Claims:a statement about the world Descriptive claim:about the way the world is/was -No explicit statements about causation -May be about correlation Causal claim:about effect one thing has/had on another thing -About the CAUSE of something Causal verbs: cause, influence, leads to, increase... Prescriptive/Normative Claims:about what should or shouldn't be done -Value laden claims • Bases for Claims Non-science bases of claims Authority:arguing a claim is true because a person in authority said it was Common sense:something is true because "everyone knows" or "it just is" Personal experience:something true because of personal observation (non-systematic) Attributes of the Scientific Method -Transparent procedure -Systematic use of evidence -guided by clear rules/principles -Limits scope for cherry picking evidence -Tests out hunch against alternatives -open to being wrong -Acknowledge uncertainty Counterfactual:A statement about what would have happened if a specific feature of the world had been different The causal claim "C is a cause of E" means: If C had not happened, then E would not have happened (counter-factual) Structural Events -Long term underlying events -Conditions which are difficult to change -Necessary for the outcome to occur Triggering Events -Short events -Only cause outcome in conjunction with structural factors -Substitutable Necessary conditions Sometimes our causal claims take the form: -"Condition C must happen for outcome E to emerge." -Condition C = necessary condition for E.
Sufficient conditions A cause that ALWAYS produces an effect. -A fire is sufficient to cause heat. -Social science examples? TEND TO BE RARE BECAUSE SO MUCH CAUSATION IS CONJUNCTURAL (REQUIRES MORE THAN ONE CONDITION) Conjectural:A and B causes E Multiple:A or B or C causes E Causal chain:C-> e1 -> e2 -> e3 -> E e1 and e2 and e3 cause E? OR C cause E Causal Mechanisms/logic:A set of statements about HOW or WHY a cause produced its effect usually involves a causal chain that logically connects the cause to the effect C ~> e1 ~> e2 ~> e3 ~> E Also includes assumptions What do we need to believe is true about the world or believe the steps in the logic? Casual statement Causal logic how you explain more in depth Common causal mechanism:motivated reasoning -People seek to satisfy goals in gathering and interpreting information about the world -Accuracy is just one goal -Another key goal: seeing the world as we prefer/believe it to be → psychological pleasure -People are emotionally attached to prior beliefs -Search for information, recall of facts, and use of lines of reasoning that reinforce prior beliefs Deterministic causal claim:A claim about what must happen or cannot happen as a result of particular causal conditions. -The outcome cannot happen when the cause is absent -Necessary or sufficient conditions claims are deterministic claims Examples: If a country builds a large army, it will go to war. High rates of gun ownership cause high rates of gun violence Probabilistic causal claim:A claim that cause makes an outcome more (or less) likely to occur. High inflation makes rebellion more likely to occur. High rates of gun ownership increase the likelihood of gun violence. Probabilistic claims are about affecting the likelihood of an event, not that a cause might have an effect on something Right: High inflation makes rebellion more likely to occur -Wrong: High inflation likely makes rebellion occur
Explanation -for our purposes "explanation" meanscausalexplanation -Generally focused on understanding what has already happened -Explanatory modelsare applied to data in order to test hypothesis inspired by a causal theory linking cause (X) to effect (Y) Prediction -generally focused on predicting an outcome (Y) in new or future observations, given a set of input values (X) -Prediction models include any method that produced predictions, regardless of underlying approach -Distinction is akin to that between "basic" and "applied" science What is common? Both represent attempts to understand the world, and in particular to map out associations between variables -Both require amodel. -Often these models are statistical in nature, but they need not be -Predictions on 2016 in readings are based on statistical models."WFT Rule" isn't Both can stand or fall based on how good that model is, including (among other things) whether or not it makes reasonable assumptions Specific: Explains a case The decline of the Canadian Labour Congress caused economic inequality to go up in Canada since 1980. General: Explains a class of phenomena Declining trade unions cause inequality to rise in liberal welfare states Hypothesis: A specific, testable expectation about empirical reality that follows from a more general proposition. a statement about the empirical relationship that ought to exist between X and Y if the researcher's theory is correct. Whatever data we collect could fail to support a hypothesis in two ways: 1) We don't find the differences we were looking for within the data 2) Even if we DO find a relationship in the data, this result may have happened by chance even when there is no more general relationship. Either because of... Random guessing in a choice task (Lady Tasting Tea); Random measurement error, OR; Random sampling error in case selection BOTH of these possibilities are contained in theNull Hypothesis(H0), which is a statement about the relationship that ought to exist between X and Y if the researcher's theory is false. Induction: The logical model in which general principles are developed from specific observations.
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