‘Witnessing the Violence of the Settler State in Alexis Wright’s Carpentaria and Lee Maracle’s Celia’s Song’
Bibliographic record
Abstract
A Canadian literary scholar based in Australia, I read “Aboriginal/Indigenous” Australian and Canadian literatures in English as sites where the ways in which we perceive racial and cultural violence might be re-configured. Cognizant of the role that literary studies discourse has had and continues to have in these nations as a tool for the maintenance of official, state-recognised ‘reconciliation’ narratives, my work looks instead to the literary encounter itself as a potential site for registering, or witnessing, the violence that the settler state attempts to screen off behind the scenes of its official attitudes towards reconciliation. This article will explore the concept of literary witnessing in an archive of trans-Indigenous literature across settler colonial states, linking award-winning authors Alexis Wright (Waanyi, writing in Australia) and Lee Maracle (Sto:lo, writing in Canada). Analysing Wright’s Carpentaria and Maracle’s Celia’s Song, I trace how these novels enact and inspire, but also complicate, witnessing in Canada and Australia (both of which maintain official policies of inclusion and multiculturalism, but are actually held up by a regime of continuing racialized violence). I also examine how these works of literature model ignorance and choosing to turn away as a form of violence and a roadblock to justice. Finally, I ask how these novels might provide models for subjectivity and justice that subvert the judiciary systems of these settler states, dislodging ‘witnessing’ from its place in discourses of state-authorized “justice”, and placing it in the realm of Indigenous law and the potential of an ethical (literary) encounter.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.029 | 0.026 |
| Scholarly communication | 0.009 | 0.003 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.002 | 0.004 |
| 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".