Talking across worlds: The ontological turn and communication in natural resource co-management with Indigenous communities
Bibliographic record
Abstract
The ontological turn in critical social theory provokes emerging calls for new approaches to natural resource management where Indigenous perspectives, worldview, knowledges, and values are prioritized in the stewardship of Indigenous lands. Yet, scant literature focuses on the ontological implications for communication within environmental decision-making, where Habermas' communicative action theory, with its norms of privileging argumentation, formality, expertise, institutional authority, rationality, and language, continues to shape spaces of public participation since the communicative turn in the 1990s. Growing calls for participatory decision-making, as well as the mounting failures of scientific management approaches espoused by conventional natural resource management, have fuelled the rise of co-management since the 1980s. The emerging emphasis in co-management approaches on community collaboration and meaningful communication was strengthened with the emergence of adaptive co-management and adaptive governance in the early 2000s. Yet, the ontological turn unveils communicative tensions which continue to persist, rooted in ontological difference and onto-epistemic violence. Rethinking communication under the ontological turn in co-management with Indigenous communities, this paper reviews the literature and further proposes the idea of ethical equivocation as a communicative tool and starting point toward learning to talk across worlds.
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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 | 0.013 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.014 | 0.077 |
| Scholarly communication | 0.014 | 0.018 |
| Open science | 0.002 | 0.016 |
| Research integrity | 0.005 | 0.005 |
| 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".