Healing Wounds: (Unsolicited) Tricksters Creating Balance Within Their Communities
Bibliographic record
Abstract
While previous scholarship holds that the trickster figure is a marginal figure on the outskirts of a society, this study reexamines that interpretation and proposes a new way to look at the trickster and its relationship with the community. Specifically, the texts considered—Toni Morrison’s Sula, Ishmael Reed’s Flight to Canada, Eric Gansworth’s Smoke Dancing, and Thomas King’s Green Grass, Running Water—are out of African American and Native American traditions respectively. The communities and tricksters within these four novels exhibit different types of communal relationships. In this study I present the idea of internally focused communities and externally focused communities, both of which determine how the trickster behaves within the community. Sula and Smoke Dancing act as insular texts, with their communities internally focused and their tricksters mediating intra-communal conflicts to heal the communities’ wounds. Flight to Canada and Green Grass, Running Water act as expansive texts, with their communities externally focused and their tricksters mediating the relationships between their own communities and the dominant cultures of the outside world in order to restore balance and begin a healing process.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.012 | 0.020 |
| Scholarly communication | 0.008 | 0.007 |
| Open science | 0.001 | 0.012 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.006 | 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".