1Historical/Comparative Research• Seeks to discover patterns in the histories of different cultures. This research method appeals most to sociologists, political scientists, historians, and anthropologists interested in tracing the development of social forms & institutions and comparing these processes across cultures.Putting Historical/Comparative Research Into ContextResearch Methods (two general types).1: Reactive/obtrusive • Surveys, focus groups, experiments, and some field research.2: Unobtrusive• comparative/historical research, archival research, content analysisPutting Historical/Comparative Research Into Context (2)• Where do History and Sociology intersect and differ? – General (nomothetic) -- prevailing mode in sociology.– Specific (idiographic) -- prevailing mode in history.• Types of Research– explanatory -- more prevalent in sociology– descriptive -- more prevalent in history2The Rise of Historical/Comparative Research: Motivations• Political/Social Context of Social Change in the 20th Century– Totalitarianism in Germany and Russia– Transitions to socialism– Resistance movements– Nationalist movements • Early Examples (Comte, Durkheim, Marx, Weber)Historical and Archival Data• Statistical (quantitative) Data• public•private•examples–Durkheim’s study of suicide–Princeton project• Non-statistical (qualitative) Data•example–Diaries in family researchAdvantages and Disadvantages of Historical and Archival Data• Advantages– Nonreactivity, wealth of information.• Disadvantages– Representativeness– Accuracy of information– Categories or definitions are interpreted or socially constructed– Selective destruction of records3Logic of Historical/Comparative Analysis• A. Data in Comparative/Historical Analysis – Number of cases– Units of analysis– Variables• B. Use of comparisons– helps to validate theories and hypotheses.– The reason for using comparisons depends on which of the following three major types of H/C analysis is being used. Three Major Types of Comparative/Historical Analysis.• 1. Parallel Demonstration of Theory• 2. Contrast of Contexts• 3. Macro-causal Analysis1. Parallel Demonstration of Theory• Purpose - show that a theory applies in many cases• How are cases selected? - so they are different from each other• Critique - selectivity bias– Not really theory testing, but theory presenting42. Contrast of Contexts• Purpose - to show that processes are distinctive; cannot be reduced to universal principles or theory.• Selection of cases - select cases that appear to be similar• Critique - doesn’t help develop alternative explanations. 3. Macro-causal Analysis• Purpose # 1 - developing new explanations• Purpose # 2 - “setting scope conditions” for theory• Method of Agreement• Method of Difference• CritiquesMethod of Agreement• 1. Select cases with same outcome (dependent variable)• 2. Compare possible causal factors across cases• 3. Try to isolate one or a few features that are the SAME across cases• 4. Conclude that this is the causal factor producing the similar outcome• Example from Skocpol’s States and Social Revolutions5Example of Method of Agreement:Causes of Revolution in Russia, China, and FranceCause Russia China FranceDifferences: type of government, religion, level of industrialization, and other factorsState Breakdown Yes Yes Yes+ + + +Peasant Revolt Yes Yes Yes|| || || ||Revolution Yes Yes YesMethod of Difference• 1. Select cases with different outcomes (dependent variable)• 2. Compare possible causal factors across cases• 3. Try to isolate one or a few features that are DIFFERENT across cases• 4. Conclude that this is the decisive difference (i.e. the causal factor) producing different outcomes.• Another Example from Skocpol’s States and Social RevolutionsExample of Method of Difference:Causes of Revolution in France and GermanyCauses France Germany in 1848 Fragmented elites Yes Yes Military threat Yes Yes Village autonomy high, Yes No so peasants could revolt || || || Successful Revolution Yes No6Critiques of Macro-Causal Analysis• 1. Researcher must assume deterministic causality• 2. Measurement error – esp. in coding of ordinal and interval variables• 3. Might have multiple causes or interaction effects• 4. Unlikely that you could measure all causal factors – major omitted variable bias problems• 5. Selection on the dependent variableIntegration of Theory and Analysis• Essential link between theory development and causal analysis– Analysis of small N may not be generalizable– Theory developed w/o reference to analysis may be even less generalizable (may be completely unsupported)– Need to test theory with analysis– Need to refine theory based on findings of analytic
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