Editing as Cultural Practice in Canada
Bibliographic record
Abstract
This collection of essays focuses on the varied and complex roles that editors have played in the production of literary and scholarly texts in Canada. With contributions from a wide range of participants who have played seminal roles as editors of Canadian literatures—from nineteenth-century works to the contemporary avant-garde, from canonized texts to anthologies of so-called minority writers and the oral literatures of the First Nations—this collection is the first of its kind. Contributors offer incisive analyses of the cultural and publishing politics of editorial practices that question inherited paradigms of literary and scholarly values. They examine specific cases of editorial production as well as theoretical considerations of editing that interrogate such key issues as authorial intentionality, textual authority, historical contingencies of textual production, circumstances of publication and reception, the pedagogical uses of edited anthologies, the instrumentality of editorial projects in relation to canon formation and minoritized literatures, and the role of editors as interpreters, enablers, facilitators, and creators. Editing as Cultural Practice in Canada situates editing in the context of the growing number of collaborative projects in which Canadian scholars are engaged, which brings into relief not only those aspects of editorial work that entail collaborating, as it were, with existing texts and documents but also collaboration as a scholarly practice that perforce involves co-editing.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.034 | 0.022 |
| Scholarly communication | 0.018 | 0.003 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 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 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".