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@@ -23,7 +23,7 @@ This RoBERTa model is fine-tuned to classify course records into the appropriate
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  More information about the fine-tuning process is available here:
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-       Annaliese Paulson, Kevin Stange, and Allyson Flaster. (2024) *Classifying Courses at Scale: a Text as Data Approach to Characterizing Student Course-Taking Trends with Administrative Transcripts*. [Working Paper](https://drive.google.com/file/d/19WO_qsVVMcpLZB4jhokxxF-qi6EQC2A1/view?usp=sharing)
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  The model is fine-tuned on data formatted as "{SUBJECT CODE} {CATALOG NUMBER} --- {COURSE TITLE}". For example, for a course offered in an economics department with subject code "ECON", course number "101", and course title "Principles of Microeconomics", the model anticipates the following string: "ECON 101 --- Principles of Microeconomics." [This](https://colab.research.google.com/drive/1iebZ_Zznpv3XPgF34LmwFozd7fSg0ZCh?usp=sharing) Colab Notebook provides a short vignette applying the model.
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  More information about the fine-tuning process is available here:
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+        Annaliese Paulson, Kevin Stange, and Allyson Flaster. (2024). *Classifying Courses at Scale: a Text as Data Approach to Characterizing Student Course-Taking Trends with Administrative Transcripts.* (EdWorkingPaper: 24-1042). Annenberg Institute at Brown University. https://doi.org/10.26300/7fpas433
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  The model is fine-tuned on data formatted as "{SUBJECT CODE} {CATALOG NUMBER} --- {COURSE TITLE}". For example, for a course offered in an economics department with subject code "ECON", course number "101", and course title "Principles of Microeconomics", the model anticipates the following string: "ECON 101 --- Principles of Microeconomics." [This](https://colab.research.google.com/drive/1iebZ_Zznpv3XPgF34LmwFozd7fSg0ZCh?usp=sharing) Colab Notebook provides a short vignette applying the model.
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