there is no standard set of tools for forecasting the growth and replacement of social cohorts.
As my MPhil project, I would like to produce a set of microsimulations that can answer numerous social cohort questions and begin to fill that gap. For example, a basic microsimulation could use population data to forecast what proportion of the German population had ever lived in pre-reunification Germany. A more complex microsimulation could forecast the replacement of people who lived through an event (e.g. World War II) with their children and grandchildren. Other microsimulations could be used to study population exposure to continuous variables, especially environmental ones. For example, one could model the life course burden of air pollution among people in the UK over time. By producing general, flexible models that can answer these sorts of questions, I hope to enrich the field of social cohort analysis, allowing the fledging field to engage with important questions of social and demographic change, political science, and population health.
As my MPhil project, I would like to produce a set of microsimulations that can answer numerous social cohort questions and begin to fill that gap. For example, a basic microsimulation could use population data to forecast what proportion of the German population had ever lived in pre-reunification Germany. A more complex microsimulation could forecast the replacement of people who lived through an event (e.g. World War II) with their children and grandchildren. Other microsimulations could be used to study population exposure to continuous variables, especially environmental ones. For example, one could model the life course burden of air pollution among people in the UK over time. By producing general, flexible models that can answer these sorts of questions, I hope to enrich the field of social cohort analysis, allowing the fledging field to engage with important questions of social and demographic change, political science, and population health.
Organisations
People |
ORCID iD |
Ridhi Kashyap (Primary Supervisor) | |
Hampton Gaddy (Student) |
Studentship Projects
Project Reference | Relationship | Related To | Start | End | Student Name |
---|---|---|---|---|---|
ES/P000649/1 | 01/10/2017 | 30/09/2027 | |||
2597138 | Studentship | ES/P000649/1 | 01/10/2021 | 30/06/2023 | Hampton Gaddy |