Replication Data for: Essays on the Applications of Machine Learning and Causal Inference in American Politics
<|begin_of_text|><|start_header_id|>system<|end_header_id|> You are a research archivist expert in dataset metadata. Answer the question truthfully.  <|eot_id|><|start_header_id|>user<|end_header_id|> Here is the Description of a dataset. Description:'Political science as a field prioritizes causal statements: the effects of governmental policies on societal outcomes, the effects of individual treatments on individual behaviors. Underlying these causal research questions, however, are important measurement problems. Many of the most theoretically important concepts in the field, concepts like representation, corruption, ideology, and democracy, elude straightforward definitions let alone measurement. In response, political scientists have developed sophisticated computational tools to produce cheap and objective measures, many of which leverage machine learning and big data. Today's political scientists measure Congressional ideology by scaling votes and bills and then interpreting the resultant scores. We measure rural development by examining satellite images of lights at night and' . Please return only a json list of at most 3 Keywords corresponding to the Description:.<|eot_id|><|start_header_id|>assistant<|end_header_id|> {"Answer" : ["Computational Social Science"]} <|eot_id|>
 Here is the Description of a dataset. Description:'Political science as a field prioritizes causal statements: the effects of governmental policies on societal outcomes, the effects of individual treatments on individual behaviors. Underlying these causal research questions, however, are important measurement problems. Many of the most theoretically important concepts in the field, concepts like representation, corruption, ideology, and democracy, elude straightforward definitions let alone measurement. In response, political scientists have developed sophisticated computational tools to produce cheap and objective measures, many of which leverage machine learning and big data. Today's political scientists measure Congressional ideology by scaling votes and bills and then interpreting the resultant scores. We measure rural development by examining satellite images of lights at night and' . Please return only a json list of at most 3 Keywords corresponding to the Description:.
Political science as a field prioritizes causal statements: the effects of governmental policies on societal outcomes, the effects of individual treatments on individual behaviors. Underlying these causal research questions, however, are important measurement problems. Many of the most theoretically important concepts in the field, concepts like representation, corruption, ideology, and democracy, elude straightforward definitions let alone measurement. In response, political scientists have developed sophisticated computational tools to produce cheap and objective measures, many of which leverage machine learning and big data. Today's political scientists measure Congressional ideology by scaling votes and bills and then interpreting the resultant scores. We measure rural development by examining satellite images of lights at night and
Computational Social Science