Bibliographic record
Abstract
In light of the ongoing practice of non-Indigenous researchers conducting studies on Indigenous lands, new opportunities are needed for creative alternatives to fieldwork, along with an honest conversation about ethics, intent, and practices of place-based collaborative methods in Indigenous studies. In this paper, I explore the notion of story-listening as a creative methodological alternative to extractive methods for settler scholars in Indigenous communities. Through personal reflection, I argue that decolonizing research strategies should involve practices which minimize settler presence in, and demands on, Indigenous communities. A storied approach to research points to academic expectations of knowledge-production, which contribute to silencing Indigenous voices, while paradoxically setting Settler researchers as a privileged audience of Indigenous stories. Looking for told-but-unheard stories, I argue, is one way to find answers and guidance in research while respecting storytellers’ agency and challenging colonial origin stories. Methodological ideas for unheard stories are explored in three phases: hearing, listening, and sharing. All stages of story-listening involve care and respect for the storyteller.
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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 | 0.022 | 0.021 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.023 | 0.053 |
| Scholarly communication | 0.010 | 0.013 |
| Open science | 0.004 | 0.013 |
| Research integrity | 0.006 | 0.008 |
| Insufficient payload (model declined to judge) | 0.005 | 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".