Curating Dissent: Indigenous Artistic Interventions as Counter-Narratives in Settler-Colonial Archives
Bibliographic record
Abstract
Settler-colonial archives have historically functioned as instruments of state power, perpetuating narratives that erase or marginalize Indigenous peoples' histories, knowledges, and sovereignties. This study investigated the growing phenomenon of contemporary Indigenous artistic interventions within these institutions, framing them as critical acts of "curating dissent" that challenge the archival claim to objective truth. This research employed a qualitative, comparative case study methodology to analyze three distinct, institutionally-sanctioned artistic interventions in major settler-colonial archives in Canada, Australia, and New Zealand between 2020 and 2024. A multi-modal data collection strategy included visual analysis of the artworks, textual analysis of archival records, and thematic analysis of 25 semi-structured interviews with artists, curators, and community members. The analysis revealed three primary strategies of intervention: (1) "Re-contextualization and Juxtaposition," which disrupts colonial classifications by placing Indigenous epistemologies alongside archival records; (2) "Embodied Knowledge and Affective Encounters," which uses performance and sensory elements to reanimate ancestral connections within the archive; and (3) "Digital Sovereignty and Archival Remixing," which leverages digital tools to reclaim and re-narrate colonial documents. Institutional responses ranged from enthusiastic collaboration to forms of negotiated resistance and containment. In conclusion, within the specific context of sanctioned projects, Indigenous artistic interventions function as potent decolonial practices that create new spaces for Indigenous knowledge and memory to flourish. This study proposes the concept of "Archival Acupuncture," a theoretical framework for understanding how these targeted, therapeutic interventions can systemically alter the narrative body of the archive to foster restorative justice. These acts signal a critical shift, demanding archives become active partners in a more just future.
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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 | 0.015 | 0.020 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.020 | 0.035 |
| Scholarly communication | 0.009 | 0.004 |
| Open science | 0.003 | 0.013 |
| Research integrity | 0.002 | 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".