<i>Paddling Her Own Canoe: The Times and Texts of E. Pauline Johnson (Tekahionwake)</i>, by Veronica Strong-Boag and Carole Gerson
Bibliographic record
Abstract
Papers of the Bibliographical Society of Canada 38/2 hand to disconnected facts "about" the world' (II4).It involves finding the personal significance in shared narratives and using that meaning socially.Writing she defines as just one more aspect of performance, helping prepare listeners to appreciate the tailoring of the story to a particular occasion.Talking on the Page has some wonderful moments.The Dauenhauers recount how when they read back his story to the late Tom Peters of Teslin, he exclaimed, 'It's been years since I've heard a story like that!'and then added, 'Let me tell you the rest of it' (16).Chamberlin quotes geographer Peter Usher's account of a Tsimshian challenge to government foresters: 'If this is your land, where are your stories?' (74).A number of the authors emphasize the ongoing work that stories do rather than the events they convey; helpful editing then becomes editing that participates in that work, according to the needs of that cultural community.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.018 | 0.008 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.027 | 0.005 |
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".