02 Section A, Key question 1 - Theory and methods (part 1)

Theory, data and provenance

A researcher's view of the social world influences what they want to discover and what they accept as evidence.

A theory is an organised explanation of social life. A method is a way of collecting or analysing evidence, such as a questionnaire, an interview or observation. Methodology concerns the reasoning behind using methods: what kind of knowledge they can produce and why that knowledge answers the research question. A questionnaire asks a set of questions; an interview involves a conversation; observation records what people do in a setting.

Suppose researchers want to understand unequal opportunities at school. One asks whether access to a quiet study space is associated with examination results across many pupils. Another asks what studying at home feels like to pupils who share crowded rooms. The topic is similar, but the questions require different evidence. A list of grades cannot by itself explain what sharing a room means to a pupil; a detailed account from one pupil cannot establish how common the experience is nationally.

Data type is a different distinction from provenance, which means where evidence comes from. Primary data are collected by the researcher for the current investigation. Secondary data already exist and are reused by the researcher. Neither distinction tells us automatically whether the evidence is good.

The distinction depends on the evidence actually produced. An interview can ask for a numerical age as well as a detailed story. A questionnaire can offer fixed response choices and an open space for explanation. Researchers can also turn descriptions into counts by coding them into categories, although the categories may lose some detail. Choosing a method does not settle the data type once and for all.

Positivism and interpretivism are methodological perspectives. Positivists generally seek measurable regularities that can help explain social behaviour. Interpretivists emphasise understanding the meanings through which people act. These preferences influence research designs, but there is no absolute rule that every positivist uses only numbers or every interpretivist uses only words. A mixed-methods design combines methods, potentially using group comparisons to establish the extent of an inequality and interviews to investigate its meaning.

Positivism, patterns and trends

Positivists seek systematic evidence of regularities in social life rather than relying on a few memorable personal experiences.

Positivism treats social behaviour as something that can be investigated using systematic, scientific procedures. Social circumstances may influence what individuals do even when those individuals are unaware of the influence. Researchers therefore look for patterns: recurring relationships or distributions in evidence. They also look for trends: changes in a measure over time. A comparison between groups at one point in time is not, by itself, a trend.

For example, a researcher might propose that pupils with better home study resources tend to achieve higher examination results. This is a hypothesis, a testable proposition. To investigate it, the researcher needs clear measures of resources and attainment, evidence from relevant pupils and a way to compare the results. Operationalisation means turning an abstract idea into something that can be measured. Home resources might be measured by access to a quiet room, while attainment might be measured by an examination score. Those are choices, not complete descriptions of either concept.

Consider these invented results for two separate annual pupil cohorts in an imaginary school system. The same group definitions and examination standard are used in both years. Each percentage refers to pupils within that resource group and year; these are illustrative figures, not a real research finding.

There is a pattern in both cohorts: a larger proportion of the group with more resources achieves the standard. There is an upward trend in each group's attainment, because both percentages rise by five percentage points. However, the attainment gap stays at twenty percentage points. Improving results do not necessarily mean narrowing inequality. Because these are separate cohorts, the figures also do not show that the same pupils improved.

Numerical data make these comparisons possible because the researcher measures people using common categories. They can establish the size or distribution of a difference. But an association, meaning that two characteristics occur together, does not establish that one caused the other. Other circumstances, such as school provision, may influence both resources and attainment. An explanation needs further evidence, not merely a visible gap.

A real source suitable for this kind of investigation is the Department for Education's 2024/25 Key Stage 4 performance release. It reports attainment for pupils at the end of Key Stage 4 in state-funded schools in England, including breakdowns by disadvantage status. Its methodology explains how examination records and school census characteristics are combined. An independent sociologist reusing these published figures would be analysing secondary quantitative data. The figures could support a positivist investigation, but official statistics do not automatically prove a positivist explanation.

Objectivity and value freedom

Objectivity and value freedom are aims for disciplined research, but using numbers does not remove every researcher choice.

Objectivity means trying to make findings depend on evidence and procedures rather than the researcher's personal preferences. A positivist can pursue it by using clearly defined measures, asking the same questions in the same way, explaining how the data were analysed and reporting evidence that challenges the hypothesis. Other researchers can then scrutinise the reasoning. Objectivity is an aim to work towards, not a property guaranteed by a large table.

Value freedom means seeking to keep personal moral or political judgements from deciding the research findings. A factual conclusion about what happens is different from a judgement about what ought to happen. A researcher may show that an attainment gap exists. Whether a government should prioritise reducing that gap also involves values about fairness, resources and competing goals.

A concern about injustice may motivate someone to study school inequality. That motivation does not automatically make the findings wrong. The important issue is whether the investigation permits evidence to challenge the researcher's expectations. A researcher who expects a funding policy to improve attainment must report credible evidence of no improvement if that is what the investigation finds.

Objectivity and value freedom overlap, but they are not identical. Objectivity concerns the grounding of knowledge in evidence; value freedom concerns the relationship between empirical inquiry and value judgements. Neither is exclusively a concern of positivists: researchers using qualitative evidence can also explain their decisions and examine interpretations that contradict their initial expectations.