The Ecocritical Subtexts of Three Early-Twenty-First-Century Aussie Animal Horror Movies
Bibliographic record
Abstract
37 In his book Animal Nation (2006), Adrian Franklin highlights the ways in which Australia’s wildlife has played an important role in the negotiation of Australians’ national identity. Since Australia’s wildlife includes species native to the country, species which migrated to Australia before white settlers arrived, and species which were consciously brought to Australia by human beings, Australia’s animal kingdom ‘do[es] not represent homogeneity but a rather puzzling and unstable heterogeneity within which there are clear indications of boundaries, border disputes and even policies and practices of species-cleansing’ (2006, p. 14). In the semantic chaos surrounding Australia’s wildlife, native animals, such as the kangaroo and the koala, have been embraced as national symbols, for, as animals ‘that existed outside European taxonomic conventions’ (2006, p. 26), they have always represented ‘the strangeness and upsidedownness’ (2006, p. 26) and, thus, the uniqueness of Australia. No wonder that the Australian coat of arms features an emu and a red kangaroo, two native animals which were already charged with symbolic meaning
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.020 | 0.022 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.008 | 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".