Replication Data for: Embedding Regression: Models for Context-Specific Description and Inference
<|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:'Replication Data for: 'Embedding Regression: Models for Context-Specific Description and Inference'. All necessary data and estimated models are available in the following Dropbox folder: https://www.dropbox.com/sh/7al371qtr9102qq/AADKhjhYgnFCxOOQaugQloTBa?dl=0Keep in mind the folder is quite large at 12.59 GB.Paper Abstract:Social scientists commonly seek to make statements about how word use varies over circumstances—including time, partisan identity, or some other document-level covari- ate. For example, researchers might wish to know how Republicans and Democrats diverge in their understanding of the term “immigration.” Building on the success of pretrained language models, we introduce the `a la Carte on Text (conText) embed- ding regression model for this purpose. This fast and simple method produces valid vector represe' . 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" : ["word embeddings"]} <|eot_id|>
 Here is the Description of a dataset. Description:'Replication Data for: 'Embedding Regression: Models for Context-Specific Description and Inference'. All necessary data and estimated models are available in the following Dropbox folder: https://www.dropbox.com/sh/7al371qtr9102qq/AADKhjhYgnFCxOOQaugQloTBa?dl=0Keep in mind the folder is quite large at 12.59 GB.Paper Abstract:Social scientists commonly seek to make statements about how word use varies over circumstances—including time, partisan identity, or some other document-level covari- ate. For example, researchers might wish to know how Republicans and Democrats diverge in their understanding of the term “immigration.” Building on the success of pretrained language models, we introduce the `a la Carte on Text (conText) embed- ding regression model for this purpose. This fast and simple method produces valid vector represe' . Please return only a json list of at most 3 Keywords corresponding to the Description:.
Replication Data for: 'Embedding Regression: Models for Context-Specific Description and Inference'. All necessary data and estimated models are available in the following Dropbox folder: https://www.dropbox.com/sh/7al371qtr9102qq/AADKhjhYgnFCxOOQaugQloTBa?dl=0Keep in mind the folder is quite large at 12.59 GB.Paper Abstract:Social scientists commonly seek to make statements about how word use varies over circumstances—including time, partisan identity, or some other document-level covari- ate. For example, researchers might wish to know how Republicans and Democrats diverge in their understanding of the term “immigration.” Building on the success of pretrained language models, we introduce the `a la Carte on Text (conText) embed- ding regression model for this purpose. This fast and simple method produces valid vector represe
word embeddings