Bibliographic record
Abstract
The purpose of this chapter is to consider how our understanding of state crime needs to be mediated through an appreciation of colonial processes. The chapter explores a number of inter-related issues around the question of colonialism, state crime and Indigenous peoples. The historical relationship between Indigenous people and the development of modern nation states raises the problem of the extent to which contemporary liberal democracies like Australia, Canada or the US were founded on processes we would now regard as state crime, and indeed engaged in activities which at the time could have been regarded as unlawful. Further, while there has been considerable literature on transitional justice and processes for reparations in post-conflict societies, this body of scholarship has tended to ignore the extent to which liberal democracies themselves might be considered in need of 'post-conflict' reconciliation and restorative justice. This chapter explores these questions through a discussion of Australia, Canada and the US, although the primary focus is on Australia and its relationship with the continent's Indigenous peoples.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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; both teacher heads agree on what is shown here.
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".