An introduction in 3 parts: Anthropological perspectives on the shooting of Kumanjayi Walker
Bibliographic record
Abstract
This is an introduction in three parts.In the first part, I introduce this Special Issue, the briefs that led to its realisation, some of the key themes the contributors wrestle with, and the contributions themselves.The second part is more of a personal introduction; namely, an ethnographic narrative of my own experience of the first hours and days following the shooting.My aim here is to take the reader into the field at the beginning of the events that unfolded from a Yuendumu view (inherently different from the perspective presented by the media and the courts).In the third introductory perspective, I look at the nature of fear.In a series of short ethnographic vignettes, I explore how police and Warlpiri people's fears differed and overwrote each other.I contextualise Warlpiri fears by situating the shooting in an historical timeline with frontier massacres.The main thrust of my enquiry is to lay bare the opposition between Warlpiri people's views and those of the settler colony, and to analyse the power of the settler colony to legitimise its fears and make Warlpiri fears illegible.I conclude by pondering the continuing looming threat of settler-colonial violence in Warlpiri lives from the vantage point of the 'Red House', the place where the shooting occurred.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.008 | 0.005 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.010 | 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".