Bibliographic record
Abstract
Smaller universities can preside over profound achievements in disciplines such as medieval studies through the fostering of commitment and focus. For instance, the profile of medieval studies has developed significantly in the last three years at Wilfrid Laurier University, where, in December of 2002, an interdisciplinary program in medieval studies was approved by the university’s senate. Prior to the development of this program, medieval material was taught largely within the traditional disciplines. The new program is designed to include course subjects from a variety of national and religious traditions. It will have four core courses: History 101, Medieval Europe 500-1100; History 102, The High Middle Ages; Medieval Studies 100, Discovering the Middle Ages (Knights, Saints, and Dragons); and Medieval Studies 200, The Medieval World View. The last two courses are designed to be team-taught by faculty members from various disciplines, such as Classics, History, Religion and Culture, Music, Fine Arts, Languages and Literatures (particularly French and Spanish), and English and Film. Participating faculty members have contributed many of their existing courses and research interests to the program, together with many new ideas for lectures, fourth-year seminars, and innovations in teaching. The program will also include courses in medievalism, that is, the study of representations of medieval cultural materials within contemporary cultures and sensibilities. Though these kinds of offerings, such as a “Tolkien and Fantasy” course, are growing at Laurier and are currently more popular among students than the more traditional medieval-themed courses, the former variety of course is not pushing aside the latter. In fact, an interdisciplinary medieval studies program should help the existing medieval courses at Laurier appeal to more students.
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 | 0.000 | 0.000 |
| 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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 teacher head, 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".