Canada as a Superpower in Elizabeth Bear’s Science Fiction: The Jenny Casey Trilogy
Bibliographic record
Abstract
English-speaking science fiction readers were impressed by Elizabeth Bear’s Jenny Casey trilogy when it appeared in 2005. Along with the high quality of the novels, Hammered, Scardown and Worldwired, the American author surprised her public by a number of features that distinguishes this trilogy from most recent American science fiction. The aim of this article is to examine two of these features more closely: Bear’s combination and revision of certain earlier science fiction genres and her depiction of a world of 2062 in which Canada and not the USA has the leading role in space exploration and global conflicts. The article uses both a comparative examination of science fiction genres and a qualitative analysis of those aspects of Canada that Bear chooses to highlight. American space fiction tends to be nationalistic, but the USA of 2062 is shown as suffering from ecological disasters that its weak and divided society cannot deal with. Canada, on the other hand, though not an ideal society, successfully upholds values like moderation, and is still able to rely on the loyalty of very different kinds of characters.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.028 | 0.022 |
| Scholarly communication | 0.008 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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".