Writing ecological disfigurement: First Nations poetry after ‘the black grass of bitumen’
Bibliographic record
Abstract
This article examines selected First Nations poetries, showing how intertextual parodic language strategies, dynamic elegy and polyphonic poetic registers critique proleptic environmental mourning, simplistic environmental apocalypticism and compromised visions of political reconciliation – ‘all this potplanting in our sovereignty’, as Evelyn Araluen (2020b, p. 81) describes it. Alison Whittaker, Jeanine Leane, Evelyn Araluen, Ellen van Neerven, Alexis Wright and others are also shown as inheritors of the environmental-activist poetries of Oodgeroo, Kevin Gilbert and Lionel Fogarty. I analyse how each of these poets represents Country in a ‘permanently disfigured state’ (Daniels & Lorimer, 2012, p. 5), bearing witness to environments that exist after settler ‘nature’, dismantling Western theologies of poetic nature alongside. To wit, I also show how poems assert temporal vantage points outside the linear telos and material endgames of extractive colonial time, reinforcing enduring and intrinsic spiritual fealty with Country, community and ‘ancestor time’. In Ali Cobby Eckermann’s words, ‘These poems are taking the time. They are honouring the story’ (2020, p. 147).
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.012 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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".