“Speche of thynges smale”: Micro-College Medievalism at Algoma University College
Bibliographic record
Abstract
The phrase “medieval studies” is virtually meaningless at a small school such as Algoma University College. One faculty member out of the entire faculty complement of just over 30 is a specialist in a medieval discipline, Medieval English Literature (especially Chaucer), and though AUC does have a handful of courses on medieval topics on its books (e.g. History of Medieval Europe, Medieval Philosophy), the only ones offered regularly are the upper-year Chaucer courses. Courses in medieval drama and romance are on the books, but only the drama course has been offered, and only as a Directed Studies course. Library holdings are so sparse that even many major texts (literary and critical) are available only through inter-library loan, and most major (and all minor) journals focusing on medieval studies are not in our holdings (we receive exactly three medieval-focused journals here, and Florilegium is not, I regret, among them). Research on medieval topics is therefore and of necessity difficult, requiring long delays as inter-library loan materials trickle in, as well as extensive travel to other sites. Furthermore, few students take courses focusing on medieval topics, and even fewer of them acquire an abiding love for the subject that carries them forward to careers as medievalists. Indeed, in my years at AUC, not a single student (to my knowledge) has pursued graduate studies in any medieval discipline. The preservation, let alone the nurturing and growth, of medieval studies, is extremely difficult under such circumstances. One might imagine that a rewarding, or even an interesting, career as a medievalist would be impossible under such circumstances.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.018 | 0.005 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.012 | 0.001 |
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".