Preface and Acknowledgments
Bibliographic record
Abstract
THIS BOOK IS A TRIBUTE to the longstanding work Reingard Nischik has done in Canadian and in Comparative North American Studies. It is published on the occasion of her retirement from the university— although she will continue to publish and be a voice in Canadian and Comparative Studies—and to take stock of recent work by Canadianists around the world. The focus is deliberately broad. Most pieces compare American and Canadian artifacts and range from literature to opera to visual culture. Reingard's exceptional endeavors in making Canadian literature known beyond Canada are honored by two prominent Canadian writers and academics, Margaret Atwood and Aritha van Herk, in their creative pieces in the coda to this book. Included in the coda are also a few photographs as visual testimony to a long academic journey. Both editors are former students of Reingard, and this book is also a token of their gratitude for decades of academic support and friendship. Throughout her career, Reingard Nischik has put enormous efforts into successfully promoting promising young scholars. We speak for all of them today in saying: thank you, Reingard! Books are made of great ideas and contributions but also of thorough editing, proofreading, and attention to a plethora of details. We would like to thank Florian Wagner, Caroline Bündgen, and Amanda Halter for their conscientious and efficient proofreading and formatting of this volume. Last but not least, we would like to thank Jim Walker from Camden House who, as always, has been incredibly supportive, level-headed, and competent. This book was supported by funding from the Office for Equal Opportunity, Family Affairs, and Diversity at the University of Konstanz and the German Association of Canadian Studies in German-Speaking Countries.
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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 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 0.004 |
| Insufficient payload (model declined to judge) | 0.240 | 0.152 |
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".