Bibliographic record
Abstract
The beginnings of New Chaucer Studies: Pedagogy and Profession are found in many energetic conversations about the state of our field and our profession at the New Chaucer Society’s 2018 Congress in Toronto. Concerned about the sustainability of medieval studies, the editors imagined a journal that not only addressed these pressing issues but also helped diminish the isolation many medievalists feel. Most of all, they sought to rethink how different forms of academic labor are defined and valued. The resulting journal rests on two pillars of accessibility: open access and peer review. Available through the University of California’s eScholarship publishing platform, the journal is freely available regardless of institutional affiliation. And by encouraging a peer-review process of constructive criticism and intellectual dialogue, the journal promotes fresh perspectives. The journal’s first issue presents timely and thoughtful contributions by Anthony Bale, Andrew James Johnston, Dan Kline, and Carolyn Dinshaw.
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 | 0.007 | 0.049 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.010 | 0.006 |
| Open science | 0.005 | 0.004 |
| Research integrity | 0.007 | 0.007 |
| Insufficient payload (model declined to judge) | 0.264 | 0.165 |
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".