Relational ontology and more-than-human agency in Indigenous Karen conservation practice
Bibliographic record
Abstract
Conservation scientists increasingly recognise the value of Indigenous knowledge in conservation practice. However, studies of Indigenous knowledge and resource management systems have often tended to overlook the role and agency of more-than-human beings and ceremonial protocols in mediating human–environment relationships. This paper presents results from community-based research with Karen communities in the Salween Peace Park, an innovative Indigenous-led conservation initiative in the autonomous Karen territory of Kawthoolei, on the border between Thailand and Burma, or Myanmar. Our findings detail ways in which relations with more-than-human beings, including spirits, constitute environmental governance in Karen communities. These findings compel externally situated conservation biologists to take relational ontologies seriously, allowing local interlocutors’ lived experience, knowledge, and theory to challenge culturally bound concepts such as resources, management, and conservation. In order to transform conservation biology through Indigenous perspectives, it is essential to pay attention to the relational world in which many Indigenous Peoples live. Doing so helps support a conservation practice attentive to the interdependence of all life in ways that uphold Indigenous Peoples’ rights of self-determination, cultural identity, and social relations with their ancestral lands. We argue that attending to these relations is essential to building community-based conservation collaborations with Indigenous Peoples that are more effective, sustainable, and just.
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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 | 0.006 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.008 | 0.051 |
| Scholarly communication | 0.006 | 0.006 |
| Open science | 0.001 | 0.009 |
| 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".