Songspirals as care infrastructure: binding human and more-than-human worlds in and as sky Country
Bibliographic record
Abstract
With and as Bawaka Country (North East Arnhem Land), we share how sky Country and Yolŋu people are connected by, and co-become through, a multidimensional, multidirectional infrastructure of care. We discuss what care means, from a Yolŋu ontology, looking to the way a Yolŋu care infrastructure emerges through and as wetj (sharing), märr (love) and raki (a string that binds everything through relationships and responsibilities). One of the many ways that a Yolŋu infrastructure of care manifests is when it is sung and enlivened through songspirals. Songspirals sing the land and its many relations into being. In this paper, we are guided by the Guwak songspiral that holds and maintains important relationships between people, Milŋiyawuy, the river of stars, and sky Country. Bawaka Country, Rrawun Maymuru who is Wäŋa Wataŋu, custodian, of the Guwak songspiral and Guwak itself lead the paper. Guwak shows how wetj, märr and raki co-become as a complex Yolŋu infrastructure of care, connecting human and more-than human beings all the way to the heavens. As we follow Guwak, we elaborate on what it means to care as Country, and consider the complex ways that care infrastructures might guide more-than-human kinship and responsibility.
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.
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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.013 | 0.048 |
| Scholarly communication | 0.007 | 0.006 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".