Learning to care for Dangaba
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
Abstract In a Kimberley place-based cultural story, Dangaba is a woman whose Country holds poison gas. Her story shows the importance of cultural ways of understanding and caring for Country, especially hazardous places. The authors contrast this with a corporate story of fossil fuel, illustrating the divergent discourses and approaches to place. Indigenous and local peoples and their knowledge, cultures, laws, philosophies and practices are vitally important to Indigenous lifeways and livelihoods, and critically significant to the long-term health and well-being of people and place in our locality, region and world. We call for storying and narratives from the pluriverse of sociocultural voices to be a meaningful part of environmental education and to be implemented in multiple places of learning. To know how to hear, understand and apply the learnings from place-based story is to know how to move beyond a normalised worldview of separation, alienation, individualism, infinite growth, consumption, extraction, commodification and craving. To know how to see, feel, describe and reflect upon experience, concepts and practice is to find ways to move towards radical generosity, mutuality of becoming, embodied kinship, wisdom, humility and respect.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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