Bibliographic record
Abstract
HI S CO LLECTI ON OF ESS A YS had its origins in an idea that took shape when I was in German y in 1992.After a Canadian Literature conferenc e in Trier, I travelled to various universities in Germany, giving talks on the subject.Interest in Canadian literature in Germany seemed high.Many people came and listened and asked questions , and discussions were lively.On one of my stops, I spent some time with Geoffrey Davis, who taught English literature at RWTH Aachen, and who was also one of the editors of a literature series at Rodopi.He suggested we do a book along the lines of what I had done on Margaret Laurence , and I pick the subject.My immediate thought was to do a book on a French Canadian writer, because I wanted the French-German-English connection to be forefronted , instead of just another antholog y on a Canadian writer.I thought of an English language writer with French Canadian roots, whose subjects were French Canadian but who was read in English Canada and the USA.Mavis Gallant struck me as the ideal subject for our European-Canadian collection of essays.Mavis Gallant was born in Montreal in 1922, and moved to Paris while young, where she has lived since.For over four decades she has been writing English-language stories, for the most part first published in the New Yorker.She has become one of Canada's major writers .Her subjects -the subjects of her fiction -are frequently European, but also French Canadian, Acadian .She has a perspective on both that is unique.One of the things that interested me most about Mavis Gallant as a writer, about her fiction and placement , is a curious slippage that occurs -both in Gallant studies, and in reading Gallant.Her work is hard to Kristjana
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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 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.263 | 0.157 |
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".