The Janus-Face of Early Modern Literary Studies: Negotiating the Boundaries of Interactivity in an Electronic Journal for the Humanities
Bibliographic record
Abstract
In its fourth year of publication at the time of writing, Early Modern Literary Studies (EMLS) is, by many measures, accepted as an academic resource by the community it has intended from its outset to serve. Well in excess of half a million EMLS "documents" -- papers, reviews, notes, announcements, and so forth -- have been accessed by a group consisting of some 3,500 regular readers and five times that number in occasional browsers; readers access the journal from its home site, at the University of Alberta, as well as its mirror site at Oxford University and its archive at the National Library of Canada. EMLS, also, is now indexed by the MLA International Bibliography, the Modern Humanities Research Association's Annual Bibliography of English Language and Literature, and a number of other services and databases. But, while EMLS enjoys the widespread recognition that follows from our accessibility, a number of those associated with the journal also find that EMLS now faces several questions, questions associated with introspection and self-evaluation.
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 | 0.029 | 0.052 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.005 | 0.004 |
| Science and technology studies | 0.029 | 0.075 |
| Scholarly communication | 0.071 | 0.045 |
| Open science | 0.002 | 0.029 |
| Research integrity | 0.004 | 0.006 |
| Insufficient payload (model declined to judge) | 0.009 | 0.002 |
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".