September Leactures

September Leactures -...

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Accounting for Post-communist Regime Diversity: What  counts as a good cause? 01:16 Eastern Europe and Central Asia in their post-communist regimes have diversity Civil and political rights Polarization of regime types, initially intermediate civic/political rights o Eventually became democratic o fully authoritarian I.e. – Democratic: Croatia, Macedonia, Moldova I.e. – Authoritarian: Belarus, Kyrgyzstan I.e. – Intermediate: Georgia, Russia, Ukraine Why is there no “communist legacy” o Physical, economic, social, cultural diversity o Conversely, they’re all “middle income” What we can (not) ask causal analysis to achieve in the social sciences Cant explain singular events or predict what will happen in one particular  instance o I.e. – Predicting earthquakes and weather o Cant predict singular events because: The problem of reflexivity: Precipitating self-fulfilling or self-destroying prophet Predictors try to change boundary conditions  assumed in event prediction Problem of Complexity Many different factors lead to one outcome Need to collect infinite data from obscure sources  to predict event
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Problem of Uncertainty Actors in politics faced with ambiguities of past and  present and therefore must interpret prospective  outcomes of different actions within political culture Also random, leaders are susceptible to cognitive  errors  Higher affluence -> Sharp Economic recession -> discord with authoritarian  elites -> democracy o Quite likely but still cant predict individual events with certainty o Max Weber: social sciences deals with general correlations and  causations that permit only probabilistic explanations and predictions Events result from multiple causal chains  What counts as a good cause? The “Covering law” Schema as explanation of causal analysis o Time-space invariant proposition about relationship between 2  variables and statement of empirical conditions that assert presence of  1 of the 2 terms  Facts corresponding to other term must be present too Therefore explanation is inference of observable fact from  knowledge of general relationship between antecent and  consequent variables together with empirical knowledge about  antecedent condition  o Problem: Covering law cant separate lawful (causal) and accidental  (correlation) generalizations Ontological criteria of causal analysis o 3 criteria pertaining to causal inference Temporal priority of cause vis-à-vis consequences Independence of cause from effect (Ab)normality condition Comes from comparative logic: many processes needed  to bring certain outcome, but only some cover with 
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This note was uploaded on 02/11/2012 for the course POLI 211 taught by Professor Sabetti during the Fall '08 term at McGill.

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September Leactures -...

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