Fishing facts and phishing fictions on K'gari (Fraser Island): Archaeological discourse in a post‐truth world
Bibliographic record
Abstract
ABSTRACT As a discipline, archaeology must explore ways to present Indigenous and scientific interpretations of the past, employing mechanisms that are effective and relevant to contemporary Indigenous people, and which communicate values for the future that are shared by Indigenous and non‐Indigenous peoples alike. Inclusive archaeological discourse and cultural heritage management can amplify First Nations voices and contribute to the public debate on the contemporary understanding of Australia's past. In developing new ways to explore archaeological relevance to First Nations people, but also working to prevent the loss of intellectual property, archaeologists in partnership with First Nations people can forge new ways to research and communicate ideas and scientific data. The contemporary story of K'gari (Fraser Island, south‐east Queensland) and the effective harnessing by Butchulla people of modern media strategies to assert their ongoing custodial and cultural rights and diminish colonial constructs imposed upon them is a powerful example of innovative resilience and positive social change.
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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 | 0.005 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.026 | 0.029 |
| Scholarly communication | 0.008 | 0.006 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.005 | 0.005 |
| Insufficient payload (model declined to judge) | 0.006 | 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".