Bibliographic record
Abstract
IAM PLEASED AND HONOURED to present this double issue of English Studies in Canada, the very first fully shepherded issue of the journal since it moved to the University of Western Ontario in 2017. Needless to say, taking on a journal of this stature after its long and illustrious tenure at the University of Alberta has been a daunting and humbling task for the Western team, and involved a steep learning curve—but it's also been a truly rewarding experience. The opportunity to encounter and read the work of so many exciting and rigorous scholars in our field not only reinforces my commitment to our discipline, but also demonstrates, on an almost daily basis, how rich your contribution continues to be.\nWe are already working on the next number of esc, a special issue that we are hoping to publish by the end of 2019.\nWe thank you for your continued support of English Studies in Canada. We also encourage you to submit your articles for consideration; this journal depends entirely on the vibrance and curiosity of its community of scholars, and we intend to make esc an increasingly interesting and cosmopolitan home for that community's work over the next few years. We hope you'll join us in the effort. [End Page 1] Allan Pero Western University
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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 | 0.003 | 0.032 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.008 | 0.006 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.004 | 0.006 |
| Insufficient payload (model declined to judge) | 0.493 | 0.443 |
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".