Fictional Research Overview

Dr Leila Morgan led a fictional study into social class mobility in England. The team wanted to investigate whether young people from working-class backgrounds were moving into higher-status jobs at the same rate as those from middle-class backgrounds. Rather than using interviews or questionnaires, the researchers relied on official statistics. They analysed publicly available government data and restricted administrative datasets already collected by state agencies. Their main sources were education records, higher education participation figures, tax and earnings data, and labour market statistics. The study followed a large cohort of young people born between 1995 and 1998 and compared their backgrounds at age 14–16 with their employment outcomes at age 25.

To measure class background, the team used two official indicators: eligibility for free school meals and parental occupation categories recorded in linked census-based data. To measure mobility, they compared these indicators with later occupational position and earnings. Jobs were grouped into broad categories such as routine and manual work, intermediate occupations, and higher managerial or professional roles. The researchers also broke the data down by region, gender and ethnicity in order to see whether patterns of mobility looked different across groups.

The official statistics suggested a clear pattern. Young people from professional and managerial households were much more likely to enter university, complete a degree and move into higher-paid professional employment by their mid-twenties. By contrast, those from routine and semi-routine backgrounds were more likely to remain in lower-paid work, move in and out of insecure employment, or enter intermediate jobs without experiencing large upward mobility. The team concluded that there was some movement between class positions, but that mobility was uneven and strongly shaped by starting position. In other words, many young people were not experiencing a level playing field.

The researchers argued that official statistics were particularly useful because they offered a very large sample size. Instead of studying a few schools or a small local area, they could examine hundreds of thousands of records, making the findings more representative of patterns across England. The method also scored highly on reliability because the same categories and procedures were used across large national datasets. Since the data already existed, the study was relatively cheap compared with a long-term primary research project, although gaining access to some linked datasets involved strict application procedures and a long waiting period.

However, Morgan also highlighted important limitations. Official statistics can show patterns, but they do not easily reveal the meanings young people give to mobility, success or failure. A student moving from a working-class home into a lower-middle-class office job might count as “upwardly mobile” statistically, but the figures cannot show whether they feel secure, included or socially confident in that new position. The researchers also warned that class categories are created by governments and may simplify complex lives. Parental occupation and free school meal status are useful indicators, but they may not fully capture wealth, cultural capital or unstable family circumstances. This raises questions about validity.

There were also ethical and practical issues. Because the data was anonymised, there was little direct risk of harm to participants and no face-to-face intrusion into private lives. Yet the researchers noted that data linkage still raises concerns about privacy and state monitoring. The study also depended entirely on what government agencies chose to collect. If a variable was missing or outdated, the team could not simply ask follow-up questions. From a theoretical point of view, the research suited a more positivist approach because it focused on measurable patterns and trends. An interpretivist sociologist might criticise it for failing to capture lived experience. Overall, Morgan concluded that official statistics are strong for identifying the scale of class inequality in mobility, but weaker for explaining how mobility is experienced in everyday life.