Bibliographic record
Abstract
Some Creative Writing programs are meeting the demand for introductory undergraduate course offerings with large-enrolment, lecture-based courses featuring tutorial groups led by graduate teaching assistants. These courses, while allowing many more students to study Creative Writing than workshop-only courses permit, still allow the students to enjoy a small-group workshop experience. A challenge is that the instructor must essentially teach two courses: not just one in Creative Writing but also a pedagogy course for the teaching assistants. Drawing on personal experience teaching such a course at the University of Toronto that has featured nearly one hundred students and seven teaching assistants at a time, Robert McGill discusses the practices that he has developed in supporting the assistants, for most of whom the course is their first opportunity to lead a workshop. He addresses how, facing the constraint of limited training time, he has included components such as grading exercises and practice workshops to help make the tutorial groups successful and ensure safe, supportive class environments. McGill also considers his efforts to aid students in making productive use of teaching assistants’ assessments of the students’ work and of the peer feedback on it.
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.
How this classification was reachedexpand
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 | 0.005 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.028 | 0.006 |
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 itClassification
machine, unvalidatedMachine predicted; both teacher heads agree on what is shown here.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".