Bibliographic record
Abstract
There are only a handful of scholars who have their primary appointments in Dalhousie departments and a primary interest in medieval fields. In French, we have Hans Runte, best known among medievalists for his work on the Seven Sages of Rome, but his more recent publications have been in the field of Acadian letters. In English, we have Hubert Morgan, who works in Middle English, Old Norse, and Old English (romance, saga, and epic are particular interests), and Melissa Furrow, who has finally completed a long labour on reception of romances in medieval England (Expectations of Romance: Drasty Rymyng or Noble Tales, currently under review) and is now returning to an earlier editorial project (Ten Fifteenth-Century Comic Poems) to revise for a new edition with TEAMS. In History, we have Cynthia Neville, well known personally to members of CSM for her extensive work 011 the national and international scene on prize, review, and adjudication committees, and more broadly known through her scholarship on late medieval English legal history and on Scottish social, political, and cultural history. She is the author of Violence, Custom, and Law: The Anglo-Scottish Border Lands in the Later Middle Ages (Edinburgh UP, 1998) and the forthcoming Native Lordship in Anglo-Norman Scotland: The Earldoms of Stratheam and Lennox, 1170-1350 (Four Courts Press). A recent and exciting addition is Jennifer Bain in Music, a music theorist who works on Hildegard of Bingen, and on fourteenth-century music. This tiny number and the clearcut disciplinary boundaries proclaimed by departmental organisation might suggest that medieval study at Dalhousie has fallen off steeply from the days when we had a formally recognised honours degree in Medieval Studies and a bigger pool of faculty. It is true, a bigger pool would be helpful, and the priority within English for the next appointment is for a medievalist. But in various ways medieval studies at Dalhousie does better than it looks as if it should.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.005 | 0.001 |
| Scholarly communication | 0.010 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.812 | 0.508 |
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".