Bibliographic record
Abstract
Links between people, their land, and culture need to be acknowledged “Indigenous” has a number of usages that differ from “to be born in a specific place,” which is how the Concise Oxford Dictionary defines it.1 These usages tend to define indigenous by the experiences shared by a group of people who have inhabited a country for thousands of years, which often contrast with those of other groups of people who reside in the same country for a few hundred years. A number of alternative terms are preferred to indigenous. For example, in Australia, Aboriginal and Torres Strait Islander is appropriate and acceptable. In Canada and the United States, the term First Nations is used to describe the Indian, Metis, and Inuit populations, whereas in Hawaii, native Hawaiian finds favour. Many groups prefer their own language. The Maori of New Zealand use “Tangata Whenua” or “people of the land” in preference to Maori used by the colonising Victorian English who, unaware of its meaning (ordinary or common), ironically deemed the indigenous population to be the ordinary inhabitants, rendering themselves extraordinary in the process.2 Te Ahukaramu Charles Royal, a recent Maori recipient of the Churchill fellowship for overseas study, offers an attractive definition of indigenous based on what he calls …
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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 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.004 | 0.013 |
| Scholarly communication | 0.002 | 0.006 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.009 | 0.015 |
| Insufficient payload (model declined to judge) | 0.006 | 0.002 |
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".