Voicing Derbarl Yerrigan as a feminist anti‐colonial methodology
Bibliographic record
Abstract
Abstract The paper voices Derbarl Yerrigan, a significant river in Western Australia, through three imperfect, non‐innocent, and necessary river‐child stories. These stories highlight the emergence of a feminist anti‐colonial methodology that is attentive to settler response‐abilities to Derbarl Yerrigan through situated, relational, active, and generative research methods. Voicing Derbarl Yerrigan influences the methodological practices used as part of an ongoing river‐child walking inquiry that is concerned with generating climate change pedagogies in response to the global climate crises and calls for new ways of thinking and producing knowledge. In particular, the authors found that voicing as a methodology includes listening and being responsive to Derbarl Yerrigan's invitations, paying attention to pastspresentsfutures, and forming attachments through naming. By telling lively settler river‐child stories, this paper shows how voicing Derbarl Yerrigan is vital to open new possibilities for education and has implications for settler‐colonial contexts, where the focus on learning shifts from learning about the world to learning to become with multispecies river worlds.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| 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 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".