Poetic Tracks and Treading on Indigenous Lands: Examining Marlatt and Warland’s and Akiwenzie-Damm’s Literary Travels to Australia and Aotearoa
Bibliographic record
Abstract
This paper considers the work of poets who travel from the area of the Indigenous land of Turtle Island now known as Canada to the Indigenous territories of Australia and Aotearoa. The poets engage in different forms of movement on the land that reveal varying degrees of awareness of and respect for Indigenous sovereignty. In particular, I put “17:00 / coming into Port Pirie” and “30/5 8:50 / past Menindee” from Daphne Marlatt and Betsy Warland’s 1988 Double Negative, an understudied collection of poetry in which the lesbian poets traverse Australia by train while reflecting on travelling through “(ab) original country” (19), into conversation with Kateri Akiwenzie-Damm’s (Chippewas of Nawash Unceded First Nation/Anishnaabe) “from turtle island to aotearoa,” the final poem in Akiwenzie-Damm’s 1993 collection My Heart is a Stray Bullet, in which she enacts a nation-to-nation relationship with the Māori people through “slow cautious steps” (50) upon their lands. Using Eve Tuck (Unangax̂) and K. Wayne Yang’s influential piece “Decolonization is not a Metaphor,” I discuss how the poets variously use language of movement to elide complicity in settler colonialism and settler mobility or, as is the case with Akiwenzie-Damm, honour Indigenous forms of movement and relationships to their lands.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.019 | 0.019 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 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".