Transforming the Planetary Health Crisis Through an Indigenous Land-Based Meta-Narrative
Bibliographic record
Abstract
Abstract Our current biodiversity, pollution, climate change, and pandemic crises are deep and complex yet have similar underpinnings and a clear road map out. Indigenous Peoples have long asserted the importance of their enduring and dynamic relationship to ancestral lands, seas, waterways, and wildlife as a protective road map for people and the planet. As we are all dynamic beings with the potential for direct kinship relationships to all planetary elements ranging from the micro to the macro level, it leaves open the possibility of large-scale and emergent positive change. This means that as action-based planetary relatives, we can all enact great change around us by precipitating these emergent processes within our own bodies and in the environment around us. Therefore, we provide an interconnected narrative that centers Land and Country, our Ancestors, and story as we consider the path we need to walk going forward. We premise that the story we need to co-walk is an ecologically derived one with the complexity of the world expressed through the simplicity of being of Nature.
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How this classification was reachedexpand
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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.019 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 teacher head, 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".