Bibliographic record
Abstract
The Department of English at McGill University has recently lost two of its medievalists, one to early retirement and one to another institution (a decision made largely for personal reasons), and for several years has had no specialist in medieval drama. The Department now has only two full-time medievalists, with the result that its offerings in medieval literature have fallen off somewhat. A few years ago, the Department also made the effort to change all its courses to 3-credits. The 6-credit introductory course in Old English thereby fell away, as did student interest. However, we have managed to keep an Old English course going at the upper level, and a new, 300-level, 3-credit Introduction to Old English is being offered next year, in the hopes of being able to offer both the introductory course in Old English and the upper-level course as a follow-up. The Department over the past few years has maintained its offerings in Chaucer, as well as in other medieval topics (gender, religion, folklore, Arthurian tradition, and literary theory); this year we were able to put on Chaucer at both the undergraduate and graduate level, an Old English undergraduate course, and two upper-level undergraduate courses in Middle English literature (on allegory and on romance). We have approval to advertise for a position in Late Medieval/Early Renaissance, which we hope we will be able to fill next year. The Department now has a very strong Renaissance studies component (especially in Shakespeare), and we are hoping to boost our medieval offerings by creating a bridge with the Renaissance.
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 machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.002 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.359 | 0.032 |
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; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".