Upsetting Fake Ideas: Jeannette Armstrong's Slash and Beatrice Culleton's April Raintree
Bibliographic record
Abstract
Both novels expose the "fake idea" that Aboriginal people in Canada can freely choose their identities. The dominant discourse forces a choice on them: assimilate or vanish. Those who refuse the choice face harsh racism. In April Raintree, April assimilates and her sister commits suicide; both "choices" forced on them by racism. In Slash, the hero realizes that it is crucial to retain his identity as an Okanagan person rather than to exhaust himself as an activist. Both novels end with a baby who will be raised in the traditions of his culture. Activism is seen as a dangerous choice for those too young to understand their identity.
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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 | 0.003 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.024 | 0.022 |
| Scholarly communication | 0.012 | 0.005 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.004 | 0.008 |
| Insufficient payload (model declined to judge) | 0.005 | 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".