Global indigenous studies in the first world: some reflections and epistemological matters
Bibliographic record
Abstract
Indigenous studies in First World nation states such as Australia, Canada, New Zealand, the United States of America and Hawaii, appear to have acquired the status of a discipline, although the accounts of its formation vary. Indigenous studies is formally recognised as part of university curricula in these countries and is included in inter‐disciplinary contexts and degree programs or is offered as a program and a degree in its own right. Indigenous scholarship is being published in unprecedented numbers with publishing houses competing for manuscripts. Indigenous studies journals have proliferated having emerged in the 1970s though most were, and continue to be, edited by non‐Indigenous people. In addition, Indigenous studies professional associations have been established organising research related activities as well as convening conferences to enable intellectual engagement and the formation of national and international networks. The nature and extent of this institutionalisation and the conditions of existence, though often marginalised and under resourced, may allude to the coherence of Indigenous Studies as a discipline with global reach but what remains unclear are its epistemological boundaries and the degree to which it perpetuates cultural entrapment . This paper will reflect on some of these epistemological matters.
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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 | 0.024 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.008 |
| Science and technology studies | 0.016 | 0.075 |
| Scholarly communication | 0.018 | 0.019 |
| Open science | 0.003 | 0.015 |
| Research integrity | 0.007 | 0.012 |
| Insufficient payload (model declined to judge) | 0.003 | 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".