Hearing, voicing and healing: Rivers as culturally located and connected
Bibliographic record
Abstract
Abstract In this article, a collaborative writing group explores how we, two rivers, express ourselves over time, place and space, our energies long interpreted as veins and arteries carrying the Country's life affirming blood. Voiced as River: I, River, this position reflects a worldview in which interrelationship with living river is normal, and River Spirit is ever‐present. It is a position underpinned by Indigenous narratives as riverine expressions of place‐based love. At times, the article is also voiced as a writing group or individuals, with voices being interchanged where required for smooth reading. We see this as part of the decolonising process, which feels liberating and healing among the writers. Each writer is equally valued as co‐creator, contributor, narrator and story teller. The two rivers, being Martuwarra Fitzroy River (Kimberley, Western Australia) and Unamen Shipu Romaine River (North Shore, Québec, Canada), illustrate a common condition of being, through heritage, life, change and possibility. Through stories and voices, the socio‐scientific implications of colonisation and lost connections become clear, considering the interaction, the dialogue and the cultural synthesis of living water systems that have always incorporated all life forms into rivers of life. As a way of navigating towards wholeness, Aboriginal knowledge systems and narratives for healing are used to bring together findings of this intercultural river learning journey.
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 | 0.005 | 0.008 |
| 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 | 0.031 |
| Scholarly communication | 0.015 | 0.007 |
| Open science | 0.002 | 0.010 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 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".