The Need for Indigenous Voices in Discourse about Introduced Species: Insights from a Controversy over Wild Horses
Bibliographic record
Abstract
Culture, livelihoods and political-economic status all influence people's perception of introduced and invasive species, shaping perspectives on what sort of management of them, if any, is warranted. Indigenous voices and values are under-represented in scholarly discourse about introduced and invasive species. This paper examines the relationship between the Xeni Gwet'in First Nation (one of six Tsilhqot'in communities) and wild or free-roaming horses in British Columbia, Canada. We outline how Xeni Gwet'in people value horses and experience management actions, contextualising the controversy over wild horses amidst power imbalances in the expression of environmental values. We suggest that Indigenous voices are vital to include when evaluating impacts of controversial species and developing management strategies.
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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 | 0.011 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.025 | 0.050 |
| Scholarly communication | 0.015 | 0.010 |
| Open science | 0.002 | 0.009 |
| Research integrity | 0.003 | 0.006 |
| Insufficient payload (model declined to judge) | 0.002 | 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".