A Trio of Voices: Interviews about American Literary Portraits of Canada with Authors Ben Farmer, Beth Powning, and P.S. Duffy
Bibliographic record
Abstract
In the wake of the recent US elections, the future of Canadian-American relations is unclear. As part of a larger SSHRC-funded exploration of American fictional portraits of Canada, the following three conversations with writers Ben Farmer, P.S. Duffy, and Beth Powning lay the foundations for a consideration of how Americans perceive and depict their northern neighbours in recently published novels. In particular, all three writers focus their attention on the Atlantic region of Canada, probing the history of the area and reflecting on its implicit and explicit relationship to its southern neighbours, locally and nationally. Yet each one attends to a specific set of concerns and a different moment in history in ways that create a potential rich conversation between and beyond the individual novels and their authors. The interviews are intended to provide primary materials to facilitate further scholarship in this area of study.
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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 | 0.007 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.005 | 0.008 |
| Science and technology studies | 0.068 | 0.033 |
| Scholarly communication | 0.015 | 0.005 |
| Open science | 0.003 | 0.006 |
| Research integrity | 0.004 | 0.009 |
| Insufficient payload (model declined to judge) | 0.004 | 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".