Escaping Authenticity’s Dark Side: How Indigenous Groups Negotiate Indigeneity During Contentious Interactions
Bibliographic record
Abstract
Indigenous movement scholarship identifies two primary approaches to claiming indigeneity, strategic essentialism and decolonization, a binary that constrains Indigenous agency by suggesting that Indigenous actors must conform to settler expectations in the short term while postponing decolonization to a later stage. We broaden this perspective by looking at indigeneity from the perspective of constructed authenticity theory, which helps us reveal alternative agentic strategies for claiming identity. We examine how Indigenous leaders, animal rights activists, and policymakers debated Indigenous rights and identity by analyzing claims made during a Canadian summit on fur harvesting. Our findings reveal a clash between non-Indigenous authenticity claims, imposing rigid stereotypes, and Indigenous claims grounded in internal values and self-determination. Polarization persisted until Indigenous leaders reframed authenticity through historical and territorial connections, opening space for dialogue. Our study contributes to Indigenous movement scholarship by showing how different authenticity claims either reinforce settler constraints or foster Indigenous agency.
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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 | 0.010 | 0.017 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.022 | 0.051 |
| Scholarly communication | 0.012 | 0.009 |
| Open science | 0.002 | 0.013 |
| Research integrity | 0.003 | 0.004 |
| 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".