Bridging knowledge systems to enhance governance of environmental commons: A typology of settings
Why this work is in the frame
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Bibliographic record
Abstract
We offer a typology of settings to bridge scientific and indigenous knowledge systems and to enhance governance of the environmental commons in contexts of change. We contribute to a need for further clarity on how to incorporate diverse knowledge systems and in ways that contribute to planning, management, monitoring and assessment from local to global levels. We ask, <em>what settings are discussed in the resource and environmental governance literature to support efforts to bridge indigenous and scientific knowledge systems?</em> The objectives are: 1) to offer a typology that organizes various settings to bridge knowledge systems; and 2) to elaborate on how these settings function independently and in concert, using examples from a diverse literature in addition to field research experience. Our focus is on indigenous and scientific knowledge, but the typology offers lessons to bridge diverse knowledge systems more generally, and in ways that are sensitive to a moral, political and process-based approach. The typology includes specific methods and processes, brokering strategies, governance and institutional contexts, and the arena of epistemology. We describe each setting in the typology, and provide examples to reflect on the function and potential outcomes of different settings. Insights from our synthesis can inform policy and participatory action.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it