Clarifying Blackness in Anglo-Native Fictions: Tom Spanbauer’s Cross-Ethnic Borrowings
Bibliographic record
Abstract
Anglo writer Tom Spanbauer’s The Man Who Fell in Love with the Moon (1991) and American-Indian author Sherman Alexie’s Reservation Blues (1995) illustrate how contemporary multicultural literature uses Jim Crow figures as reference points for sorting intricate social lines among other ethnic groups. Spanbauer also illustrates the related dangers of cross-ethnic pilfering. The Man Who Fell in Love with the Moon (1991) de l’écrivain anglophone Tom Spanbauer et Reservation Blues (1995) de l’auteur amérindien Sherman Alexie illustrent comment la littérature multiculturelle contemporaine utilise les chiffres sur Jim Crow comme points de référence pour trier les classes sociales complexes chez d’autres groupes ethniques. Spanbauer illustre aussi les dangers liés à l’appropriation d’autres groupes ethniques.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.005 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 teacher head, 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".