Big Gubba Business: The making of the United Nations Declaration of the Rights of Indigenous Peoples, First Nations resurgence and the Australian connection
Bibliographic record
Abstract
Incorporating a significant component of Yarning-based oral history, Big Gubba Business investigates the making of the United Nations Declaration on the Rights of Indigenous Peoples (UNDRIP) from an Aboriginal Australian standpoint. This study examines the dynamics of the global Indigenous resurgence and interrogates the evolution of the Indigenous/UN relationship. First Nations engagement with the UN system and participation at the 1993 UN World Conference on Human Rights are explored in detail. Big Gubba Business also unravels the ongoing self-determination debate and the rise of the CANZUS bloc of resistant States. Having established the political context and surveyed the cultural landscape, this study identifies and analyses the actions and achievements of Indigenous Australian representatives in the drafting, elaboration and eventual adoption of the UN Declaration on the Rights of Indigenous Peoples. Big Gubba Business finds that the principal value of the Declaration derives from its role as a rallying point and common cause for First Nations activists and theorists. The legacy of the Declaration project includes the building and embedding of a worldwide network of Indigenous organizations and an enhanced First Peoples political and intellectual presence on the world stage. It is hoped that Big Gubba Business will serve to direct academic attention to this neglected domain of political activity and inform a wider public of the nature and importance of the Indigenous/UN relationship.
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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 | 0.006 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.014 | 0.016 |
| Scholarly communication | 0.008 | 0.005 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 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".