Bibliographic record
Abstract
Sovereignty is an often invoked, yet notoriously misunderstood and misused term in relation to the political, territorial, cultural and economic needs, aspirations, and goals of Indigenous peoples living in post-colonial settler states. Archives were established as places where official records became anchors for nations in the making as they documented the accepted demise of their first peoples. As a result, the archival imagination is both a process of political work and ideological maneuvering. In the post-colonial imagination, archives have become hotbeds for revising the historical fictions and fantasies that allowed for the erasure and presumed demise of Indigenous peoples. As archives shift to include Indigenous voices, and as Indigenous archives assert their own prominence in the landscape, the archival imagination expands. This article analyzes the emergent archival imagination through the lens of sovereignty, repatriation movements, and digital technologies to expose the place of Indigenous rights, histories, and imaginations in the practical work of archives in post-colonial settler states. Using examples from my own collaborations in the United States and Canada with Indigenous communities and my work as the director of Mukurtu CMS, I examine how multiple stakeholders grapple with and infuse archival practices, tools, and work with the many nuances of sovereignty.
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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 | 0.014 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.029 | 0.119 |
| Scholarly communication | 0.026 | 0.020 |
| Open science | 0.002 | 0.022 |
| Research integrity | 0.004 | 0.006 |
| 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".