5. The Unfairness of Life Chances

About this Lecture

Lecture

In this lecture, we put together the methods we have considered thus far to think about unfairness in educational opportunities and wider society, focusing in particular on: (i) some key factors shaping inequality; (ii) problems with three main sources of numerical data on social stratification – occupational status, income, and FSM eligibility; (iii) an example of how FSM data can be used effectively – by comparing the exam results of long-term FSM-eligible pupils with those of all other pupils; (iii) how the reduction in the attainment gap between these two groups relates to the decline in segregation between schools and the pupil premium policy.

Course

In this course, Professor Stephen Gorard (Durham University) explores the use of numerical data in education research. In the first lecture, we think about why numbers are important in sociology and whether the distinction between qualitative and quantitative research is useful. In the second lecture, we look at comparing frequencies between groups. In the third lecture, we look at identifying differences between groups – with examples from education research. Next, we examine the concepts of correlation and causation by exploring the relationship between Free School Meal eligibility and attainment in school exams. In the fifth and final lecture, we put these different methods together to discuss more broadly the unfairness of life chances.

Lecturer

Professor Stephen Gorard is Professor of Education and Public Policy and Director of the Evidence Centre for Education at Durham University. He has written very widely on educational inequalities, education policy, and research methods. His recent publications include How to Make Sense of Statistics (2021), How Can We Get Educators to Use Research Evidence? (2019, co-author), and Education Policy: Evidence of Equity and Effectiveness (2018).