Indigenous peoples: dispossession, colonisation and discrimination
Bibliographic record
Abstract
Introduction This chapter reviews the experience of indigenous peoples, that is, those who are also referred to as aboriginal or native peoples. It identifies some of the major populations of indigenous peoples living in rural areas within Westernised welfare structures, including: the Aborigines and Torres Strait Islanders of Australia; the Maori of New Zealand; the Inuit, Métis and the First Nations (Indians) of Canada and the US. Currently, the proportions of these indigenous peoples in the respective national populations are: 15% in New Zealand, 4% in Canada, 2% in Australia (Statistics Canada, 2008) and 1.5% in the US (US Census Bureau, 2002). In many countries, the recorded numbers of indigenous people have risen as more people have been willing to identify themselves as such. There are other smaller groups whose history and circumstances have similarities and who may face similar difficulties in securing justice and equitable provision in welfare services, such as Native Hawaiians and other Pacific Islanders, the Sami people of Scandinavia and, of course, other descendants of the older indigenous populations in Europe. It can be difficult to accurately establish the relative position of some of these groups, either because information is not collected or because it remains undifferentiated. This is the case with Native Hawaiians where there is a tendency to conflate data about their situation with that of other Pacific Islanders (Mokuau et al, 2008). There are different conventions and sensibilities in different countries regarding the terminology used to identify these peoples. In Australia, the capitalised term ‘Aborigine’ is widely accepted by Aboriginal people, and widely used by government departments, politicians, academics and journalists to refer to people who are native to mainland Australia and Tasmania. Aborigines are distinguished from Torres Strait Islanders originating from the islands north of Cape York, though both are Indigenous Australians. Elsewhere, even in its lower-case form, the term ‘aboriginal’ is not widely used in ordinary speech. In the US, the term ‘Red Indian’ is widely thought to be derogatory, and there has also been a move away from the use of the word ‘Indian’ to the preferred terms of ‘First Nation’ or ‘Native Americans’.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.004 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.011 | 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".