Negotiating Indigenous knowledge at the science-policy interface: Insights from the Xáxli’p Community Forest
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Despite increasing interest in learning from Indigenous communities, efforts to involve Indigenous knowledge in environmental policy-making are often fraught with contestations over knowledge, values, and interests. Using the co-production of knowledge and social order (Jasanoff, 2004), this case study seeks to understand how some Indigenous communities are engaging in science-policy negotiations by linking traditional ecological knowledge (TEK), western science, and other knowledge systems. The analysis follows twenty years of Indigenous forest management negotiations between the Xáxli’p community and the Ministry of Forests in British Columbia (B.C.), Canada, which resulted in the Xáxli’p Community Forest (XCF). The XCF is an eco-cultural restoration initiative that established an exclusive forest tenure for Xáxli’p over the majority of their aboriginal territory—a political shift that was co-produced with new articulations of Xáxli’p knowledge. This research seeks to understand knowledge co-production with Indigenous communities, and suggests that existing knowledge integration concepts are insufficient to address ongoing challenges with power asymmetries and Indigenous knowledge. Rather, this work proposes interpreting XCF knowledge production strategies through the framework of “Indigenous articulations, ” where Indigenous peoples self-determine representations of their identities and interests in a contemporary socio-political context. This work has broader implications for considering how Indigenous knowledge is shaping science-policy negotiations, and vice versa.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.156 | 0.012 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.004 | 0.009 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.002 |
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 it