Canadian children's literature Local Color, Universal Problems: The Novels of
Bibliographic record
Abstract
from Shore (1980), and Thirty-six Exposures (1984). He has created distinctive fiction by combining local color and the universal problems of adolescence. Major is not, however, simply an author giving novelty or quaintness to the "problem novel, " a form that usually chronicles the tribulations of the urban teenager. He is, in fact, quite critical of much adolescent fiction. In an interview published in Books ¡n Canada, he said, "I find many of the novels shallow and too pre-packaged. The writers have a tendency to choose a highly topical problem, like anorexia nervosa or homosexuality, and then build a story around it. Novels should be relevant and readable in years to come—which I doubt many of them will be " (24). In an attempt to avoid the limitations of the typical adolescent novel while still retaining its audience appeal, Major has tried to make the Newfoundland setting itself one source of conflict.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.023 | 0.009 |
| Scholarly communication | 0.005 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.016 | 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".