Bibliographic record
Abstract
Points of Departure MORE THAN THIRTY YEARS AGO—in 1985—Reingard M. Nischik coedited a book that, despite its modest title Gaining Ground , was in fact ground breaking . It blazed a trail for Canadian Literary Studies in Europe while the field back home was still in the process of becoming part of the institutional grid. The volume, which Nischik co-edited with the renowned Canadian author and scholar Robert Kroetsch, brought together seventeen European critics from seven countries and provided insights on topics ranging from Canadian Postmodernism to “Found” Poetry. While the main thrust of the book was comprised of in-depth studies of individual Canadian authors and their works, its second part, written by Reingard Nischik, assessed the state of Canadian Studies in Europe by giving an overview of academic activities and publications as well as programs and institutions focusing on Canadian Literature in European countries. Nischik's first stocktaking laid the groundwork for much subsequent research in European Canadian Studies and became a milestone that is still frequently referenced today, see, for instance, Beyond “Understanding Canada”: Transnational Perspectives on Canadian Studies (Tanti et al., 2017). Nischik's motivation was “to make better known to an international audience how [and to what extent] Canadian literature is treated in Europe” (Kroetsch and Nischik 1985, 250). And indeed, Gaining Ground achieved in Europe what Margaret Atwood's Survival: A Thematic Guide to Canadian Literature (1972) did in Canada: it put Canadian Literature on the map and charted the territory of what was at the time still shaky ground. The book was greeted enthusiastically on both sides of the Atlantic and considered “a breakthrough in the academic acceptance of Canadian literary studies abroad” (Keith 1986, 158). Not only did it testify to the quality of work European scholars had done on Canadian literature; it also made its Canadian readers reflect on their own creative and critical practices and traditions. Frank Moher thus considered it “an engrossing, and exotic, exercise in seeing ourselves as others see us” (1986, 44), while Renate Usmiani urged: “The book should make Canadian scholars sit up and take notice” (1986, 236). Such Canadian self-consciousness and (literary) soul searching, although even more dominant in the 1960s and ‘70s, was still paradigmatic for the time of Gaining Ground 's publication— and is not surprising given the comparatively recent emergence and institutionalization of both Canadian literature as such and Canadian Studies as a field.
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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 | 0.002 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.005 | 0.003 |
| Scholarly communication | 0.012 | 0.006 |
| Open science | 0.003 | 0.005 |
| Research integrity | 0.005 | 0.004 |
| Insufficient payload (model declined to judge) | 0.407 | 0.233 |
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".