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Today: Go over process tracing and process tracing tests; Finish up lecture on causality;

Today: Go over process tracing and process tracing tests; Finish up lecture on causality; Hand out assignment #3. Key ideas for assignment #3: Process tracing: a qualitative method of looking at data within a particular case to make inferences about that case.

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Today: Go over process tracing and process tracing tests; Finish up lecture on causality;

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  1. Today: • Go over process tracing and process tracing tests; • Finish up lecture on causality; • Hand out assignment #3.

  2. Key ideas for assignment #3: Process tracing: a qualitative method of looking at data within a particular case to make inferences about that case.

  3. Process tracing is a method that can work with only one case. It has strong parallels to detective work and the kind of reasoning that juries use in trials.

  4. Causal-process observations (CPOs): specific pieces of information or data from within a case that are useful for making judgments about causation. You can think of them as similar to “clues” about a case.

  5. For example, in the Tannenwald article, specific conversations in which foreign policy decision makers had trouble discussing nuclear use are CPOs.

  6. Data-set observation: the scores or values for a case across all systematically measured variables. This is often what we mean by a “case” when we have a rectangular dataset.

  7. Process tracing tests: • Hoop tests; • Smoking gun tests; • Straw in the wind tests; • Doubly decisive tests.

  8. All of these tests involve relating: • Specific pieces of evidence (CPOs), to • Preexisting generalizations that apply more broadly.

  9. Hoop test: Passing a hoop test is necessary but not sufficient for the validity of a given hypothesis. This kind of test can eliminate a given hypothesis but it cannot always provide strong support that the hypothesis is valid.

  10. Example Hypothesis: O.J. Simpson intentionally caused the death of Ron Goldman.

  11. Hoop test: Was O.J. in the general area at the time that Goldman was killed?

  12. Some hoop tests are harder to pass than others: • Was O.J. on the planet Earth at the time that Goldman was killed? • Was O.J. at the Nicole Brown Simpson home at the time that Goldman was killed?

  13. Failing a hoop test always eliminates a hypothesis. Passing a hoop test lends support in favor of a hypothesis only to the degree that it is a hard test.

  14. What makes a hoop test easy or hard?

  15. The difficulty of a hoop test is related to the frequency at which the CPO is typically or normally present. Hoop tests that make reference to rare CPOs are hard hoop tests. Hoop tests that make reference to common CPOs are easy hoop tests.

  16. Other hoop tests: • Is O.J. right handed? • Did O.J. have motive to carry out a violent murder? • Does O.J.’s hand fit the glove?

  17. Smoking gun test: With these tests, one has access to evidence that acts like a smoking gun in a murder investigation: the evidence is sufficient but not necessary for the validity of a given hypothesis.

  18. Smoking gun tests are used primarily to confirm the validity of a hypothesis. Failing a smoking gun test does not mean that a hypothesis is necessarily wrong.

  19. Example from O.J. investigation: Traces discovered at the crime scene included Simpson’s DNA in blood samples from footprints and the glove.

  20. Goldman’s DNA was found in Simpson’s Bronco. Nicole Brown Simpson’s DNA was found in the Bronco and on a sock in Simpson’s bedroom.

  21. The defense suggested that one of the detectives may have intentionally planted blood in Simpson’s Bronco by using the bloody glove found at Simpson’s estate.

  22. They also suggested that the DNA samples were degraded and suffered from cross-contamination.

  23. How consequential was the absence of the murder weapon for challenging the validity of the hypothesis that Simpson was the murderer?

  24. It might depend on difficult/unusual it would have been to not find the weapon.

  25. Straw in the wind test: Provides some support for or against a hypothesis, but it is not decisive.

  26. Example: Passing a hard hoop test provides straw in the wind evidence in favor of a hypothesis.

  27. Back to causality lecture . . .

  28. 4 Criteria of Causality: • Time Order • Association • Not Spurious • Mechanism

  29. (2) Association: there is a “systematic relationship” between variables or events. One kind of association: a correlation

  30. Correlation with dichotomous variables I: present Cases here Dependent Variable Cases here absent absent present Independent Variable

  31. Correlation with dichotomous variables I: present Cases here Good Grade Cases here absent absent present Studies a lot

  32. Correlation with dichotomous variables II: present Cases here Dependent Variable Cases here absent absent present Independent Variable

  33. We can also think about correlations using continuous data. High Dependent Variable Low Low High Independent Variable

  34. Example: xxx High xxxx xxxx xx xxxxxx Level of Democracy xx xxxxx x xxxx xx x x x xxx Low xxxx Low High Level of Economic Growth

  35. Please notice the relationship between the two-by-two table for dichotomous variable correlations and the scatterplot for continuous variable correlations. (I will help you notice it!)

  36. Another kind of association: a necessary condition (actually a type of asymmetrical correlation). present Dependent Variable absent absent present Independent Variable

  37. For example: present Pregnancy absent absent (Male) present (Female) Female

  38. For example: present Social Revolution absent absent present Authoritarian Government

  39. Question: How would a necessary condition look with continuous variables? Dependent Variable Independent Variable

  40. Necessary cause: powerful notion of causality because it implies that if the cause had not occurred, then the outcome would not have occurred. In that sense, the cause really seems to have “made a difference.”

  41. Counterfactual Statement: “If it had been the case that C (or not C), it would have been the case that E (or not E).” If I had eaten breakfast, I would not be hungry right now. Counterfactual because it makes a claim about the effect of an event in the past that did not happen (me eating breakfast).

  42. Always useful to ask about the counterfactual. For example: If there was no nuclear taboo, what would have happened? If systematic vulnerability did not exist, what would have happened?

  43. Problem of counterfactuals: We can never directly test them. It would require “re-running history.” Instead, we must imagine a “possible world” in which the cause did not occur.

  44. Issue: How close is the “possible world” to the real world? How much do we have to rewrite history even to imagine the possible world? Example: “If the United States did not exist, Iraq would be allied with France.”

  45. Useful counterfactuals require us to rewrite history only a little bit. But it is often hard to find such counterfactuals. Example: If McCain had won the election, the economy would be stronger right now.

  46. The problem of “over-determination” and necessary causes: Soldier 1 Soldier 2 Prisoner Dies Soldier 3 Soldier 4

  47. The problem of “preemption” and necessary causes: Two assassins shoot 5 seconds apart at a dictator. Are these actions both causes of the dictator’s death?

  48. How do we distinguish “trivial” from important necessary causes? Rule of thumb: important necessary causes are rare events.

  49. “We may define a cause to be an object followed by objects similar to the second. Or, in other words, where, if the first object had not been, the second never ceased to exist.” --David Hume

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