For Cambridge OCR A Level Sociology, students need to understand how sociologists use research methods in the context of social inequalities. The OCR specification includes quantitative and qualitative data, mixed methods, triangulation and methodological pluralism, and asks students to consider the uses of research methods when studying social inequalities.
The Mixed Methods Mission helps students move beyond simply defining questionnaires, interviews, statistics or observations. Instead, students build a research design by selecting one quantitative method and one qualitative method for a particular inequality topic.
This matters because different methods give sociologists different types of evidence. Quantitative methods, such as official statistics or questionnaires, can show broad patterns and trends. For example, they might show differences in pay, health, employment, poverty or educational outcomes. Qualitative methods, such as interviews, ethnography or observations, can reveal meanings, experiences, emotions and everyday barriers.
The key concept in this activity is triangulation. This means using more than one method or source of evidence to improve the quality of the research. A sociologist might use official statistics to show that a gender pay gap exists, then use interviews to explore how women experience promotion barriers, part-time work or caring responsibilities. The first method gives breadth; the second gives depth.
The activity also introduces methodological pluralism. This means being open to using different methods rather than assuming that one approach is always best. Positivists may prefer quantitative methods because they can produce reliable and representative data. Interpretivists may prefer qualitative methods because they can produce valid data about meanings and lived experiences. A mixed-methods design can combine both strengths.
This activity is aimed at higher-level students because it requires them to make a judgement. They must choose a quantitative method, choose a qualitative method, explain why the combination works, and evaluate the design. Strong answers should refer to validity, reliability, representativeness, generalisability, ethics, access, gatekeeping and life chances.
Mixed Methods Mission
Build a mixed-methods research design by selecting one quantitative method and one qualitative method. Then judge whether your combination improves the study through triangulation.
Mission: Gender pay inequality
Step 1: choose one quantitative method
Quantitative methods are useful for patterns, trends, reliability and representativeness.
Step 2: choose one qualitative method
Qualitative methods are useful for meanings, experiences, validity and verstehen.
What does your combination add?
Quantitative contribution
Choose a quantitative method to reveal its contribution.
Qualitative contribution
Choose a qualitative method to reveal its contribution.
Triangulation judgement
Check your design to reveal a judgement.
Research links
- ONS — useful for official statistics on earnings, employment, health, housing and population trends.
- Joseph Rowntree Foundation — useful for poverty, class inequality and social policy.
- Runnymede Trust — useful for race, racism and institutional inequality.
- Marmot Review — useful for health inequalities and social determinants of health.
- Centre for Longitudinal Studies — useful for cohort studies and life-course research.
Write your mixed-methods justification
Write 4–5 sentences explaining why your two chosen methods work together. Include the words triangulation and methodological pluralism.
Revision table: mixed methods and triangulation
| Combination | What the quantitative method adds | What the qualitative method adds | Triangulation judgement |
|---|---|---|---|
| Official statistics + interviews | Broad patterns and trends. | Lived experience and meanings. | Strong because it combines breadth and depth. |
| Questionnaires + ethnography | Comparable responses from a larger group. | Observation of behaviour in context. | Strong, but it may be time-consuming. |
| Statistical data + content analysis | Patterns across areas or groups. | Insight into representations, language or documents. | Useful where inequality is both material and cultural. |
| Survey + interviews | Measures how common an issue is. | Explains why it happens and how it feels. | Useful for evaluating validity and representativeness together. |
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