Replication Data for: 'Understanding delegation through machine learning: A method and application to the European Union.'
<|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:'Delegation of powers represents a grant of authority by a legislature to one or more agents whose powers are determined by the conditions in enabling statutes. Extant empirical studies of this problem have relied on labor-intensive content analysis that ultimately restricts our knowledge of how delegation has responded to politics and institutional change in recent years. We present a machine learning approach to the empirical estimation of authority and constraint in European Union (EU) legislation and demonstrate its ability to accurately generate the same discretion measures used in an original study directly from all EU directives and regulations enacted between 1958-2017. We assess validity by training our classifier on a random sample of only 10% of hand-coded provisions and replicating an important substantive finding. While our ' . 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" : ["Delegation","European Commission","European Union","Machine Learning","Text Analysis"]} <|eot_id|>
 Here is the Description of a dataset. Description:'Delegation of powers represents a grant of authority by a legislature to one or more agents whose powers are determined by the conditions in enabling statutes. Extant empirical studies of this problem have relied on labor-intensive content analysis that ultimately restricts our knowledge of how delegation has responded to politics and institutional change in recent years. We present a machine learning approach to the empirical estimation of authority and constraint in European Union (EU) legislation and demonstrate its ability to accurately generate the same discretion measures used in an original study directly from all EU directives and regulations enacted between 1958-2017. We assess validity by training our classifier on a random sample of only 10% of hand-coded provisions and replicating an important substantive finding. While our ' . Please return only a json list of at most 3 Keywords corresponding to the Description:.
Delegation of powers represents a grant of authority by a legislature to one or more agents whose powers are determined by the conditions in enabling statutes. Extant empirical studies of this problem have relied on labor-intensive content analysis that ultimately restricts our knowledge of how delegation has responded to politics and institutional change in recent years. We present a machine learning approach to the empirical estimation of authority and constraint in European Union (EU) legislation and demonstrate its ability to accurately generate the same discretion measures used in an original study directly from all EU directives and regulations enacted between 1958-2017. We assess validity by training our classifier on a random sample of only 10% of hand-coded provisions and replicating an important substantive finding. While our 
Delegation; European Commission; European Union; Machine Learning; Text Analysis