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Methods, Measurement, and Research Design in Sociology

Manual: General · Subject: Sociology

This lesson examines how sociologists operationalize concepts, design studies, and infer causality across qualitative, quantitative, mixed, and computational approaches.

Inference and Identification

From Concepts to Measures

Sociological concepts such as class, race, legitimacy, cohesion, stigma, and institutional trust are abstract and often contested. The methodological challenge is to convert these concepts into valid measures without collapsing their richness. Graduate-level work demands explicit attention to construct validity, measurement invariance, reliability, endogeneity, and the logic of inference.

Major Research Strategies

StrategyStrengthLimitation
Survey researchBroad generalizabilityMeasurement error and nonresponse
EthnographyHigh contextual depthLimited external validity
ExperimentsStrong causal identificationSometimes constrained realism
Administrative dataLarge scale and precisionOften limited conceptual richness
Computational methodsCan analyze trace and digital dataRisk of black-box inference
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Measurement Principle

If the construct is socially contested, validity depends on theory, not just statistical fit.

Which issue most directly threatens causal inference in observational sociology?

What does construct validity refer to?

Qualitative and Quantitative Logics

Qualitative vs Quantitative Inference

Qualitative research

  • Identifies meanings, processes, and context
  • Useful for mechanism discovery
  • Often relies on purposive sampling

Quantitative research

  • Estimates associations and effects
  • Useful for generalization and modeling
  • Often relies on probabilistic sampling and statistical assumptions

What is a major advantage of ethnography in sociological research?

A Pragmatic Mixed-Methods Workflow

  1. 1

    Step 1: Use qualitative work to refine concepts and mechanisms.

  2. 2

    Step 2: Build a measurement strategy and sampling frame.

  3. 3

    Step 3: Estimate patterns with quantitative data.

  4. 4

    Step 4: Return to cases to interpret anomalies and mechanisms.

  5. 5

    Step 5: Triangulate findings across data sources and levels.

Why is measurement invariance important in comparative sociology?