Decolonizing conservation? Indigenous resurgence and buffalo restoration in the American West
Bibliographic record
Abstract
There has been a recent surge of interest in “decolonizing” conservation and natural resource management fields. Most of this scholarship, however, speaks to colonialism on a global scale and does not address conservation within modern settler colonial states such as the United States and Canada. This project focuses on the reintroduction of buffalo (bison) in the American West as an example of how even conservation efforts that purport to include, value, and share Indigenous perspectives can ultimately uphold settler colonial relations of power. Using an Indigenous mixed-methodology approach, it interrogates the discursive construction of buffalo as “America's great conservation success story” and highlights the ways in which conservation has historically worked to support colonial projects of Indigenous erasure and dispossession. Some contemporary buffalo restoration projects seek to include Indigenous people as stakeholders and/or collaborators with unique cultural interests in buffalo, but these efforts do not always embody the material shift in power relations that Indigenous scholars have identified as a key component of decolonization. For Indigenous people, buffalo are more than a keystone species with cultural import; they are relatives whose well-being is deeply entwined with our own. For landscape-scale buffalo restoration projects to engage in decolonization, they must seek to not only repair the harm done to tribal nations through buffalo eradication but also work to support Indigenous resurgence by transforming structures of power.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.011 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| 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".