Replication Data for Generative Dynamics of Supreme Court Citations: Analysis with a New Statistical Network Model by Schmid, Chen, and Desmarais
<|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:'R-Code and data sets of Generative Dynamics of Supreme Court Citations: Analysis with a New Statistical Network Modelby Schmid, Chen, and Desmarais.AbstractThe significance and influence of US Supreme Court majority opinions derive in large part from opinions' roles as precedents for future opinions. A growing body of literature seeks to understand what drives the use of opinions as precedents through the study of Supreme Court case citation patterns. We raise two limitations of existing work on Supreme Court citations. First, dyadic citations are typically aggregated to the case level before they are analyzed. Second, citations are treated as if they arise independently. We present a methodology for studying citations between Supreme Court opinions at the dyadic level, as a network, that overcomes these limitations. This methodo' . 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" : ["US Supreme Court, majority opinions, citations, network, ERGM"]} <|eot_id|>
 Here is the Description of a dataset. Description:'R-Code and data sets of Generative Dynamics of Supreme Court Citations: Analysis with a New Statistical Network Modelby Schmid, Chen, and Desmarais.AbstractThe significance and influence of US Supreme Court majority opinions derive in large part from opinions' roles as precedents for future opinions. A growing body of literature seeks to understand what drives the use of opinions as precedents through the study of Supreme Court case citation patterns. We raise two limitations of existing work on Supreme Court citations. First, dyadic citations are typically aggregated to the case level before they are analyzed. Second, citations are treated as if they arise independently. We present a methodology for studying citations between Supreme Court opinions at the dyadic level, as a network, that overcomes these limitations. This methodo' . Please return only a json list of at most 3 Keywords corresponding to the Description:.
R-Code and data sets of Generative Dynamics of Supreme Court Citations: Analysis with a New Statistical Network Modelby Schmid, Chen, and Desmarais.AbstractThe significance and influence of US Supreme Court majority opinions derive in large part from opinions' roles as precedents for future opinions. A growing body of literature seeks to understand what drives the use of opinions as precedents through the study of Supreme Court case citation patterns. We raise two limitations of existing work on Supreme Court citations. First, dyadic citations are typically aggregated to the case level before they are analyzed. Second, citations are treated as if they arise independently. We present a methodology for studying citations between Supreme Court opinions at the dyadic level, as a network, that overcomes these limitations. This methodo
US Supreme Court, majority opinions, citations, network, ERGM