Scalable, scaffolded writing assignments with online peer review in a large introductory economics course
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Despite widely acknowledged benefits of integrating writing into economics courses, instructors’ costs are often prohibitive. To reduce costs and make writing assignments more feasible, the authors describe multi-part, scaffolded writing assignments developed by an economist and a WAC (Writing Across the Curriculum) specialist, integrated into an 800-student introductory economics course with multilingual students and TAs. Students draft and revise an abstract and later draft and write an op-ed with a convincing economic argument for a general audience. The authors use writing centers and peer review software to provide feedback while reducing grading time, and train inexperienced TAs to evaluate student writing through detailed rubrics and moderated marking sessions. They provide detailed assignment descriptions and an accounting of resources and time needed to grade each assignment.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.016 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it