“To See Together Without Claiming to Be Another”: Stories as Relations, Against One-Direction Mode of Indigenous Stories Travelling
Bibliographic record
Abstract
Once communities’ stories are taken up by researchers and shared within the ivory tower of academia, the stories circulate within the ivory tower. It is often the case that these archived stories from communities are used by researchers, without asking permission from the communities where the stories originate. In this article, we aim to critically review and reflect on underlying theories and practices in conventional Eurocentric academia that allows for a ‘one direction’ mode of storytelling dissemination, allowing researchers to take the ‘version’ of community knowledge and/or stories without seeking the original approval from the communities themselves. We suggest ‘thoughtful’ questions for both settler and Indigenous researchers to consider in hopes of promoting ‘travelling back to original sources’ in their scholarly work.
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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 | 0.028 | 0.041 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.021 | 0.120 |
| Scholarly communication | 0.022 | 0.027 |
| Open science | 0.003 | 0.018 |
| Research integrity | 0.006 | 0.009 |
| Insufficient payload (model declined to judge) | 0.003 | 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".